diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml
index e1c623fd56f..300f47fcd08 100644
--- a/.github/workflows/test.yml
+++ b/.github/workflows/test.yml
@@ -20,7 +20,7 @@ jobs:
       matrix:
         include:
           - os: ubuntu
-            runner: ubuntu-large
+            runner: ubuntu-latest
             target: x86_64-linux
 
     steps:
diff --git a/.gitignore b/.gitignore
index 8aec0edeadc..af3a8e8beb2 100644
--- a/.gitignore
+++ b/.gitignore
@@ -22,3 +22,5 @@ result
 **/target
 !crates/nargo_cli/tests/test_data/*/target
 !crates/nargo_cli/tests/test_data/*/target/witness.tr
+!crates/nargo_cli/tests/test_data_ssa_refactor/*/target
+!crates/nargo_cli/tests/test_data_ssa_refactor/*/target/witness.tr
\ No newline at end of file
diff --git a/.release-please-manifest.json b/.release-please-manifest.json
index 64f3cdd6471..76d5538a47e 100644
--- a/.release-please-manifest.json
+++ b/.release-please-manifest.json
@@ -1,3 +1,3 @@
 {
-  ".": "0.8.0"
+  ".": "0.9.0"
 }
diff --git a/CHANGELOG.md b/CHANGELOG.md
index 9f823481b4f..830c841ddb6 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -1,5 +1,70 @@
 # Changelog
 
+## [0.9.0](https://github.com/noir-lang/noir/compare/v0.8.0...v0.9.0) (2023-07-25)
+
+
+### ⚠ BREAKING CHANGES
+
+* ACIR bytecode encoding with Base64 ([#1935](https://github.com/noir-lang/noir/issues/1935))
+* Update to ACVM 0.18.1 and implement missing brillig blackboxes ([#1914](https://github.com/noir-lang/noir/issues/1914))
+
+### Features
+
+* ACIR bytecode encoding with Base64 ([#1935](https://github.com/noir-lang/noir/issues/1935)) ([347cfc4](https://github.com/noir-lang/noir/commit/347cfc4ce2ed463b457fce9a2530cad4b06516e0))
+* Add `nargo build` as alias for `nargo compile` ([#1940](https://github.com/noir-lang/noir/issues/1940)) ([13618d4](https://github.com/noir-lang/noir/commit/13618d4bcc89079155a9fcadc3cbe2c07d2aa972))
+* add `nargo init` command ([#1859](https://github.com/noir-lang/noir/issues/1859)) ([2d87c87](https://github.com/noir-lang/noir/commit/2d87c873a286b21741736ad61fbef546b6d42b21))
+* Add ability to create a proof for a workspace member using `nargo prove -p {crate_name}` ([#1930](https://github.com/noir-lang/noir/issues/1930)) ([266126f](https://github.com/noir-lang/noir/commit/266126f89935ffe9abcecac709b7b06af36a5c95))
+* Add Acir debug information ([#1864](https://github.com/noir-lang/noir/issues/1864)) ([5ff8b53](https://github.com/noir-lang/noir/commit/5ff8b53bbb4720241768acfcb76e9866214d43c2))
+* Add multi-line comments ([#1936](https://github.com/noir-lang/noir/issues/1936)) ([cfb1765](https://github.com/noir-lang/noir/commit/cfb176562736207e5844ac16f0f941b4ee4e12d0))
+* Add support for nested arrays on brillig gen ([#2029](https://github.com/noir-lang/noir/issues/2029)) ([8adc57c](https://github.com/noir-lang/noir/commit/8adc57c77ad0012d329684781d9cbee882d0b100))
+* Add to_radix and to_bits support to brillig gen ([#2012](https://github.com/noir-lang/noir/issues/2012)) ([3eef41c](https://github.com/noir-lang/noir/commit/3eef41c752fabd1d0c989084f12cd82f81a6fa4c))
+* Add unit literals and unit types to parser ([#1960](https://github.com/noir-lang/noir/issues/1960)) ([ea80de5](https://github.com/noir-lang/noir/commit/ea80de57a57a92533b3fb545a0920bca2d74e109))
+* Adding internal keyword ([#1873](https://github.com/noir-lang/noir/issues/1873)) ([7a85493](https://github.com/noir-lang/noir/commit/7a854937ca5a300ae05f335612d2ff72ce88b4b1))
+* Allow arrays of arbitrary types in the program ABI ([#1651](https://github.com/noir-lang/noir/issues/1651)) ([811ede1](https://github.com/noir-lang/noir/commit/811ede19f2160d809904deffc09a51799448d8d6))
+* Allow shadowing by default ([#2000](https://github.com/noir-lang/noir/issues/2000)) ([88a4f74](https://github.com/noir-lang/noir/commit/88a4f74a36704137d7de94e3791c2e6bea9319b5))
+* avoid unnecessary witness assignments in euclidian division / bound constraint  ([#1989](https://github.com/noir-lang/noir/issues/1989)) ([c23257d](https://github.com/noir-lang/noir/commit/c23257d4bdd8d93b9219fd767de6d806e237ccea))
+* **brillig_gen:** Return slices from foreign calls ([#1909](https://github.com/noir-lang/noir/issues/1909)) ([6fa3144](https://github.com/noir-lang/noir/commit/6fa3144b30ef908a350273fbfd950d5a247104b2))
+* compile to brillig reachable acir fns ([#1919](https://github.com/noir-lang/noir/issues/1919)) ([2b4237d](https://github.com/noir-lang/noir/commit/2b4237d7ffc2a0246cdaa1b7d85cc1ef7d7b3eb1))
+* dynamic arrays for experimental-ssa ([#1969](https://github.com/noir-lang/noir/issues/1969)) ([08d199a](https://github.com/noir-lang/noir/commit/08d199aa4daa2038ca01f5ad23376fec27950f9a))
+* Implement parsing of traits ([#1886](https://github.com/noir-lang/noir/issues/1886)) ([3ba1e72](https://github.com/noir-lang/noir/commit/3ba1e72408b5f15cc623a4b2ca9f5c2e4b9652ae))
+* Implement references in brillig ([#1901](https://github.com/noir-lang/noir/issues/1901)) ([3a078fb](https://github.com/noir-lang/noir/commit/3a078fb9c5c5c256a767c8bd7f1312d07c8db93c))
+* initial implementation of slices in brillig ([#1932](https://github.com/noir-lang/noir/issues/1932)) ([ea47936](https://github.com/noir-lang/noir/commit/ea47936cfea201aa634432c972b71e6b89cdb513))
+* Refactor Logging to use Brillig foreign calls ([#1917](https://github.com/noir-lang/noir/issues/1917)) ([c15f9aa](https://github.com/noir-lang/noir/commit/c15f9aa8a7d21ec44e9b63e90cc83290ac96cd9c))
+* **stdlib:** Add multiple slice builtins ([#1888](https://github.com/noir-lang/noir/issues/1888)) ([008a16b](https://github.com/noir-lang/noir/commit/008a16b799f494115f028e523f9daa54fd8f476f))
+* **stdlib:** Add secp256r1 builtin function   ([#1858](https://github.com/noir-lang/noir/issues/1858)) ([f3800c5](https://github.com/noir-lang/noir/commit/f3800c52c81a27d3b52cfe23f45e764234b1c268))
+* **stdlib:** Vec type ([#1905](https://github.com/noir-lang/noir/issues/1905)) ([3734e25](https://github.com/noir-lang/noir/commit/3734e2554661567a77e7a18d91134b2d521a5c06))
+* Update to ACVM 0.18.1 and implement missing brillig blackboxes ([#1914](https://github.com/noir-lang/noir/issues/1914)) ([2bc7d25](https://github.com/noir-lang/noir/commit/2bc7d25271ca8c375a54d00116f507857b4b79ae))
+
+
+### Bug Fixes
+
+* `9_conditional` end to end test ([#1951](https://github.com/noir-lang/noir/issues/1951)) ([2f6741f](https://github.com/noir-lang/noir/commit/2f6741f4f3eaa892bd970ffbb19703546c4254c4))
+* `regression` end to end test ([#1965](https://github.com/noir-lang/noir/issues/1965)) ([59f92e3](https://github.com/noir-lang/noir/commit/59f92e303a7d3279af779946e216860082567de3))
+* Account for missing indices in flattened witness map ([#1907](https://github.com/noir-lang/noir/issues/1907)) ([3972410](https://github.com/noir-lang/noir/commit/39724108a428015cfade4c4ef032af8941bc9a93))
+* Add missing `follow_bindings` when checking if a type can be casted ([#2022](https://github.com/noir-lang/noir/issues/2022)) ([537c2bd](https://github.com/noir-lang/noir/commit/537c2bd7844dea85c9d7136b09a5d2ccd33c3108))
+* Add Result to acir gen ([#1927](https://github.com/noir-lang/noir/issues/1927)) ([1f8fd51](https://github.com/noir-lang/noir/commit/1f8fd51fb28b62e05f4b0c0829d446e43e8b85cc))
+* Assignment to arrays of structs ([#1998](https://github.com/noir-lang/noir/issues/1998)) ([2c3d976](https://github.com/noir-lang/noir/commit/2c3d976ded4d98529a76b7f24284209f58bc04b9))
+* **brillig_gen:** Pass correct size of complex types input for brillig foreign calls ([#1922](https://github.com/noir-lang/noir/issues/1922)) ([04c89d2](https://github.com/noir-lang/noir/commit/04c89d2581f3f73073bb0ab83d37a853c638959f))
+* Create `FileManager` with a root and normalize filenames against it ([#1881](https://github.com/noir-lang/noir/issues/1881)) ([50c1648](https://github.com/noir-lang/noir/commit/50c16489173f847dc466e2f82738a5e441445407))
+* Differentiate stdlib `CrateId` from others ([#1895](https://github.com/noir-lang/noir/issues/1895)) ([211e251](https://github.com/noir-lang/noir/commit/211e2512861566f21c5bfec4b47eb6964211f4c0))
+* Don't panic when checking if an undeclared variable is mutable ([#1987](https://github.com/noir-lang/noir/issues/1987)) ([0449518](https://github.com/noir-lang/noir/commit/0449518a430d1148b4edccb819af072cf029a83d))
+* emit `Opcode`s in correct order from `GeneratedAcir::radix_le_decompose` ([#1903](https://github.com/noir-lang/noir/issues/1903)) ([e5fe839](https://github.com/noir-lang/noir/commit/e5fe839876210a208f68fd4672b4b1e86d3c0073))
+* emit opcode in correct order from `GeneratedAcir::radix_le_decompose` ([e5fe839](https://github.com/noir-lang/noir/commit/e5fe839876210a208f68fd4672b4b1e86d3c0073))
+* emit opcodes for sorting variables in order of execution ([c43efab](https://github.com/noir-lang/noir/commit/c43efab06065c32fa83f8b09afca9605ba82da45))
+* Emit opcodes for sorting variables in order of execution ([#1941](https://github.com/noir-lang/noir/issues/1941)) ([c43efab](https://github.com/noir-lang/noir/commit/c43efab06065c32fa83f8b09afca9605ba82da45))
+* Fix auto-deref operations assigning the wrong result type ([#1904](https://github.com/noir-lang/noir/issues/1904)) ([827f78c](https://github.com/noir-lang/noir/commit/827f78c8d3cd478b7917deb2fcd3c854540116cb))
+* **lsp:** Avoid storing Context until recompiles are possible ([#1891](https://github.com/noir-lang/noir/issues/1891)) ([fb5f20b](https://github.com/noir-lang/noir/commit/fb5f20b1b4d911de565faebfc9baa498cd5e2128))
+* method resolution when calling an `&mut` method with an `&mut` object type ([#1947](https://github.com/noir-lang/noir/issues/1947)) ([73c2e94](https://github.com/noir-lang/noir/commit/73c2e9416c2c77cc384b9cfe76b594cd1764c586))
+* Only flatten main ([#1984](https://github.com/noir-lang/noir/issues/1984)) ([ac865b1](https://github.com/noir-lang/noir/commit/ac865b1b83952015d89cc8fde4702148c5eac3c6))
+* Parse an if followed by a tuple as a block ([#1924](https://github.com/noir-lang/noir/issues/1924)) ([8df4f05](https://github.com/noir-lang/noir/commit/8df4f05d3ae467c74c409287ad6202c5778b073d))
+* Perform `occurs` check before binding function types ([#2027](https://github.com/noir-lang/noir/issues/2027)) ([1544786](https://github.com/noir-lang/noir/commit/154478698db4192d56050e57091991ffd25da36b))
+* Prevent `if` and `for` from parsing constructor expressions ([#1916](https://github.com/noir-lang/noir/issues/1916)) ([6d3029a](https://github.com/noir-lang/noir/commit/6d3029a10fdcb4f839f624e2011f32b3774dbeea))
+* Rebuild tests plus script to include secp256r1 change ([#1908](https://github.com/noir-lang/noir/issues/1908)) ([ca68666](https://github.com/noir-lang/noir/commit/ca68666d959fb63dbddd449691f43305460c1a9d))
+* Switch from HashMap to BTreeMap in merge_stores ([#2035](https://github.com/noir-lang/noir/issues/2035)) ([4d179e3](https://github.com/noir-lang/noir/commit/4d179e3862a63d3d924215e75e31199369c6f3e8))
+* update int division optimization ([#1928](https://github.com/noir-lang/noir/issues/1928)) ([fb872c6](https://github.com/noir-lang/noir/commit/fb872c624cb04a66b99f121b4e4a478998d96271))
+* Various fixes for defunctionalization & brillig gen ([#1973](https://github.com/noir-lang/noir/issues/1973)) ([f99f4bf](https://github.com/noir-lang/noir/commit/f99f4bf94053918f1baee7d985bca92d64977a3e))
+* workaround for LSP dependency resolution ([#1865](https://github.com/noir-lang/noir/issues/1865)) ([a8ac338](https://github.com/noir-lang/noir/commit/a8ac338758e4afd1cd459803658f011e04666177))
+
 ## [0.8.0](https://github.com/noir-lang/noir/compare/v0.7.1...v0.8.0) (2023-07-07)
 
 
diff --git a/Cargo.lock b/Cargo.lock
index 2799e338fc3..a166aabd01c 100644
--- a/Cargo.lock
+++ b/Cargo.lock
@@ -4,9 +4,9 @@ version = 3
 
 [[package]]
 name = "acir"
-version = "0.19.0"
+version = "0.21.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "2a8e08ddd57e123075a643f9515f712c34ebcfd6333628a4e8972af41f21a694"
+checksum = "9915f2895792d8d9e4f25d9e026bac35774513a97c564fa7604e80462ac19e04"
 dependencies = [
  "acir_field",
  "bincode",
@@ -18,9 +18,9 @@ dependencies = [
 
 [[package]]
 name = "acir_field"
-version = "0.19.0"
+version = "0.21.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "729849a0f1ca22f267c83b4d04043f6fa44f159a6606dc58e586c131c67ab774"
+checksum = "3a43a2e9419db7a1b046e763154fa67e66039e8fe08b88c13f18f81f9220ebdf"
 dependencies = [
  "ark-bn254",
  "ark-ff",
@@ -32,9 +32,9 @@ dependencies = [
 
 [[package]]
 name = "acvm"
-version = "0.19.0"
+version = "0.21.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "f5f1c272779208fe823fe2a327d5e85efb6b8861e858507df4d532ec372514ee"
+checksum = "38362933e2f7fcf6faf6c7c969f4c1ad2370953c35613801686259cdb8b5d194"
 dependencies = [
  "acir",
  "acvm_blackbox_solver",
@@ -44,15 +44,14 @@ dependencies = [
  "indexmap 1.9.3",
  "num-bigint",
  "num-traits",
- "rmp-serde",
  "thiserror",
 ]
 
 [[package]]
 name = "acvm-backend-barretenberg"
-version = "0.9.0"
+version = "0.10.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "9ff47ff4fd4ae9c6a606f88f1f67a5b4e382313ae3e99edfdc7403bef4a49972"
+checksum = "48216028c1e503f26e52f85b3888010ee2cedc72d67de629a1318ceaf09dc67c"
 dependencies = [
  "acvm",
  "barretenberg-sys",
@@ -70,9 +69,9 @@ dependencies = [
 
 [[package]]
 name = "acvm_blackbox_solver"
-version = "0.19.0"
+version = "0.21.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "7ee8080267f367360522f24a5cd0de2bf7b9d31795266471c69e352083ceda39"
+checksum = "aa2d887ed2c7203f08efb6661d8f30ecfd69b453fe2965393d7e99664afc7558"
 dependencies = [
  "acir",
  "blake2",
@@ -85,9 +84,9 @@ dependencies = [
 
 [[package]]
 name = "acvm_stdlib"
-version = "0.19.0"
+version = "0.21.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "e4b52ef8c927058b451576fa7ab7e173c2b302ee81a0337d2420d3ca01c71d5e"
+checksum = "e7958693ac099e257b1791dc71f0296b0cc5e97764e55d67efc06f25191ecbaf"
 dependencies = [
  "acir",
 ]
@@ -129,15 +128,6 @@ dependencies = [
  "version_check",
 ]
 
-[[package]]
-name = "aho-corasick"
-version = "0.7.20"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "cc936419f96fa211c1b9166887b38e5e40b19958e5b895be7c1f93adec7071ac"
-dependencies = [
- "memchr",
-]
-
 [[package]]
 name = "aho-corasick"
 version = "1.0.2"
@@ -213,7 +203,7 @@ dependencies = [
 
 [[package]]
 name = "arena"
-version = "0.8.0"
+version = "0.9.0"
 dependencies = [
  "generational-arena",
 ]
@@ -337,9 +327,9 @@ dependencies = [
 
 [[package]]
 name = "assert_cmd"
-version = "2.0.11"
+version = "2.0.12"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "86d6b683edf8d1119fe420a94f8a7e389239666aa72e65495d91c00462510151"
+checksum = "88903cb14723e4d4003335bb7f8a14f27691649105346a0f0957466c096adfe6"
 dependencies = [
  "anstyle",
  "bstr",
@@ -393,7 +383,7 @@ checksum = "a564d521dd56509c4c47480d00b80ee55f7e385ae48db5744c67ad50c92d2ebf"
 dependencies = [
  "proc-macro2",
  "quote",
- "syn 2.0.25",
+ "syn 2.0.26",
 ]
 
 [[package]]
@@ -533,9 +523,9 @@ dependencies = [
 
 [[package]]
 name = "brillig"
-version = "0.19.0"
+version = "0.21.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "30647da3d1347c3f3a3c0e955f75b1fd3a91c123ee87d6b55d94c042d68e2ae6"
+checksum = "9d24f35009f581a810c74628ab6bf03eb717b0e55d2c27994694b11ae98ff950"
 dependencies = [
  "acir_field",
  "serde",
@@ -543,12 +533,14 @@ dependencies = [
 
 [[package]]
 name = "brillig_vm"
-version = "0.19.0"
+version = "0.21.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "0dc5c4ce5b6553b4d48f9895ca6b336a3672f1dc802792a37f13dcb8902d47b5"
+checksum = "1534e2b03604d08a586ef735fa704f692c468c7e0e6663210fd414bac5382040"
 dependencies = [
  "acir",
  "acvm_blackbox_solver",
+ "num-bigint",
+ "num-traits",
 ]
 
 [[package]]
@@ -601,12 +593,6 @@ dependencies = [
  "syn 1.0.109",
 ]
 
-[[package]]
-name = "byteorder"
-version = "1.4.3"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "14c189c53d098945499cdfa7ecc63567cf3886b3332b312a5b4585d8d3a6a610"
-
 [[package]]
 name = "bytes"
 version = "1.4.0"
@@ -677,9 +663,9 @@ dependencies = [
 
 [[package]]
 name = "clap"
-version = "4.3.11"
+version = "4.3.16"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "1640e5cc7fb47dbb8338fd471b105e7ed6c3cb2aeb00c2e067127ffd3764a05d"
+checksum = "74bb1b4028935821b2d6b439bba2e970bdcf740832732437ead910c632e30d7d"
 dependencies = [
  "clap_builder",
  "clap_derive",
@@ -688,9 +674,9 @@ dependencies = [
 
 [[package]]
 name = "clap_builder"
-version = "4.3.11"
+version = "4.3.16"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "98c59138d527eeaf9b53f35a77fcc1fad9d883116070c63d5de1c7dc7b00c72b"
+checksum = "5ae467cbb0111869b765e13882a1dbbd6cb52f58203d8b80c44f667d4dd19843"
 dependencies = [
  "anstream",
  "anstyle",
@@ -700,14 +686,14 @@ dependencies = [
 
 [[package]]
 name = "clap_derive"
-version = "4.3.2"
+version = "4.3.12"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "b8cd2b2a819ad6eec39e8f1d6b53001af1e5469f8c177579cdaeb313115b825f"
+checksum = "54a9bb5758fc5dfe728d1019941681eccaf0cf8a4189b692a0ee2f2ecf90a050"
 dependencies = [
  "heck",
  "proc-macro2",
  "quote",
- "syn 2.0.25",
+ "syn 2.0.26",
 ]
 
 [[package]]
@@ -793,9 +779,9 @@ dependencies = [
 
 [[package]]
 name = "const-oid"
-version = "0.9.3"
+version = "0.9.4"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "6340df57935414636969091153f35f68d9f00bbc8fb4a9c6054706c213e6c6bc"
+checksum = "795bc6e66a8e340f075fcf6227e417a2dc976b92b91f3cdc778bb858778b6747"
 
 [[package]]
 name = "const_format"
@@ -980,9 +966,9 @@ dependencies = [
 
 [[package]]
 name = "darling"
-version = "0.20.1"
+version = "0.20.3"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "0558d22a7b463ed0241e993f76f09f30b126687447751a8638587b864e4b3944"
+checksum = "0209d94da627ab5605dcccf08bb18afa5009cfbef48d8a8b7d7bdbc79be25c5e"
 dependencies = [
  "darling_core",
  "darling_macro",
@@ -990,26 +976,26 @@ dependencies = [
 
 [[package]]
 name = "darling_core"
-version = "0.20.1"
+version = "0.20.3"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "ab8bfa2e259f8ee1ce5e97824a3c55ec4404a0d772ca7fa96bf19f0752a046eb"
+checksum = "177e3443818124b357d8e76f53be906d60937f0d3a90773a664fa63fa253e621"
 dependencies = [
  "fnv",
  "ident_case",
  "proc-macro2",
  "quote",
- "syn 2.0.25",
+ "syn 2.0.26",
 ]
 
 [[package]]
 name = "darling_macro"
-version = "0.20.1"
+version = "0.20.3"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "29a358ff9f12ec09c3e61fef9b5a9902623a695a46a917b07f269bff1445611a"
+checksum = "836a9bbc7ad63342d6d6e7b815ccab164bc77a2d95d84bc3117a8c0d5c98e2d5"
 dependencies = [
  "darling_core",
  "quote",
- "syn 2.0.25",
+ "syn 2.0.26",
 ]
 
 [[package]]
@@ -1161,14 +1147,14 @@ dependencies = [
  "darling",
  "proc-macro2",
  "quote",
- "syn 2.0.25",
+ "syn 2.0.26",
 ]
 
 [[package]]
 name = "equivalent"
-version = "1.0.0"
+version = "1.0.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "88bffebc5d80432c9b140ee17875ff173a8ab62faad5b257da912bd2f6c1c0a1"
+checksum = "5443807d6dff69373d433ab9ef5378ad8df50ca6298caf15de6e52e24aaf54d5"
 
 [[package]]
 name = "errno"
@@ -1247,7 +1233,7 @@ dependencies = [
 
 [[package]]
 name = "fm"
-version = "0.8.0"
+version = "0.9.0"
 dependencies = [
  "cfg-if",
  "codespan-reporting",
@@ -1328,7 +1314,7 @@ checksum = "89ca545a94061b6365f2c7355b4b32bd20df3ff95f02da9329b34ccc3bd6ee72"
 dependencies = [
  "proc-macro2",
  "quote",
- "syn 2.0.25",
+ "syn 2.0.26",
 ]
 
 [[package]]
@@ -1418,11 +1404,11 @@ checksum = "d2fabcfbdc87f4758337ca535fb41a6d701b65693ce38287d856d1674551ec9b"
 
 [[package]]
 name = "globset"
-version = "0.4.10"
+version = "0.4.11"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "029d74589adefde59de1a0c4f4732695c32805624aec7b68d91503d4dba79afc"
+checksum = "1391ab1f92ffcc08911957149833e682aa3fe252b9f45f966d2ef972274c97df"
 dependencies = [
- "aho-corasick 0.7.20",
+ "aho-corasick",
  "bstr",
  "fnv",
  "log",
@@ -1442,9 +1428,9 @@ dependencies = [
 
 [[package]]
 name = "gloo-utils"
-version = "0.1.6"
+version = "0.1.7"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "a8e8fc851e9c7b9852508bc6e3f690f452f474417e8545ec9857b7f7377036b5"
+checksum = "037fcb07216cb3a30f7292bd0176b050b7b9a052ba830ef7d5d65f6dc64ba58e"
 dependencies = [
  "js-sys",
  "serde",
@@ -1745,13 +1731,13 @@ source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "cb0889898416213fab133e1d33a0e5858a48177452750691bde3666d0fdbaf8b"
 dependencies = [
  "hermit-abi",
- "rustix 0.38.3",
+ "rustix 0.38.4",
  "windows-sys 0.48.0",
 ]
 
 [[package]]
 name = "iter-extended"
-version = "0.8.0"
+version = "0.9.0"
 
 [[package]]
 name = "itertools"
@@ -1764,9 +1750,9 @@ dependencies = [
 
 [[package]]
 name = "itoa"
-version = "1.0.8"
+version = "1.0.9"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "62b02a5381cc465bd3041d84623d0fa3b66738b52b8e2fc3bab8ad63ab032f4a"
+checksum = "af150ab688ff2122fcef229be89cb50dd66af9e01a4ff320cc137eecc9bacc38"
 
 [[package]]
 name = "js-sys"
@@ -1988,7 +1974,7 @@ checksum = "7843ec2de400bcbc6a6328c958dc38e5359da6e93e72e37bc5246bf1ae776389"
 
 [[package]]
 name = "nargo"
-version = "0.8.0"
+version = "0.9.0"
 dependencies = [
  "acvm",
  "base64",
@@ -1998,13 +1984,14 @@ dependencies = [
  "noirc_errors",
  "rustc_version",
  "serde",
+ "serde_json",
  "thiserror",
  "toml",
 ]
 
 [[package]]
 name = "nargo_cli"
-version = "0.8.0"
+version = "0.9.0"
 dependencies = [
  "acvm",
  "acvm-backend-barretenberg",
@@ -2041,12 +2028,13 @@ dependencies = [
 
 [[package]]
 name = "noir_lsp"
-version = "0.8.0"
+version = "0.9.0"
 dependencies = [
  "acvm",
  "async-lsp",
  "codespan-lsp",
  "codespan-reporting",
+ "fm",
  "lsp-types 0.94.0",
  "noirc_driver",
  "noirc_errors",
@@ -2059,11 +2047,12 @@ dependencies = [
 
 [[package]]
 name = "noir_wasm"
-version = "0.8.0"
+version = "0.9.0"
 dependencies = [
  "acvm",
  "build-data",
  "console_error_panic_hook",
+ "fm",
  "getrandom",
  "gloo-utils",
  "log",
@@ -2076,7 +2065,7 @@ dependencies = [
 
 [[package]]
 name = "noirc_abi"
-version = "0.8.0"
+version = "0.9.0"
 dependencies = [
  "acvm",
  "iter-extended",
@@ -2107,7 +2096,7 @@ dependencies = [
 
 [[package]]
 name = "noirc_driver"
-version = "0.8.0"
+version = "0.9.0"
 dependencies = [
  "acvm",
  "base64",
@@ -2122,7 +2111,7 @@ dependencies = [
 
 [[package]]
 name = "noirc_errors"
-version = "0.8.0"
+version = "0.9.0"
 dependencies = [
  "chumsky",
  "codespan",
@@ -2133,24 +2122,21 @@ dependencies = [
 
 [[package]]
 name = "noirc_evaluator"
-version = "0.8.0"
+version = "0.9.0"
 dependencies = [
  "acvm",
- "arena",
  "im",
  "iter-extended",
  "noirc_abi",
  "noirc_errors",
  "noirc_frontend",
  "num-bigint",
- "num-traits",
- "rand 0.8.5",
  "thiserror",
 ]
 
 [[package]]
 name = "noirc_frontend"
-version = "0.8.0"
+version = "0.9.0"
 dependencies = [
  "acvm",
  "arena",
@@ -2161,6 +2147,7 @@ dependencies = [
  "noirc_errors",
  "rustc-hash",
  "serde",
+ "serde_json",
  "small-ord-set",
  "smol_str",
  "strum",
@@ -2270,9 +2257,9 @@ dependencies = [
 
 [[package]]
 name = "paste"
-version = "1.0.13"
+version = "1.0.14"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "b4b27ab7be369122c218afc2079489cdcb4b517c0a3fc386ff11e1fedfcc2b35"
+checksum = "de3145af08024dea9fa9914f381a17b8fc6034dfb00f3a84013f7ff43f29ed4c"
 
 [[package]]
 name = "peeking_take_while"
@@ -2388,9 +2375,9 @@ dependencies = [
 
 [[package]]
 name = "proc-macro2"
-version = "1.0.64"
+version = "1.0.66"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "78803b62cbf1f46fde80d7c0e803111524b9877184cfe7c3033659490ac7a7da"
+checksum = "18fb31db3f9bddb2ea821cde30a9f70117e3f119938b5ee630b7403aa6e2ead9"
 dependencies = [
  "unicode-ident",
 ]
@@ -2426,9 +2413,9 @@ dependencies = [
 
 [[package]]
 name = "quote"
-version = "1.0.29"
+version = "1.0.31"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "573015e8ab27661678357f27dc26460738fd2b6c86e46f386fde94cb5d913105"
+checksum = "5fe8a65d69dd0808184ebb5f836ab526bb259db23c657efa38711b1072ee47f0"
 dependencies = [
  "proc-macro2",
 ]
@@ -2458,7 +2445,6 @@ version = "0.8.5"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "34af8d1a0e25924bc5b7c43c079c942339d8f0a8b57c39049bef581b46327404"
 dependencies = [
- "libc",
  "rand_chacha",
  "rand_core 0.6.4",
 ]
@@ -2583,7 +2569,7 @@ version = "1.9.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "b2eae68fc220f7cf2532e4494aded17545fce192d59cd996e0fe7887f4ceb575"
 dependencies = [
- "aho-corasick 1.0.2",
+ "aho-corasick",
  "memchr",
  "regex-automata",
  "regex-syntax",
@@ -2591,20 +2577,20 @@ dependencies = [
 
 [[package]]
 name = "regex-automata"
-version = "0.3.2"
+version = "0.3.3"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "83d3daa6976cffb758ec878f108ba0e062a45b2d6ca3a2cca965338855476caf"
+checksum = "39354c10dd07468c2e73926b23bb9c2caca74c5501e38a35da70406f1d923310"
 dependencies = [
- "aho-corasick 1.0.2",
+ "aho-corasick",
  "memchr",
  "regex-syntax",
 ]
 
 [[package]]
 name = "regex-syntax"
-version = "0.7.3"
+version = "0.7.4"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "2ab07dc67230e4a4718e70fd5c20055a4334b121f1f9db8fe63ef39ce9b8c846"
+checksum = "e5ea92a5b6195c6ef2a0295ea818b312502c6fc94dde986c5553242e18fd4ce2"
 
 [[package]]
 name = "region"
@@ -2729,28 +2715,6 @@ dependencies = [
  "syn 1.0.109",
 ]
 
-[[package]]
-name = "rmp"
-version = "0.8.11"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "44519172358fd6d58656c86ab8e7fbc9e1490c3e8f14d35ed78ca0dd07403c9f"
-dependencies = [
- "byteorder",
- "num-traits",
- "paste",
-]
-
-[[package]]
-name = "rmp-serde"
-version = "1.1.1"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "c5b13be192e0220b8afb7222aa5813cb62cc269ebb5cac346ca6487681d2913e"
-dependencies = [
- "byteorder",
- "rmp",
- "serde",
-]
-
 [[package]]
 name = "rust-embed"
 version = "6.8.1"
@@ -2772,7 +2736,7 @@ dependencies = [
  "quote",
  "rust-embed-utils",
  "shellexpand",
- "syn 2.0.25",
+ "syn 2.0.26",
  "walkdir",
 ]
 
@@ -2824,9 +2788,9 @@ dependencies = [
 
 [[package]]
 name = "rustix"
-version = "0.38.3"
+version = "0.38.4"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "ac5ffa1efe7548069688cd7028f32591853cd7b5b756d41bcffd2353e4fc75b4"
+checksum = "0a962918ea88d644592894bc6dc55acc6c0956488adcebbfb6e273506b7fd6e5"
 dependencies = [
  "bitflags 2.3.3",
  "errno",
@@ -2837,9 +2801,9 @@ dependencies = [
 
 [[package]]
 name = "rustls"
-version = "0.21.3"
+version = "0.21.5"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "b19faa85ecb5197342b54f987b142fb3e30d0c90da40f80ef4fa9a726e6676ed"
+checksum = "79ea77c539259495ce8ca47f53e66ae0330a8819f67e23ac96ca02f50e7b7d36"
 dependencies = [
  "log",
  "ring",
@@ -2868,15 +2832,15 @@ dependencies = [
 
 [[package]]
 name = "rustversion"
-version = "1.0.13"
+version = "1.0.14"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "dc31bd9b61a32c31f9650d18add92aa83a49ba979c143eefd27fe7177b05bd5f"
+checksum = "7ffc183a10b4478d04cbbbfc96d0873219d962dd5accaff2ffbd4ceb7df837f4"
 
 [[package]]
 name = "ryu"
-version = "1.0.14"
+version = "1.0.15"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "fe232bdf6be8c8de797b22184ee71118d63780ea42ac85b61d1baa6d3b782ae9"
+checksum = "1ad4cc8da4ef723ed60bced201181d83791ad433213d8c24efffda1eec85d741"
 
 [[package]]
 name = "safe-lock"
@@ -2948,9 +2912,9 @@ checksum = "e1cf6437eb19a8f4a6cc0f7dca544973b0b78843adbfeb3683d1a94a0024a294"
 
 [[package]]
 name = "scopeguard"
-version = "1.1.0"
+version = "1.2.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "d29ab0c6d3fc0ee92fe66e2d99f700eab17a8d57d1c1d3b748380fb20baa78cd"
+checksum = "94143f37725109f92c262ed2cf5e59bce7498c01bcc1502d7b9afe439a4e9f49"
 
 [[package]]
 name = "sct"
@@ -2984,9 +2948,9 @@ dependencies = [
 
 [[package]]
 name = "semver"
-version = "1.0.17"
+version = "1.0.18"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "bebd363326d05ec3e2f532ab7660680f3b02130d780c299bca73469d521bc0ed"
+checksum = "b0293b4b29daaf487284529cc2f5675b8e57c61f70167ba415a463651fd6a918"
 
 [[package]]
 name = "serde"
@@ -3008,9 +2972,9 @@ dependencies = [
 
 [[package]]
 name = "serde_bytes"
-version = "0.11.11"
+version = "0.11.12"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "5a16be4fe5320ade08736447e3198294a5ea9a6d44dde6f35f0a5e06859c427a"
+checksum = "ab33ec92f677585af6d88c65593ae2375adde54efdbf16d597f2cbc7a6d368ff"
 dependencies = [
  "serde",
 ]
@@ -3023,14 +2987,14 @@ checksum = "389894603bd18c46fa56231694f8d827779c0951a667087194cf9de94ed24682"
 dependencies = [
  "proc-macro2",
  "quote",
- "syn 2.0.25",
+ "syn 2.0.26",
 ]
 
 [[package]]
 name = "serde_json"
-version = "1.0.100"
+version = "1.0.103"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "0f1e14e89be7aa4c4b78bdbdc9eb5bf8517829a600ae8eaa39a6e1d960b5185c"
+checksum = "d03b412469450d4404fe8499a268edd7f8b79fecb074b0d812ad64ca21f4031b"
 dependencies = [
  "itoa",
  "ryu",
@@ -3045,7 +3009,7 @@ checksum = "1d89a8107374290037607734c0b73a85db7ed80cae314b3c5791f192a496e731"
 dependencies = [
  "proc-macro2",
  "quote",
- "syn 2.0.25",
+ "syn 2.0.26",
 ]
 
 [[package]]
@@ -3262,9 +3226,9 @@ dependencies = [
 
 [[package]]
 name = "syn"
-version = "2.0.25"
+version = "2.0.26"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "15e3fc8c0c74267e2df136e5e5fb656a464158aa57624053375eb9c8c6e25ae2"
+checksum = "45c3457aacde3c65315de5031ec191ce46604304d2446e803d71ade03308d970"
 dependencies = [
  "proc-macro2",
  "quote",
@@ -3279,9 +3243,9 @@ checksum = "55937e1799185b12863d447f42597ed69d9928686b8d88a1df17376a097d8369"
 
 [[package]]
 name = "target-lexicon"
-version = "0.12.8"
+version = "0.12.10"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "1b1c7f239eb94671427157bd93b3694320f3668d4e1eff08c7285366fd777fac"
+checksum = "1d2faeef5759ab89935255b1a4cd98e0baf99d1085e37d36599c625dac49ae8e"
 
 [[package]]
 name = "tempdir"
@@ -3339,7 +3303,7 @@ checksum = "463fe12d7993d3b327787537ce8dd4dfa058de32fc2b195ef3cde03dc4771e8f"
 dependencies = [
  "proc-macro2",
  "quote",
- "syn 2.0.25",
+ "syn 2.0.26",
 ]
 
 [[package]]
@@ -3403,7 +3367,7 @@ checksum = "630bdcf245f78637c13ec01ffae6187cca34625e8c63150d424b59e55af2675e"
 dependencies = [
  "proc-macro2",
  "quote",
- "syn 2.0.25",
+ "syn 2.0.26",
 ]
 
 [[package]]
@@ -3453,9 +3417,9 @@ dependencies = [
 
 [[package]]
 name = "toml_edit"
-version = "0.19.12"
+version = "0.19.14"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "c500344a19072298cd05a7224b3c0c629348b78692bf48466c5238656e315a78"
+checksum = "f8123f27e969974a3dfba720fdb560be359f57b44302d280ba72e76a74480e8a"
 dependencies = [
  "indexmap 2.0.0",
  "serde",
@@ -3508,7 +3472,7 @@ checksum = "5f4f31f56159e98206da9efd823404b79b6ef3143b4a7ab76e67b1751b25a4ab"
 dependencies = [
  "proc-macro2",
  "quote",
- "syn 2.0.25",
+ "syn 2.0.26",
 ]
 
 [[package]]
@@ -3562,9 +3526,9 @@ checksum = "92888ba5573ff080736b3648696b70cafad7d250551175acbaa4e0385b3e1460"
 
 [[package]]
 name = "unicode-ident"
-version = "1.0.10"
+version = "1.0.11"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "22049a19f4a68748a168c0fc439f9516686aa045927ff767eca0a85101fb6e73"
+checksum = "301abaae475aa91687eb82514b328ab47a211a533026cb25fc3e519b86adfc3c"
 
 [[package]]
 name = "unicode-normalization"
@@ -3613,9 +3577,9 @@ checksum = "711b9620af191e0cdc7468a8d14e709c3dcdb115b36f838e601583af800a370a"
 
 [[package]]
 name = "uuid"
-version = "1.4.0"
+version = "1.4.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "d023da39d1fde5a8a3fe1f3e01ca9632ada0a63e9797de55a879d6e2236277be"
+checksum = "79daa5ed5740825c40b389c5e50312b9c86df53fccd33f281df655642b43869d"
 
 [[package]]
 name = "valuable"
@@ -3692,7 +3656,7 @@ dependencies = [
  "once_cell",
  "proc-macro2",
  "quote",
- "syn 2.0.25",
+ "syn 2.0.26",
  "wasm-bindgen-shared",
 ]
 
@@ -3726,7 +3690,7 @@ checksum = "e128beba882dd1eb6200e1dc92ae6c5dbaa4311aa7bb211ca035779e5efc39f8"
 dependencies = [
  "proc-macro2",
  "quote",
- "syn 2.0.25",
+ "syn 2.0.26",
  "wasm-bindgen-backend",
  "wasm-bindgen-shared",
 ]
@@ -3763,9 +3727,9 @@ dependencies = [
 
 [[package]]
 name = "wasm-encoder"
-version = "0.29.0"
+version = "0.31.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "18c41dbd92eaebf3612a39be316540b8377c871cb9bde6b064af962984912881"
+checksum = "06a3d1b4a575ffb873679402b2aedb3117555eb65c27b1b86c8a91e574bc2a2a"
 dependencies = [
  "leb128",
 ]
@@ -4020,9 +3984,9 @@ checksum = "718ed7c55c2add6548cca3ddd6383d738cd73b892df400e96b9aa876f0141d7a"
 
 [[package]]
 name = "wast"
-version = "60.0.0"
+version = "62.0.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "bd06cc744b536e30387e72a48fdd492105b9c938bb4f415c39c616a7a0a697ad"
+checksum = "c7f7ee878019d69436895f019b65f62c33da63595d8e857cbdc87c13ecb29a32"
 dependencies = [
  "leb128",
  "memchr",
@@ -4032,9 +3996,9 @@ dependencies = [
 
 [[package]]
 name = "wat"
-version = "1.0.66"
+version = "1.0.68"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "5abe520f0ab205366e9ac7d3e6b2fc71de44e32a2b58f2ec871b6b575bdcea3b"
+checksum = "295572bf24aa5b685a971a83ad3e8b6e684aaad8a9be24bc7bf59bed84cc1c08"
 dependencies = [
  "wast",
 ]
@@ -4230,9 +4194,9 @@ checksum = "1a515f5799fe4961cb532f983ce2b23082366b898e52ffbce459c86f67c8378a"
 
 [[package]]
 name = "winnow"
-version = "0.4.9"
+version = "0.5.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "81a2094c43cc94775293eaa0e499fbc30048a6d824ac82c0351a8c0bf9112529"
+checksum = "81fac9742fd1ad1bd9643b991319f72dd031016d44b77039a26977eb667141e7"
 dependencies = [
  "memchr",
 ]
@@ -4272,5 +4236,5 @@ checksum = "ce36e65b0d2999d2aafac989fb249189a141aee1f53c612c1f37d72631959f69"
 dependencies = [
  "proc-macro2",
  "quote",
- "syn 2.0.25",
+ "syn 2.0.26",
 ]
diff --git a/Cargo.toml b/Cargo.toml
index 65b1ad87225..6f83ac6dfe0 100644
--- a/Cargo.toml
+++ b/Cargo.toml
@@ -18,14 +18,14 @@ default-members = ["crates/nargo_cli"]
 
 [workspace.package]
 # x-release-please-start-version
-version = "0.8.0"
+version = "0.9.0"
 # x-release-please-end
 authors = ["The Noir Team <team@noir-lang.org>"]
 edition = "2021"
 rust-version = "1.66"
 
 [workspace.dependencies]
-acvm = "0.19.0"
+acvm = "0.21.0"
 arena = { path = "crates/arena" }
 fm = { path = "crates/fm" }
 iter-extended = { path = "crates/iter-extended" }
@@ -38,10 +38,9 @@ noirc_errors = { path = "crates/noirc_errors" }
 noirc_evaluator = { path = "crates/noirc_evaluator" }
 noirc_frontend = { path = "crates/noirc_frontend" }
 noir_wasm = { path = "crates/wasm" }
-
 cfg-if = "1.0.0"
 clap = { version = "4.1.4", features = ["derive"] }
-codespan = {version = "0.11.1", features = ["serialization"]}
+codespan = { version = "0.11.1", features = ["serialization"] }
 codespan-lsp = "0.11.1"
 codespan-reporting = "0.11.1"
 chumsky = { git = "https://github.com/jfecher/chumsky", rev = "ad9d312" }
diff --git a/crates/fm/src/file_reader.rs b/crates/fm/src/file_reader.rs
index f0a5fe625aa..df4e49b919a 100644
--- a/crates/fm/src/file_reader.rs
+++ b/crates/fm/src/file_reader.rs
@@ -11,6 +11,16 @@ use std::path::Path;
 #[cfg_attr(target_os = "windows", prefix = r"std\")] // Note reversed slash direction
 struct StdLibAssets;
 
+#[cfg(target_os = "windows")]
+pub(super) fn is_stdlib_asset(path: &Path) -> bool {
+    path.starts_with("std\\")
+}
+
+#[cfg(not(target_os = "windows"))]
+pub(super) fn is_stdlib_asset(path: &Path) -> bool {
+    path.starts_with("std/")
+}
+
 cfg_if::cfg_if! {
     if #[cfg(target_arch = "wasm32")] {
         use wasm_bindgen::{prelude::*, JsValue};
@@ -41,6 +51,7 @@ cfg_if::cfg_if! {
             }
         }
     } else {
+
         pub(crate) fn read_file_to_string(path_to_file: &Path) -> Result<String, Error> {
 
             match StdLibAssets::get(path_to_file.to_str().unwrap()) {
diff --git a/crates/fm/src/lib.rs b/crates/fm/src/lib.rs
index d22d74c757a..dc78db87684 100644
--- a/crates/fm/src/lib.rs
+++ b/crates/fm/src/lib.rs
@@ -7,10 +7,11 @@ mod file_map;
 mod file_reader;
 
 pub use file_map::{File, FileId, FileMap};
+use file_reader::is_stdlib_asset;
 
 use std::{
     collections::HashMap,
-    path::{Path, PathBuf},
+    path::{Component, Path, PathBuf},
 };
 
 pub const FILE_EXTENSION: &str = "nr";
@@ -18,30 +19,43 @@ pub const FILE_EXTENSION: &str = "nr";
 #[derive(Clone, Debug, PartialEq, Eq, Hash)]
 struct VirtualPath(PathBuf);
 
-#[derive(Debug, Default)]
+#[derive(Debug)]
 pub struct FileManager {
+    root: PathBuf,
     file_map: file_map::FileMap,
     id_to_path: HashMap<FileId, VirtualPath>,
     path_to_id: HashMap<VirtualPath, FileId>,
 }
 
 impl FileManager {
-    // XXX: Maybe use a AsRef<Path> here, for API ergonomics
-    pub fn add_file(&mut self, path_to_file: &Path) -> Option<FileId> {
+    pub fn new(root: &Path) -> Self {
+        Self {
+            root: normalize_path(root),
+            file_map: Default::default(),
+            id_to_path: Default::default(),
+            path_to_id: Default::default(),
+        }
+    }
+
+    pub fn add_file(&mut self, file_name: &Path) -> Option<FileId> {
         // Handle both relative file paths and std/lib virtual paths.
-        let base = Path::new(".").canonicalize().expect("Base path canonicalize failed");
-        let res = path_to_file.canonicalize().unwrap_or_else(|_| path_to_file.to_path_buf());
-        let resolved_path = res.strip_prefix(base).unwrap_or(&res);
+        let resolved_path: PathBuf = if is_stdlib_asset(file_name) {
+            // Special case for stdlib where we want to read specifically the `std/` relative path
+            // TODO: The stdlib path should probably be an absolute path rooted in something people would never create
+            file_name.to_path_buf()
+        } else {
+            normalize_path(&self.root.join(file_name))
+        };
 
         // Check that the resolved path already exists in the file map, if it is, we return it.
-        let path_to_file = virtualize_path(resolved_path);
+        let path_to_file = virtualize_path(&resolved_path);
         if let Some(file_id) = self.path_to_id.get(&path_to_file) {
             return Some(*file_id);
         }
 
         // Otherwise we add the file
-        let source = file_reader::read_file_to_string(resolved_path).ok()?;
-        let file_id = self.file_map.add_file(resolved_path.to_path_buf().into(), source);
+        let source = file_reader::read_file_to_string(&resolved_path).ok()?;
+        let file_id = self.file_map.add_file(resolved_path.into(), source);
         self.register_path(file_id, path_to_file);
         Some(file_id)
     }
@@ -87,6 +101,37 @@ impl FileManager {
     }
 }
 
+/// Replacement for `std::fs::canonicalize` that doesn't verify the path exists.
+///
+/// Plucked from https://github.com/rust-lang/cargo/blob/fede83ccf973457de319ba6fa0e36ead454d2e20/src/cargo/util/paths.rs#L61
+/// Advice from https://www.reddit.com/r/rust/comments/hkkquy/comment/fwtw53s/
+fn normalize_path(path: &Path) -> PathBuf {
+    let mut components = path.components().peekable();
+    let mut ret = if let Some(c @ Component::Prefix(..)) = components.peek().cloned() {
+        components.next();
+        PathBuf::from(c.as_os_str())
+    } else {
+        PathBuf::new()
+    };
+
+    for component in components {
+        match component {
+            Component::Prefix(..) => unreachable!(),
+            Component::RootDir => {
+                ret.push(component.as_os_str());
+            }
+            Component::CurDir => {}
+            Component::ParentDir => {
+                ret.pop();
+            }
+            Component::Normal(c) => {
+                ret.push(c);
+            }
+        }
+    }
+    ret
+}
+
 /// Takes a path to a noir file. This will panic on paths to directories
 /// Returns the file path with the extension removed
 fn virtualize_path(path: &Path) -> VirtualPath {
@@ -102,46 +147,49 @@ mod tests {
     use super::*;
     use tempfile::{tempdir, TempDir};
 
-    fn dummy_file_path(dir: &TempDir, file_name: &str) -> PathBuf {
+    fn create_dummy_file(dir: &TempDir, file_name: &Path) {
         let file_path = dir.path().join(file_name);
-        let _file = std::fs::File::create(file_path.clone()).unwrap();
-
-        file_path
+        let _file = std::fs::File::create(file_path).unwrap();
     }
 
     #[test]
     fn path_resolve_file_module() {
         let dir = tempdir().unwrap();
-        let file_path = dummy_file_path(&dir, "my_dummy_file.nr");
 
-        let mut fm = FileManager::default();
+        let entry_file_name = Path::new("my_dummy_file.nr");
+        create_dummy_file(&dir, entry_file_name);
+
+        let mut fm = FileManager::new(dir.path());
 
-        let file_id = fm.add_file(&file_path).unwrap();
+        let file_id = fm.add_file(entry_file_name).unwrap();
 
-        let _foo_file_path = dummy_file_path(&dir, "foo.nr");
+        let dep_file_name = Path::new("foo.nr");
+        create_dummy_file(&dir, dep_file_name);
         fm.resolve_path(file_id, "foo").unwrap();
     }
     #[test]
     fn path_resolve_file_module_other_ext() {
         let dir = tempdir().unwrap();
-        let file_path = dummy_file_path(&dir, "foo.noir");
+        let file_name = Path::new("foo.noir");
+        create_dummy_file(&dir, file_name);
 
-        let mut fm = FileManager::default();
+        let mut fm = FileManager::new(dir.path());
 
-        let file_id = fm.add_file(&file_path).unwrap();
+        let file_id = fm.add_file(file_name).unwrap();
 
         assert!(fm.path(file_id).ends_with("foo"));
     }
     #[test]
     fn path_resolve_sub_module() {
-        let mut fm = FileManager::default();
-
         let dir = tempdir().unwrap();
+        let mut fm = FileManager::new(dir.path());
+
         // Create a lib.nr file at the root.
         // we now have dir/lib.nr
-        let file_path = dummy_file_path(&dir, "lib.nr");
+        let file_name = Path::new("lib.nr");
+        create_dummy_file(&dir, file_name);
 
-        let file_id = fm.add_file(&file_path).unwrap();
+        let file_id = fm.add_file(file_name).unwrap();
 
         // Create a sub directory
         // we now have:
@@ -154,14 +202,14 @@ mod tests {
         // we no have:
         // - dir/lib.nr
         // - dir/sub_dir/foo.nr
-        let _foo_file_path = dummy_file_path(&sub_dir, "foo.nr");
+        create_dummy_file(&sub_dir, Path::new("foo.nr"));
 
         // Add a parent module for the sub_dir
         // we no have:
         // - dir/lib.nr
         // - dir/sub_dir.nr
         // - dir/sub_dir/foo.nr
-        let _sub_dir_root_file_path = dummy_file_path(&dir, &format!("{}.nr", sub_dir_name));
+        create_dummy_file(&dir, Path::new(&format!("{}.nr", sub_dir_name)));
 
         // First check for the sub_dir.nr file and add it to the FileManager
         let sub_dir_file_id = fm.resolve_path(file_id, sub_dir_name).unwrap();
@@ -176,20 +224,22 @@ mod tests {
     /// they should both resolve to ../foo.nr
     #[test]
     fn path_resolve_modules_with_different_paths_as_same_file() {
-        let mut fm = FileManager::default();
-
-        // Create a lib.nr file at the root.
         let dir = tempdir().unwrap();
         let sub_dir = TempDir::new_in(&dir).unwrap();
         let sub_sub_dir = TempDir::new_in(&sub_dir).unwrap();
-        let file_path = dummy_file_path(&dir, "lib.nr");
 
-        // Create another file in a subdirectory with a convoluted path
-        let second_file_path = dummy_file_path(&sub_sub_dir, "./../../lib.nr");
+        let mut fm = FileManager::new(dir.path());
+
+        // Create a lib.nr file at the root.
+        let file_name = Path::new("lib.nr");
+        create_dummy_file(&dir, file_name);
+
+        // Create another path with `./` and `../` inside it
+        let second_file_name = PathBuf::from(sub_sub_dir.path()).join("./../../lib.nr");
 
         // Add both files to the file manager
-        let file_id = fm.add_file(&file_path).unwrap();
-        let second_file_id = fm.add_file(&second_file_path).unwrap();
+        let file_id = fm.add_file(file_name).unwrap();
+        let second_file_id = fm.add_file(&second_file_name).unwrap();
 
         assert_eq!(file_id, second_file_id);
     }
diff --git a/crates/lsp/Cargo.toml b/crates/lsp/Cargo.toml
index 47278ab5291..2611abd67dc 100644
--- a/crates/lsp/Cargo.toml
+++ b/crates/lsp/Cargo.toml
@@ -11,6 +11,7 @@ edition.workspace = true
 acvm.workspace = true
 codespan-lsp.workspace = true
 codespan-reporting.workspace = true
+fm.workspace = true
 lsp-types.workspace = true
 noirc_driver.workspace = true
 noirc_errors.workspace = true
diff --git a/crates/lsp/src/lib.rs b/crates/lsp/src/lib.rs
index 95aae571fbb..bd4112218e4 100644
--- a/crates/lsp/src/lib.rs
+++ b/crates/lsp/src/lib.rs
@@ -2,17 +2,19 @@ mod lib_hacky;
 use std::env;
 
 use std::{
-    future::Future,
+    future::{self, Future},
     ops::{self, ControlFlow},
+    path::PathBuf,
     pin::Pin,
     task::{self, Poll},
 };
 
 use async_lsp::{
-    router::Router, AnyEvent, AnyNotification, AnyRequest, ClientSocket, Error, LanguageClient,
-    LspService, ResponseError,
+    router::Router, AnyEvent, AnyNotification, AnyRequest, ClientSocket, Error, ErrorCode,
+    LanguageClient, LspService, ResponseError,
 };
 use codespan_reporting::files;
+use fm::FileManager;
 use lsp_types::{
     notification, request, CodeLens, CodeLensOptions, CodeLensParams, Command, Diagnostic,
     DiagnosticSeverity, DidChangeConfigurationParams, DidChangeTextDocumentParams,
@@ -22,7 +24,10 @@ use lsp_types::{
 };
 use noirc_driver::{check_crate, create_local_crate};
 use noirc_errors::{DiagnosticKind, FileDiagnostic};
-use noirc_frontend::{graph::CrateType, hir::Context};
+use noirc_frontend::{
+    graph::{CrateGraph, CrateType},
+    hir::Context,
+};
 use serde_json::Value as JsonValue;
 use tower::Service;
 
@@ -31,12 +36,13 @@ const TEST_CODELENS_TITLE: &str = "▶\u{fe0e} Run Test";
 
 // State for the LSP gets implemented on this struct and is internal to the implementation
 pub struct LspState {
+    root_path: Option<PathBuf>,
     client: ClientSocket,
 }
 
 impl LspState {
     fn new(client: &ClientSocket) -> Self {
-        Self { client: client.clone() }
+        Self { client: client.clone(), root_path: None }
     }
 }
 
@@ -131,9 +137,13 @@ impl LspService for NargoLspService {
 // and params passed in.
 
 fn on_initialize(
-    _state: &mut LspState,
-    _params: InitializeParams,
+    state: &mut LspState,
+    params: InitializeParams,
 ) -> impl Future<Output = Result<InitializeResult, ResponseError>> {
+    if let Some(root_uri) = params.root_uri {
+        state.root_path = root_uri.to_file_path().ok();
+    }
+
     async {
         let text_document_sync =
             TextDocumentSyncOptions { save: Some(true.into()), ..Default::default() };
@@ -160,25 +170,38 @@ fn on_shutdown(
 }
 
 fn on_code_lens_request(
-    _state: &mut LspState,
+    state: &mut LspState,
     params: CodeLensParams,
 ) -> impl Future<Output = Result<Option<Vec<CodeLens>>, ResponseError>> {
     let file_path = &params.text_document.uri.to_file_path().unwrap();
 
-    let mut context = Context::default();
+    let mut context = match &state.root_path {
+        Some(root_path) => {
+            let fm = FileManager::new(root_path);
+            let graph = CrateGraph::default();
+            Context::new(fm, graph)
+        }
+        None => {
+            let err = ResponseError::new(
+                ErrorCode::REQUEST_FAILED,
+                "Unable to determine the project root path",
+            );
+            return future::ready(Err(err));
+        }
+    };
 
     let crate_id = create_local_crate(&mut context, file_path, CrateType::Binary);
 
     // We ignore the warnings and errors produced by compilation for producing codelenses
     // because we can still get the test functions even if compilation fails
-    let _ = check_crate(&mut context, false, false);
+    let _ = check_crate(&mut context, crate_id, false);
 
     let fm = &context.file_manager;
     let files = fm.as_simple_files();
     let tests = context.get_all_test_functions_in_crate_matching(&crate_id, "");
 
     let mut lenses: Vec<CodeLens> = vec![];
-    for func_id in tests {
+    for (func_name, func_id) in tests {
         let location = context.function_meta(&func_id).name.location;
         let file_id = location.file;
         // TODO(#1681): This file_id never be 0 because the "path" where it maps is the directory, not a file
@@ -186,8 +209,6 @@ fn on_code_lens_request(
             continue;
         }
 
-        let func_name = context.function_name(&func_id);
-
         let range =
             byte_span_to_range(files, file_id.as_usize(), location.span.into()).unwrap_or_default();
 
@@ -202,13 +223,9 @@ fn on_code_lens_request(
         lenses.push(lens);
     }
 
-    async move {
-        if lenses.is_empty() {
-            Ok(None)
-        } else {
-            Ok(Some(lenses))
-        }
-    }
+    let res = if lenses.is_empty() { Ok(None) } else { Ok(Some(lenses)) };
+
+    future::ready(res)
 }
 
 fn on_initialized(
@@ -251,14 +268,26 @@ fn on_did_save_text_document(
     params: DidSaveTextDocumentParams,
 ) -> ControlFlow<Result<(), async_lsp::Error>> {
     let file_path = &params.text_document.uri.to_file_path().unwrap();
+    let mut context = match &state.root_path {
+        Some(root_path) => {
+            let fm = FileManager::new(root_path);
+            let graph = CrateGraph::default();
+            Context::new(fm, graph)
+        }
+        None => {
+            let err = ResponseError::new(
+                ErrorCode::REQUEST_FAILED,
+                "Unable to determine the project root path",
+            );
+            return ControlFlow::Break(Err(err.into()));
+        }
+    };
 
-    let mut context = Context::default();
-
-    create_local_crate(&mut context, file_path, CrateType::Binary);
+    let crate_id = create_local_crate(&mut context, file_path, CrateType::Binary);
 
     let mut diagnostics = Vec::new();
 
-    let file_diagnostics = match check_crate(&mut context, false, false) {
+    let file_diagnostics = match check_crate(&mut context, crate_id, false) {
         Ok(warnings) => warnings,
         Err(errors_and_warnings) => errors_and_warnings,
     };
diff --git a/crates/lsp/src/lib_hacky.rs b/crates/lsp/src/lib_hacky.rs
index 9d0e4c0c2dc..72a2625fcac 100644
--- a/crates/lsp/src/lib_hacky.rs
+++ b/crates/lsp/src/lib_hacky.rs
@@ -4,13 +4,14 @@
 use std::{
     collections::HashMap,
     fs,
-    future::Future,
+    future::{self, Future},
     ops::{self, ControlFlow},
     path::{Path, PathBuf},
 };
 
-use async_lsp::{LanguageClient, ResponseError};
+use async_lsp::{ErrorCode, LanguageClient, ResponseError};
 use codespan_reporting::files;
+use fm::FileManager;
 use lsp_types::{
     CodeLens, CodeLensOptions, CodeLensParams, Command, Diagnostic, DiagnosticSeverity,
     DidChangeConfigurationParams, DidChangeTextDocumentParams, DidCloseTextDocumentParams,
@@ -21,10 +22,11 @@ use lsp_types::{
 use noirc_driver::{check_crate, create_local_crate, create_non_local_crate, propagate_dep};
 use noirc_errors::{DiagnosticKind, FileDiagnostic};
 use noirc_frontend::{
-    graph::{CrateId, CrateName, CrateType},
+    graph::{CrateGraph, CrateId, CrateType},
     hir::Context,
 };
 
+// I'm guessing this is here so the `lib.rs` file compiles
 use crate::LspState;
 
 const TEST_COMMAND: &str = "nargo.test";
@@ -41,9 +43,13 @@ const TEST_CODELENS_TITLE: &str = "▶\u{fe0e} Run Test";
 // and params passed in.
 
 pub fn on_initialize(
-    _state: &mut LspState,
-    _params: InitializeParams,
+    state: &mut LspState,
+    params: InitializeParams,
 ) -> impl Future<Output = Result<InitializeResult, ResponseError>> {
+    if let Some(root_uri) = params.root_uri {
+        state.root_path = root_uri.to_file_path().ok();
+    }
+
     async {
         let text_document_sync =
             TextDocumentSyncOptions { save: Some(true.into()), ..Default::default() };
@@ -70,31 +76,32 @@ pub fn on_shutdown(
 }
 
 pub fn on_code_lens_request(
-    _state: &mut LspState,
+    state: &mut LspState,
     params: CodeLensParams,
 ) -> impl Future<Output = Result<Option<Vec<CodeLens>>, ResponseError>> {
     let actual_path = params.text_document.uri.to_file_path().unwrap();
-    let (mut driver, current_crate_id) = create_context_at_path(actual_path);
+    let (mut context, crate_id) = match create_context_at_path(&state.root_path, &actual_path) {
+        Err(err) => return future::ready(Err(err)),
+        Ok(res) => res,
+    };
 
     // We ignore the warnings and errors produced by compilation for producing codelenses
     // because we can still get the test functions even if compilation fails
-    let _ = check_crate(&mut driver, false, false);
+    let _ = check_crate(&mut context, crate_id, false);
 
-    let fm = &driver.file_manager;
+    let fm = &context.file_manager;
     let files = fm.as_simple_files();
-    let tests = driver.get_all_test_functions_in_crate_matching(&current_crate_id, "");
+    let tests = context.get_all_test_functions_in_crate_matching(&crate_id, "");
 
     let mut lenses: Vec<CodeLens> = vec![];
-    for func_id in tests {
-        let location = driver.function_meta(&func_id).name.location;
+    for (func_name, func_id) in tests {
+        let location = context.function_meta(&func_id).name.location;
         let file_id = location.file;
         // TODO(#1681): This file_id never be 0 because the "path" where it maps is the directory, not a file
         if file_id.as_usize() != 0 {
             continue;
         }
 
-        let func_name = driver.function_name(&func_id);
-
         let range =
             byte_span_to_range(files, file_id.as_usize(), location.span.into()).unwrap_or_default();
 
@@ -109,13 +116,9 @@ pub fn on_code_lens_request(
         lenses.push(lens);
     }
 
-    async move {
-        if lenses.is_empty() {
-            Ok(None)
-        } else {
-            Ok(Some(lenses))
-        }
-    }
+    let res = if lenses.is_empty() { Ok(None) } else { Ok(Some(lenses)) };
+
+    future::ready(res)
 }
 
 pub fn on_initialized(
@@ -197,9 +200,13 @@ pub fn on_did_save_text_document(
     params: DidSaveTextDocumentParams,
 ) -> ControlFlow<Result<(), async_lsp::Error>> {
     let actual_path = params.text_document.uri.to_file_path().unwrap();
-    let (mut context, _) = create_context_at_path(actual_path.clone());
+    let actual_file_name = actual_path.file_name();
+    let (mut context, crate_id) = match create_context_at_path(&state.root_path, &actual_path) {
+        Err(err) => return ControlFlow::Break(Err(err.into())),
+        Ok(res) => res,
+    };
 
-    let file_diagnostics = match check_crate(&mut context, false, false) {
+    let file_diagnostics = match check_crate(&mut context, crate_id, false) {
         Ok(warnings) => warnings,
         Err(errors_and_warnings) => errors_and_warnings,
     };
@@ -213,13 +220,13 @@ pub fn on_did_save_text_document(
             // TODO(AD): HACK, undo these total hacks once we have a proper approach
             if file_id.as_usize() == 0 {
                 // main.nr case
-                if actual_path.file_name().unwrap().to_str() != Some("main.nr")
-                    && actual_path.file_name().unwrap().to_str() != Some("lib.nr")
+                if actual_file_name.unwrap().to_str() != Some("main.nr")
+                    && actual_file_name.unwrap().to_str() != Some("lib.nr")
                 {
                     continue;
                 }
             } else if fm.path(file_id).file_name().unwrap().to_str().unwrap()
-                != actual_path.file_name().unwrap().to_str().unwrap().replace(".nr", "")
+                != actual_file_name.unwrap().to_str().unwrap().replace(".nr", "")
             {
                 // every other file case
                 continue; // TODO(AD): HACK, we list all errors, filter by hacky final path component
@@ -256,19 +263,30 @@ pub fn on_did_save_text_document(
     ControlFlow::Continue(())
 }
 
-fn create_context_at_path(actual_path: PathBuf) -> (Context, CrateId) {
-    // TODO: Requiring `Language` and `is_opcode_supported` to construct a driver makes for some real stinky code
-    // The driver should not require knowledge of the backend; instead should be implemented as an independent pass (in nargo?)
-    let mut context = Context::default();
+fn create_context_at_path(
+    root_path: &Option<PathBuf>,
+    actual_path: &Path,
+) -> Result<(Context, CrateId), ResponseError> {
+    let mut context = match &root_path {
+        Some(root_path) => {
+            let fm = FileManager::new(root_path);
+            let graph = CrateGraph::default();
+            Context::new(fm, graph)
+        }
+        None => {
+            let err = ResponseError::new(ErrorCode::REQUEST_FAILED, "Project has not been built");
+            return Err(err);
+        }
+    };
 
-    let mut file_path: PathBuf = actual_path;
+    let mut file_path = actual_path.to_path_buf();
     // TODO better naming/unhacking
     if let Some(new_path) = find_nearest_parent_file(&file_path, &["lib.nr", "main.nr"]) {
         file_path = new_path; // TODO unhack
     }
     let nargo_toml_path = find_nearest_parent_file(&file_path, &["Nargo.toml"]);
 
-    let current_crate_id = create_local_crate(&mut context, file_path, CrateType::Binary);
+    let current_crate_id = create_local_crate(&mut context, &file_path, CrateType::Binary);
 
     // TODO(AD): undo hacky dependency resolution
     if let Some(nargo_toml_path) = nargo_toml_path {
@@ -280,12 +298,12 @@ fn create_context_at_path(actual_path: PathBuf) -> (Context, CrateId) {
                     .unwrap() // TODO
                     .join(PathBuf::from(&dependency_path).join("src").join("lib.nr"));
                 let library_crate =
-                    create_non_local_crate(&mut context, path_to_lib, CrateType::Library);
-                propagate_dep(&mut context, library_crate, &CrateName::new(crate_name).unwrap());
+                    create_non_local_crate(&mut context, &path_to_lib, CrateType::Library);
+                propagate_dep(&mut context, library_crate, &crate_name.parse().unwrap());
             }
         }
     }
-    (context, current_crate_id)
+    Ok((context, current_crate_id))
 }
 
 pub fn on_exit(_state: &mut LspState, _params: ()) -> ControlFlow<Result<(), async_lsp::Error>> {
diff --git a/crates/nargo/Cargo.toml b/crates/nargo/Cargo.toml
index dce7b098aaa..6c053cba931 100644
--- a/crates/nargo/Cargo.toml
+++ b/crates/nargo/Cargo.toml
@@ -17,6 +17,7 @@ noirc_driver.workspace = true
 iter-extended.workspace = true
 toml.workspace = true
 serde.workspace = true
+serde_json.workspace = true
 thiserror.workspace = true
 noirc_errors.workspace = true
 base64.workspace = true
\ No newline at end of file
diff --git a/crates/nargo/src/errors.rs b/crates/nargo/src/errors.rs
index e9561aa15a9..2878d9f2db7 100644
--- a/crates/nargo/src/errors.rs
+++ b/crates/nargo/src/errors.rs
@@ -1,4 +1,5 @@
 use acvm::pwg::OpcodeResolutionError;
+use noirc_abi::errors::{AbiError, InputParserError};
 use thiserror::Error;
 
 #[derive(Debug, Error)]
@@ -10,4 +11,21 @@ pub enum NargoError {
     /// ACIR circuit solving error
     #[error(transparent)]
     SolvingError(#[from] OpcodeResolutionError),
+
+    #[error(transparent)]
+    ForeignCallError(#[from] ForeignCallError),
+}
+
+#[derive(Debug, Error)]
+pub enum ForeignCallError {
+    #[error("Foreign call inputs needed for execution are missing")]
+    MissingForeignCallInputs,
+
+    /// ABI encoding/decoding error
+    #[error(transparent)]
+    AbiError(#[from] AbiError),
+
+    /// Input parsing error
+    #[error(transparent)]
+    InputParserError(#[from] InputParserError),
 }
diff --git a/crates/nargo/src/manifest/mod.rs b/crates/nargo/src/manifest/mod.rs
index ea51d622d82..f5a247cf72a 100644
--- a/crates/nargo/src/manifest/mod.rs
+++ b/crates/nargo/src/manifest/mod.rs
@@ -64,7 +64,9 @@ pub struct WorkspaceConfig {
 #[allow(dead_code)]
 #[derive(Default, Debug, Deserialize, Clone)]
 pub struct PackageMetadata {
-    // Note: a package name is not needed unless there is a registry
+    #[serde(default = "panic_missing_name")]
+    pub name: String,
+    description: Option<String>,
     authors: Vec<String>,
     // If not compiler version is supplied, the latest is used
     // For now, we state that all packages must be compiled under the same
@@ -76,6 +78,26 @@ pub struct PackageMetadata {
     license: Option<String>,
 }
 
+// TODO: Remove this after a couple of breaking releases (added in 0.10.0)
+fn panic_missing_name() -> String {
+    panic!(
+        r#"
+
+Failed to parse `Nargo.toml`.
+    
+`Nargo.toml` now requires a "name" field for Noir packages.
+
+```toml
+[package]
+name = "package_name"
+```
+
+Modify your `Nargo.toml` similarly to above and rerun the command.
+
+"#
+    )
+}
+
 #[derive(Debug, Deserialize, Clone)]
 #[serde(untagged)]
 /// Enum representing the different types of ways to
@@ -90,6 +112,7 @@ fn parse_standard_toml() {
     let src = r#"
 
         [package]
+        name = "test"
         authors = ["kev", "foo"]
         compiler_version = "0.1"
 
diff --git a/crates/nargo/src/ops/execute.rs b/crates/nargo/src/ops/execute.rs
index f5b2cd7a3b6..13ea64ed261 100644
--- a/crates/nargo/src/ops/execute.rs
+++ b/crates/nargo/src/ops/execute.rs
@@ -1,11 +1,11 @@
-use acvm::acir::brillig::{ForeignCallResult, Value};
-use acvm::pwg::{ACVMStatus, ForeignCallWaitInfo, ACVM};
+use acvm::pwg::{ACVMStatus, ACVM};
 use acvm::BlackBoxFunctionSolver;
 use acvm::{acir::circuit::Circuit, acir::native_types::WitnessMap};
-use iter_extended::vecmap;
 
 use crate::NargoError;
 
+use super::foreign_calls::ForeignCall;
+
 pub fn execute_circuit<B: BlackBoxFunctionSolver + Default>(
     _backend: &B,
     circuit: Circuit,
@@ -22,11 +22,9 @@ pub fn execute_circuit<B: BlackBoxFunctionSolver + Default>(
                 unreachable!("Execution should not stop while in `InProgress` state.")
             }
             ACVMStatus::Failure(error) => return Err(error.into()),
-            ACVMStatus::RequiresForeignCall => {
-                while let Some(foreign_call) = acvm.get_pending_foreign_call() {
-                    let foreign_call_result = execute_foreign_call(foreign_call);
-                    acvm.resolve_pending_foreign_call(foreign_call_result);
-                }
+            ACVMStatus::RequiresForeignCall(foreign_call) => {
+                let foreign_call_result = ForeignCall::execute(&foreign_call)?;
+                acvm.resolve_pending_foreign_call(foreign_call_result);
             }
         }
     }
@@ -34,41 +32,3 @@ pub fn execute_circuit<B: BlackBoxFunctionSolver + Default>(
     let solved_witness = acvm.finalize();
     Ok(solved_witness)
 }
-
-fn execute_foreign_call(foreign_call: &ForeignCallWaitInfo) -> ForeignCallResult {
-    // TODO(#1615): Nargo only supports "oracle_print_**_impl" functions  that print a singular value or an array and nothing else
-    // This should be expanded in a general logging refactor
-    match foreign_call.function.as_str() {
-        // TODO(#1910): Move to an enum and don't match directly on these strings
-        "oracle_print_impl" => {
-            let values = &foreign_call.inputs[0];
-            println!("{:?}", values[0].to_field().to_hex());
-            values[0].into()
-        }
-        "oracle_print_array_impl" => {
-            let mut outputs_hex = Vec::new();
-            for values in &foreign_call.inputs {
-                for value in values {
-                    outputs_hex.push(value.to_field().to_hex());
-                }
-            }
-            // Join all of the hex strings using a comma
-            let comma_separated_elements = outputs_hex.join(", ");
-            let output_witnesses_string = "[".to_owned() + &comma_separated_elements + "]";
-            println!("{output_witnesses_string}");
-
-            foreign_call.inputs[0][0].into()
-        }
-        "get_number_sequence" => {
-            let sequence_length: u128 = foreign_call.inputs[0][0].to_field().to_u128();
-
-            vecmap(0..sequence_length, Value::from).into()
-        }
-        "get_reverse_number_sequence" => {
-            let sequence_length: u128 = foreign_call.inputs[0][0].to_field().to_u128();
-
-            vecmap((0..sequence_length).rev(), Value::from).into()
-        }
-        _ => panic!("unexpected foreign call type"),
-    }
-}
diff --git a/crates/nargo/src/ops/foreign_calls.rs b/crates/nargo/src/ops/foreign_calls.rs
new file mode 100644
index 00000000000..4bbd4eb58bc
--- /dev/null
+++ b/crates/nargo/src/ops/foreign_calls.rs
@@ -0,0 +1,93 @@
+use acvm::{
+    acir::brillig::{ForeignCallResult, Value},
+    pwg::ForeignCallWaitInfo,
+};
+use iter_extended::vecmap;
+use noirc_abi::{decode_string_value, input_parser::InputValueDisplay, AbiType};
+
+use crate::errors::ForeignCallError;
+
+/// This enumeration represents the Brillig foreign calls that are natively supported by nargo.
+/// After resolution of a foreign call, nargo will restart execution of the ACVM
+pub(crate) enum ForeignCall {
+    Println,
+    Sequence,
+    ReverseSequence,
+}
+
+impl std::fmt::Display for ForeignCall {
+    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
+        write!(f, "{}", self.name())
+    }
+}
+
+impl ForeignCall {
+    pub(crate) fn name(&self) -> &'static str {
+        match self {
+            ForeignCall::Println => "println",
+            ForeignCall::Sequence => "get_number_sequence",
+            ForeignCall::ReverseSequence => "get_reverse_number_sequence",
+        }
+    }
+
+    pub(crate) fn lookup(op_name: &str) -> Option<ForeignCall> {
+        match op_name {
+            "println" => Some(ForeignCall::Println),
+            "get_number_sequence" => Some(ForeignCall::Sequence),
+            "get_reverse_number_sequence" => Some(ForeignCall::ReverseSequence),
+            _ => None,
+        }
+    }
+
+    pub(crate) fn execute(
+        foreign_call: &ForeignCallWaitInfo,
+    ) -> Result<ForeignCallResult, ForeignCallError> {
+        let foreign_call_name = foreign_call.function.as_str();
+        match Self::lookup(foreign_call_name) {
+            Some(ForeignCall::Println) => {
+                Self::execute_println(&foreign_call.inputs)?;
+                Ok(ForeignCallResult { values: vec![] })
+            }
+            Some(ForeignCall::Sequence) => {
+                let sequence_length: u128 = foreign_call.inputs[0][0].to_field().to_u128();
+
+                Ok(vecmap(0..sequence_length, Value::from).into())
+            }
+            Some(ForeignCall::ReverseSequence) => {
+                let sequence_length: u128 = foreign_call.inputs[0][0].to_field().to_u128();
+
+                Ok(vecmap((0..sequence_length).rev(), Value::from).into())
+            }
+            None => panic!("unexpected foreign call {:?}", foreign_call_name),
+        }
+    }
+
+    fn execute_println(foreign_call_inputs: &[Vec<Value>]) -> Result<(), ForeignCallError> {
+        let (abi_type, input_values) = fetch_abi_type(foreign_call_inputs)?;
+
+        // We must use a flat map here as each value in a struct will be in a separate input value
+        let mut input_values_as_fields =
+            input_values.iter().flat_map(|values| values.iter().map(|value| value.to_field()));
+
+        let input_value_display =
+            InputValueDisplay::try_from_fields(&mut input_values_as_fields, abi_type)?;
+
+        println!("{input_value_display}");
+        Ok(())
+    }
+}
+
+/// Fetch the abi type from the foreign call input
+/// The remaining input values should hold the values to be printed
+fn fetch_abi_type(
+    foreign_call_inputs: &[Vec<Value>],
+) -> Result<(AbiType, &[Vec<Value>]), ForeignCallError> {
+    let (abi_type_as_values, input_values) =
+        foreign_call_inputs.split_last().ok_or(ForeignCallError::MissingForeignCallInputs)?;
+    let abi_type_as_fields = vecmap(abi_type_as_values, |value| value.to_field());
+    let abi_type_as_string = decode_string_value(&abi_type_as_fields);
+    let abi_type: AbiType = serde_json::from_str(&abi_type_as_string)
+        .map_err(|err| ForeignCallError::InputParserError(err.into()))?;
+
+    Ok((abi_type, input_values))
+}
diff --git a/crates/nargo/src/ops/mod.rs b/crates/nargo/src/ops/mod.rs
index 8a0cce4b8c5..6d55e5b0dad 100644
--- a/crates/nargo/src/ops/mod.rs
+++ b/crates/nargo/src/ops/mod.rs
@@ -6,6 +6,7 @@ pub use self::verify::verify_proof;
 
 mod codegen_verifier;
 mod execute;
+mod foreign_calls;
 mod preprocess;
 mod prove;
 mod verify;
diff --git a/crates/nargo_cli/Cargo.toml b/crates/nargo_cli/Cargo.toml
index 0fd2ce19927..a1c15997ef5 100644
--- a/crates/nargo_cli/Cargo.toml
+++ b/crates/nargo_cli/Cargo.toml
@@ -48,7 +48,7 @@ color-eyre = "0.6.2"
 tokio = { version = "1.0", features = ["io-std"] }
 
 # Backends
-acvm-backend-barretenberg = { version = "0.9.0", default-features = false }
+acvm-backend-barretenberg = { version = "0.10.0", default-features = false }
 
 [dev-dependencies]
 tempdir = "0.3.7"
@@ -62,3 +62,4 @@ default = ["plonk_bn254"]
 plonk_bn254 = ["acvm-backend-barretenberg/native"]
 plonk_bn254_wasm = ["acvm-backend-barretenberg/wasm"]
 flat_witness = ["acvm-backend-barretenberg/native"]
+
diff --git a/crates/nargo_cli/build.rs b/crates/nargo_cli/build.rs
index e453f51777c..d889ba6856c 100644
--- a/crates/nargo_cli/build.rs
+++ b/crates/nargo_cli/build.rs
@@ -29,11 +29,10 @@ fn main() {
     }
 
     let out_dir = env::var("OUT_DIR").unwrap();
-    let destination = Path::new(&out_dir).join("prove_and_verify.rs");
+    let destination = Path::new(&out_dir).join("execute.rs");
     let mut test_file = File::create(destination).unwrap();
 
-    generate_tests(&mut test_file, false);
-    generate_tests(&mut test_file, true);
+    generate_tests(&mut test_file);
 }
 
 fn load_conf(conf_path: &Path) -> BTreeMap<String, Vec<String>> {
@@ -54,15 +53,14 @@ fn load_conf(conf_path: &Path) -> BTreeMap<String, Vec<String>> {
     conf_data
 }
 
-fn generate_tests(test_file: &mut File, experimental_ssa: bool) {
+fn generate_tests(test_file: &mut File) {
     // Try to find the directory that Cargo sets when it is running; otherwise fallback to assuming the CWD
     // is the root of the repository and append the crate path
     let manifest_dir = match std::env::var("CARGO_MANIFEST_DIR") {
         Ok(dir) => PathBuf::from(dir),
         Err(_) => std::env::current_dir().unwrap().join("crates").join("nargo_cli"),
     };
-    // Choose the test directory depending on whether we are in the SSA refactor module or not
-    let test_sub_dir = if experimental_ssa { "test_data_ssa_refactor" } else { "test_data" };
+    let test_sub_dir = "test_data";
     let test_data_dir = manifest_dir.join("tests").join(test_sub_dir);
     let config_path = test_data_dir.join("config.toml");
 
@@ -93,16 +91,13 @@ fn generate_tests(test_file: &mut File, experimental_ssa: bool) {
             r#"
 {exclude_macro}
 #[test]
-fn prove_and_verify_{test_sub_dir}_{test_name}() {{
+fn execute_{test_sub_dir}_{test_name}() {{
     let test_program_dir = PathBuf::from("{test_dir}");
 
     let mut cmd = Command::cargo_bin("nargo").unwrap();
     cmd.arg("--program-dir").arg(test_program_dir);
     cmd.arg(if {is_workspace} {{ "test" }} else {{ "execute" }});
-    if {experimental_ssa} {{
-        cmd.arg("--experimental-ssa");
-    }};
-    
+
 
     if {should_fail} {{
         cmd.assert().failure();
diff --git a/crates/nargo_cli/src/cli/check_cmd.rs b/crates/nargo_cli/src/cli/check_cmd.rs
index 5abef7bfb2a..9a0a2f77e7c 100644
--- a/crates/nargo_cli/src/cli/check_cmd.rs
+++ b/crates/nargo_cli/src/cli/check_cmd.rs
@@ -5,7 +5,7 @@ use iter_extended::btree_map;
 use noirc_abi::{AbiParameter, AbiType, MAIN_RETURN_NAME};
 use noirc_driver::{check_crate, compute_function_signature, CompileOptions};
 use noirc_errors::reporter::ReportedErrors;
-use noirc_frontend::hir::Context;
+use noirc_frontend::{graph::CrateId, hir::Context};
 use std::path::{Path, PathBuf};
 
 use super::fs::write_to_file;
@@ -36,15 +36,11 @@ fn check_from_path<B: Backend>(
     program_dir: &Path,
     compile_options: &CompileOptions,
 ) -> Result<(), CliError<B>> {
-    let mut context = resolve_root_manifest(program_dir)?;
-    check_crate_and_report_errors(
-        &mut context,
-        compile_options.deny_warnings,
-        compile_options.experimental_ssa,
-    )?;
+    let (mut context, crate_id) = resolve_root_manifest(program_dir, None)?;
+    check_crate_and_report_errors(&mut context, crate_id, compile_options.deny_warnings)?;
 
     // XXX: We can have a --overwrite flag to determine if you want to overwrite the Prover/Verifier.toml files
-    if let Some((parameters, return_type)) = compute_function_signature(&context) {
+    if let Some((parameters, return_type)) = compute_function_signature(&context, &crate_id) {
         // XXX: The root config should return an enum to determine if we are looking for .json or .toml
         // For now it is hard-coded to be toml.
         //
@@ -217,9 +213,9 @@ d2 = ["", "", ""]
 /// and errors found.
 pub(crate) fn check_crate_and_report_errors(
     context: &mut Context,
+    crate_id: CrateId,
     deny_warnings: bool,
-    enable_slices: bool,
 ) -> Result<(), ReportedErrors> {
-    let result = check_crate(context, deny_warnings, enable_slices).map(|warnings| ((), warnings));
+    let result = check_crate(context, crate_id, deny_warnings).map(|warnings| ((), warnings));
     super::compile_cmd::report_errors(result, context, deny_warnings)
 }
diff --git a/crates/nargo_cli/src/cli/codegen_verifier_cmd.rs b/crates/nargo_cli/src/cli/codegen_verifier_cmd.rs
index c19ed5df3a6..cedf558bcb8 100644
--- a/crates/nargo_cli/src/cli/codegen_verifier_cmd.rs
+++ b/crates/nargo_cli/src/cli/codegen_verifier_cmd.rs
@@ -52,7 +52,7 @@ pub(crate) fn run<B: Backend>(
         }
         None => {
             let (program, _) =
-                compile_circuit(backend, config.program_dir.as_ref(), &args.compile_options)?;
+                compile_circuit(backend, None, config.program_dir.as_ref(), &args.compile_options)?;
             let common_reference_string =
                 update_common_reference_string(backend, &common_reference_string, &program.circuit)
                     .map_err(CliError::CommonReferenceStringError)?;
diff --git a/crates/nargo_cli/src/cli/compile_cmd.rs b/crates/nargo_cli/src/cli/compile_cmd.rs
index da945e6e15e..fbaecb606a1 100644
--- a/crates/nargo_cli/src/cli/compile_cmd.rs
+++ b/crates/nargo_cli/src/cli/compile_cmd.rs
@@ -57,9 +57,9 @@ pub(crate) fn run<B: Backend>(
 
     // If contracts is set we're compiling every function in a 'contract' rather than just 'main'.
     if args.contracts {
-        let mut context = resolve_root_manifest(&config.program_dir)?;
+        let (mut context, crate_id) = resolve_root_manifest(&config.program_dir, None)?;
 
-        let result = compile_contracts(&mut context, &args.compile_options);
+        let result = compile_contracts(&mut context, crate_id, &args.compile_options);
         let contracts = report_errors(result, &context, args.compile_options.deny_warnings)?;
 
         // TODO(#1389): I wonder if it is incorrect for nargo-core to know anything about contracts.
@@ -101,7 +101,8 @@ pub(crate) fn run<B: Backend>(
             );
         }
     } else {
-        let (program, _) = compile_circuit(backend, &config.program_dir, &args.compile_options)?;
+        let (program, _) =
+            compile_circuit(backend, None, &config.program_dir, &args.compile_options)?;
         common_reference_string =
             update_common_reference_string(backend, &common_reference_string, &program.circuit)
                 .map_err(CliError::CommonReferenceStringError)?;
@@ -119,11 +120,12 @@ pub(crate) fn run<B: Backend>(
 
 pub(crate) fn compile_circuit<B: Backend>(
     backend: &B,
+    package: Option<String>,
     program_dir: &Path,
     compile_options: &CompileOptions,
 ) -> Result<(CompiledProgram, Context), CliError<B>> {
-    let mut context = resolve_root_manifest(program_dir)?;
-    let result = compile_main(&mut context, compile_options);
+    let (mut context, crate_id) = resolve_root_manifest(program_dir, package)?;
+    let result = compile_main(&mut context, crate_id, compile_options);
     let mut program = report_errors(result, &context, compile_options.deny_warnings)?;
 
     // Apply backend specific optimizations.
diff --git a/crates/nargo_cli/src/cli/execute_cmd.rs b/crates/nargo_cli/src/cli/execute_cmd.rs
index d8b764a6282..eaaea6d4ab3 100644
--- a/crates/nargo_cli/src/cli/execute_cmd.rs
+++ b/crates/nargo_cli/src/cli/execute_cmd.rs
@@ -61,7 +61,7 @@ fn execute_with_path<B: Backend>(
     prover_name: String,
     compile_options: &CompileOptions,
 ) -> Result<(Option<InputValue>, WitnessMap), CliError<B>> {
-    let (compiled_program, context) = compile_circuit(backend, program_dir, compile_options)?;
+    let (compiled_program, context) = compile_circuit(backend, None, program_dir, compile_options)?;
     let CompiledProgram { abi, circuit, debug } = compiled_program;
 
     // Parse the initial witness values from Prover.toml
diff --git a/crates/nargo_cli/src/cli/gates_cmd.rs b/crates/nargo_cli/src/cli/info_cmd.rs
similarity index 64%
rename from crates/nargo_cli/src/cli/gates_cmd.rs
rename to crates/nargo_cli/src/cli/info_cmd.rs
index 030daef9719..7ad0a2caf8c 100644
--- a/crates/nargo_cli/src/cli/gates_cmd.rs
+++ b/crates/nargo_cli/src/cli/info_cmd.rs
@@ -8,27 +8,31 @@ use crate::errors::CliError;
 
 use super::NargoConfig;
 
-/// Counts the occurrences of different gates in circuit
+/// Provides detailed informaton on a circuit
+/// Current information provided:
+/// 1. The number of ACIR opcodes
+/// 2. Counts the final number gates in the circuit used by a backend
 #[derive(Debug, Clone, Args)]
-pub(crate) struct GatesCommand {
+pub(crate) struct InfoCommand {
     #[clap(flatten)]
     compile_options: CompileOptions,
 }
 
 pub(crate) fn run<B: Backend>(
     backend: &B,
-    args: GatesCommand,
+    args: InfoCommand,
     config: NargoConfig,
 ) -> Result<(), CliError<B>> {
-    count_gates_with_path(backend, config.program_dir, &args.compile_options)
+    count_opcodes_and_gates_with_path(backend, config.program_dir, &args.compile_options)
 }
 
-fn count_gates_with_path<B: Backend, P: AsRef<Path>>(
+fn count_opcodes_and_gates_with_path<B: Backend, P: AsRef<Path>>(
     backend: &B,
     program_dir: P,
     compile_options: &CompileOptions,
 ) -> Result<(), CliError<B>> {
-    let (compiled_program, _) = compile_circuit(backend, program_dir.as_ref(), compile_options)?;
+    let (compiled_program, _) =
+        compile_circuit(backend, None, program_dir.as_ref(), compile_options)?;
     let num_opcodes = compiled_program.circuit.opcodes.len();
 
     println!(
diff --git a/crates/nargo_cli/src/cli/init_cmd.rs b/crates/nargo_cli/src/cli/init_cmd.rs
new file mode 100644
index 00000000000..77613611343
--- /dev/null
+++ b/crates/nargo_cli/src/cli/init_cmd.rs
@@ -0,0 +1,58 @@
+use crate::{
+    constants::{PKG_FILE, SRC_DIR},
+    errors::CliError,
+};
+
+use super::fs::{create_named_dir, write_to_file};
+use super::{NargoConfig, CARGO_PKG_VERSION};
+use acvm::Backend;
+use clap::Args;
+use std::path::PathBuf;
+
+/// Create a Noir project in the current directory.
+#[derive(Debug, Clone, Args)]
+pub(crate) struct InitCommand;
+
+const EXAMPLE: &str = r#"fn main(x : Field, y : pub Field) {
+    assert(x != y);
+}
+
+#[test]
+fn test_main() {
+    main(1, 2);
+
+    // Uncomment to make test fail
+    // main(1, 1);
+}
+"#;
+
+pub(crate) fn run<B: Backend>(
+    // Backend is currently unused, but we might want to use it to inform the "new" template in the future
+    _backend: &B,
+    _args: InitCommand,
+    config: NargoConfig,
+) -> Result<(), CliError<B>> {
+    initialize_project(config.program_dir);
+    Ok(())
+}
+
+/// Initializes a new Noir project in `package_dir`.
+pub(crate) fn initialize_project(package_dir: PathBuf) {
+    // TODO: Should this reject if we have non-Unicode filepaths?
+    let package_name = package_dir.file_name().expect("Expected a filename").to_string_lossy();
+    let src_dir = package_dir.join(SRC_DIR);
+    create_named_dir(&src_dir, "src");
+
+    let toml_contents = format!(
+        r#"[package]
+name = "{package_name}"
+authors = [""]
+compiler_version = "{CARGO_PKG_VERSION}"
+
+[dependencies]"#
+    );
+
+    write_to_file(toml_contents.as_bytes(), &package_dir.join(PKG_FILE));
+    write_to_file(EXAMPLE.as_bytes(), &src_dir.join("main.nr"));
+    println!("Project successfully created! Binary located at {}", package_dir.display());
+}
diff --git a/crates/nargo_cli/src/cli/mod.rs b/crates/nargo_cli/src/cli/mod.rs
index 91ad14f9458..8ce66db1b7b 100644
--- a/crates/nargo_cli/src/cli/mod.rs
+++ b/crates/nargo_cli/src/cli/mod.rs
@@ -12,7 +12,8 @@ mod check_cmd;
 mod codegen_verifier_cmd;
 mod compile_cmd;
 mod execute_cmd;
-mod gates_cmd;
+mod info_cmd;
+mod init_cmd;
 mod lsp_cmd;
 mod new_cmd;
 mod prove_cmd;
@@ -48,13 +49,15 @@ pub(crate) struct NargoConfig {
 enum NargoCommand {
     Check(check_cmd::CheckCommand),
     CodegenVerifier(codegen_verifier_cmd::CodegenVerifierCommand),
+    #[command(alias = "build")]
     Compile(compile_cmd::CompileCommand),
     New(new_cmd::NewCommand),
+    Init(init_cmd::InitCommand),
     Execute(execute_cmd::ExecuteCommand),
     Prove(prove_cmd::ProveCommand),
     Verify(verify_cmd::VerifyCommand),
     Test(test_cmd::TestCommand),
-    Gates(gates_cmd::GatesCommand),
+    Info(info_cmd::InfoCommand),
     Lsp(lsp_cmd::LspCommand),
 }
 
@@ -62,7 +65,7 @@ pub fn start_cli() -> eyre::Result<()> {
     let NargoCli { command, mut config } = NargoCli::parse();
 
     // Search through parent directories to find package root if necessary.
-    if !matches!(command, NargoCommand::New(_) | NargoCommand::Lsp(_)) {
+    if !matches!(command, NargoCommand::New(_) | NargoCommand::Init(_) | NargoCommand::Lsp(_)) {
         config.program_dir = find_package_root(&config.program_dir)?;
     }
 
@@ -70,13 +73,14 @@ pub fn start_cli() -> eyre::Result<()> {
 
     match command {
         NargoCommand::New(args) => new_cmd::run(&backend, args, config),
+        NargoCommand::Init(args) => init_cmd::run(&backend, args, config),
         NargoCommand::Check(args) => check_cmd::run(&backend, args, config),
         NargoCommand::Compile(args) => compile_cmd::run(&backend, args, config),
         NargoCommand::Execute(args) => execute_cmd::run(&backend, args, config),
         NargoCommand::Prove(args) => prove_cmd::run(&backend, args, config),
         NargoCommand::Verify(args) => verify_cmd::run(&backend, args, config),
         NargoCommand::Test(args) => test_cmd::run(&backend, args, config),
-        NargoCommand::Gates(args) => gates_cmd::run(&backend, args, config),
+        NargoCommand::Info(args) => info_cmd::run(&backend, args, config),
         NargoCommand::CodegenVerifier(args) => codegen_verifier_cmd::run(&backend, args, config),
         NargoCommand::Lsp(args) => lsp_cmd::run(&backend, args, config),
     }?;
@@ -87,9 +91,13 @@ pub fn start_cli() -> eyre::Result<()> {
 // FIXME: I not sure that this is the right place for this tests.
 #[cfg(test)]
 mod tests {
+    use fm::FileManager;
     use noirc_driver::{check_crate, create_local_crate};
     use noirc_errors::reporter;
-    use noirc_frontend::{graph::CrateType, hir::Context};
+    use noirc_frontend::{
+        graph::{CrateGraph, CrateType},
+        hir::Context,
+    };
 
     use std::path::{Path, PathBuf};
 
@@ -98,11 +106,13 @@ mod tests {
     /// Compiles a file and returns true if compilation was successful
     ///
     /// This is used for tests.
-    fn file_compiles<P: AsRef<Path>>(root_file: P) -> bool {
-        let mut context = Context::default();
-        create_local_crate(&mut context, &root_file, CrateType::Binary);
+    fn file_compiles(root_dir: &Path, root_file: &Path) -> bool {
+        let fm = FileManager::new(root_dir);
+        let graph = CrateGraph::default();
+        let mut context = Context::new(fm, graph);
+        let crate_id = create_local_crate(&mut context, root_file, CrateType::Binary);
 
-        let result = check_crate(&mut context, false, false);
+        let result = check_crate(&mut context, crate_id, false);
         let success = result.is_ok();
 
         let errors = match result {
@@ -119,10 +129,10 @@ mod tests {
         let pass_dir =
             PathBuf::from(env!("CARGO_MANIFEST_DIR")).join(format!("{TEST_DATA_DIR}/pass"));
 
-        let paths = std::fs::read_dir(pass_dir).unwrap();
+        let paths = std::fs::read_dir(&pass_dir).unwrap();
         for path in paths.flatten() {
             let path = path.path();
-            assert!(file_compiles(&path), "path: {}", path.display());
+            assert!(file_compiles(&pass_dir, &path), "path: {}", path.display());
         }
     }
 
@@ -131,10 +141,10 @@ mod tests {
         let fail_dir =
             PathBuf::from(env!("CARGO_MANIFEST_DIR")).join(format!("{TEST_DATA_DIR}/fail"));
 
-        let paths = std::fs::read_dir(fail_dir).unwrap();
+        let paths = std::fs::read_dir(&fail_dir).unwrap();
         for path in paths.flatten() {
             let path = path.path();
-            assert!(!file_compiles(&path), "path: {}", path.display());
+            assert!(!file_compiles(&fail_dir, &path), "path: {}", path.display());
         }
     }
 }
diff --git a/crates/nargo_cli/src/cli/new_cmd.rs b/crates/nargo_cli/src/cli/new_cmd.rs
index 5868c1e820e..66c29eb3292 100644
--- a/crates/nargo_cli/src/cli/new_cmd.rs
+++ b/crates/nargo_cli/src/cli/new_cmd.rs
@@ -1,16 +1,11 @@
-use crate::{
-    constants::{PKG_FILE, SRC_DIR},
-    errors::CliError,
-};
+use crate::errors::CliError;
 
-use super::fs::{create_named_dir, write_to_file};
-use super::{NargoConfig, CARGO_PKG_VERSION};
+use super::{init_cmd::initialize_project, NargoConfig};
 use acvm::Backend;
 use clap::Args;
-use const_format::formatcp;
-use std::path::{Path, PathBuf};
+use std::path::PathBuf;
 
-/// Create a new binary project
+/// Create a Noir project in a new directory.
 #[derive(Debug, Clone, Args)]
 pub(crate) struct NewCommand {
     /// Name of the package
@@ -19,27 +14,6 @@ pub(crate) struct NewCommand {
     path: Option<PathBuf>,
 }
 
-const SETTINGS: &str = formatcp!(
-    r#"[package]
-authors = [""]
-compiler_version = "{CARGO_PKG_VERSION}"
-
-[dependencies]"#,
-);
-
-const EXAMPLE: &str = r#"fn main(x : Field, y : pub Field) {
-    assert(x != y);
-}
-
-#[test]
-fn test_main() {
-    main(1, 2);
-
-    // Uncomment to make test fail
-    // main(1, 1);
-}
-"#;
-
 pub(crate) fn run<B: Backend>(
     // Backend is currently unused, but we might want to use it to inform the "new" template in the future
     _backend: &B,
@@ -52,11 +26,6 @@ pub(crate) fn run<B: Backend>(
         return Err(CliError::DestinationAlreadyExists(package_dir));
     }
 
-    let src_dir = package_dir.join(Path::new(SRC_DIR));
-    create_named_dir(&src_dir, "src");
-
-    write_to_file(SETTINGS.as_bytes(), &package_dir.join(PKG_FILE));
-    write_to_file(EXAMPLE.as_bytes(), &src_dir.join("main.nr"));
-    println!("Project successfully created! Binary located at {}", package_dir.display());
+    initialize_project(package_dir);
     Ok(())
 }
diff --git a/crates/nargo_cli/src/cli/prove_cmd.rs b/crates/nargo_cli/src/cli/prove_cmd.rs
index 346638835e3..92e9599cd8b 100644
--- a/crates/nargo_cli/src/cli/prove_cmd.rs
+++ b/crates/nargo_cli/src/cli/prove_cmd.rs
@@ -49,6 +49,9 @@ pub(crate) struct ProveCommand {
 
     #[clap(flatten)]
     compile_options: CompileOptions,
+
+    #[clap(long)]
+    package: Option<String>,
 }
 
 pub(crate) fn run<B: Backend>(
@@ -67,6 +70,7 @@ pub(crate) fn run<B: Backend>(
         args.proof_name,
         args.prover_name,
         args.verifier_name,
+        args.package,
         config.program_dir,
         proof_dir,
         circuit_build_path,
@@ -83,6 +87,7 @@ pub(crate) fn prove_with_path<B: Backend, P: AsRef<Path>>(
     proof_name: Option<String>,
     prover_name: String,
     verifier_name: String,
+    package: Option<String>,
     program_dir: P,
     proof_dir: P,
     circuit_build_path: Option<PathBuf>,
@@ -104,7 +109,7 @@ pub(crate) fn prove_with_path<B: Backend, P: AsRef<Path>>(
         }
         None => {
             let (program, context) =
-                compile_circuit(backend, program_dir.as_ref(), compile_options)?;
+                compile_circuit(backend, package, program_dir.as_ref(), compile_options)?;
             let common_reference_string =
                 update_common_reference_string(backend, &common_reference_string, &program.circuit)
                     .map_err(CliError::CommonReferenceStringError)?;
diff --git a/crates/nargo_cli/src/cli/test_cmd.rs b/crates/nargo_cli/src/cli/test_cmd.rs
index 5634c913c84..c1aa359e724 100644
--- a/crates/nargo_cli/src/cli/test_cmd.rs
+++ b/crates/nargo_cli/src/cli/test_cmd.rs
@@ -4,7 +4,7 @@ use acvm::{acir::native_types::WitnessMap, Backend};
 use clap::Args;
 use nargo::ops::execute_circuit;
 use noirc_driver::{compile_no_check, CompileOptions};
-use noirc_frontend::{graph::LOCAL_CRATE, hir::Context, node_interner::FuncId};
+use noirc_frontend::{hir::Context, node_interner::FuncId};
 use termcolor::{Color, ColorChoice, ColorSpec, StandardStream, WriteColor};
 
 use crate::{
@@ -20,6 +20,10 @@ pub(crate) struct TestCommand {
     /// If given, only tests with names containing this string will be run
     test_name: Option<String>,
 
+    /// Display output of `println` statements
+    #[arg(long)]
+    show_output: bool,
+
     #[clap(flatten)]
     compile_options: CompileOptions,
 }
@@ -31,27 +35,24 @@ pub(crate) fn run<B: Backend>(
 ) -> Result<(), CliError<B>> {
     let test_name: String = args.test_name.unwrap_or_else(|| "".to_owned());
 
-    run_tests(backend, &config.program_dir, &test_name, &args.compile_options)
+    run_tests(backend, &config.program_dir, &test_name, args.show_output, &args.compile_options)
 }
 
 fn run_tests<B: Backend>(
     backend: &B,
     program_dir: &Path,
     test_name: &str,
+    show_output: bool,
     compile_options: &CompileOptions,
 ) -> Result<(), CliError<B>> {
-    let mut context = resolve_root_manifest(program_dir)?;
-    check_crate_and_report_errors(
-        &mut context,
-        compile_options.deny_warnings,
-        compile_options.experimental_ssa,
-    )?;
-
-    let test_functions = match context.crate_graph.crate_type(LOCAL_CRATE) {
+    let (mut context, crate_id) = resolve_root_manifest(program_dir, None)?;
+    check_crate_and_report_errors(&mut context, crate_id, compile_options.deny_warnings)?;
+
+    let test_functions = match context.crate_graph.crate_type(crate_id) {
         noirc_frontend::graph::CrateType::Workspace => {
             context.get_all_test_functions_in_workspace_matching(test_name)
         }
-        _ => context.get_all_test_functions_in_crate_matching(&LOCAL_CRATE, test_name),
+        _ => context.get_all_test_functions_in_crate_matching(&crate_id, test_name),
     };
 
     println!("Running {} test functions...", test_functions.len());
@@ -60,12 +61,11 @@ fn run_tests<B: Backend>(
     let writer = StandardStream::stderr(ColorChoice::Always);
     let mut writer = writer.lock();
 
-    for test_function in test_functions {
-        let test_name = context.function_name(&test_function);
+    for (test_name, test_function) in test_functions {
         writeln!(writer, "Testing {test_name}...").expect("Failed to write to stdout");
         writer.flush().ok();
 
-        match run_test(backend, test_name, test_function, &context, compile_options) {
+        match run_test(backend, &test_name, test_function, &context, show_output, compile_options) {
             Ok(_) => {
                 writer.set_color(ColorSpec::new().set_fg(Some(Color::Green))).ok();
                 writeln!(writer, "ok").ok();
@@ -93,9 +93,10 @@ fn run_test<B: Backend>(
     test_name: &str,
     main: FuncId,
     context: &Context,
+    show_output: bool,
     config: &CompileOptions,
 ) -> Result<(), CliError<B>> {
-    let mut program = compile_no_check(context, config, main)
+    let mut program = compile_no_check(context, show_output, config, main)
         .map_err(|_| CliError::Generic(format!("Test '{test_name}' failed to compile")))?;
     // Note: We could perform this test using the unoptimized ACIR as generated by `compile_no_check`.
     program.circuit = optimize_circuit(backend, program.circuit).unwrap().0;
diff --git a/crates/nargo_cli/src/cli/verify_cmd.rs b/crates/nargo_cli/src/cli/verify_cmd.rs
index cc85159e488..f9068c66c9c 100644
--- a/crates/nargo_cli/src/cli/verify_cmd.rs
+++ b/crates/nargo_cli/src/cli/verify_cmd.rs
@@ -83,7 +83,8 @@ fn verify_with_path<B: Backend, P: AsRef<Path>>(
             (common_reference_string, program)
         }
         None => {
-            let (program, _) = compile_circuit(backend, program_dir.as_ref(), compile_options)?;
+            let (program, _) =
+                compile_circuit(backend, None, program_dir.as_ref(), compile_options)?;
             let common_reference_string =
                 update_common_reference_string(backend, &common_reference_string, &program.circuit)
                     .map_err(CliError::CommonReferenceStringError)?;
diff --git a/crates/nargo_cli/src/resolver.rs b/crates/nargo_cli/src/resolver.rs
index 5fc158d1d7f..5c4e8225ee4 100644
--- a/crates/nargo_cli/src/resolver.rs
+++ b/crates/nargo_cli/src/resolver.rs
@@ -3,10 +3,11 @@ use std::{
     path::{Path, PathBuf},
 };
 
-use nargo::manifest::{Dependency, Manifest, PackageManifest};
+use fm::FileManager;
+use nargo::manifest::{Dependency, Manifest, PackageManifest, WorkspaceConfig};
 use noirc_driver::{add_dep, create_local_crate, create_non_local_crate};
 use noirc_frontend::{
-    graph::{CrateId, CrateType},
+    graph::{CrateGraph, CrateId, CrateName, CrateType},
     hir::Context,
 };
 use thiserror::Error;
@@ -49,6 +50,20 @@ pub(crate) enum DependencyResolutionError {
     /// Use workspace as a dependency is not currently supported
     #[error("use workspace as a dependency is not currently supported")]
     WorkspaceDependency,
+
+    /// Multiple workspace roots found in the same workspace
+    #[error("multiple workspace roots found in the same workspace:\n{}\n{}", root.display(), member.display())]
+    MultipleWorkspace { root: PathBuf, member: PathBuf },
+
+    /// Invalid character `-` in package name
+    #[error("invalid character `-` in package name")]
+    InvalidPackageName,
+
+    #[error("package specification `{0}` did not match any packages")]
+    PackageNotFound(String),
+
+    #[error("two packages named `{0}` in this workspace")]
+    PackageCollision(String),
 }
 
 #[derive(Debug, Clone)]
@@ -72,48 +87,36 @@ struct CachedDep {
 /// XXX: Need to handle when a local package changes!
 pub(crate) fn resolve_root_manifest(
     dir_path: &std::path::Path,
-) -> Result<Context, DependencyResolutionError> {
-    let mut context = Context::default();
+    package: Option<String>,
+) -> Result<(Context, CrateId), DependencyResolutionError> {
+    let fm = FileManager::new(dir_path);
+    let graph = CrateGraph::default();
+    let mut context = Context::new(fm, graph);
 
     let manifest_path = super::find_package_manifest(dir_path)?;
     let manifest = super::manifest::parse(&manifest_path)?;
 
-    match manifest {
+    let crate_id = match manifest {
         Manifest::Package(package) => {
             let (entry_path, crate_type) = super::lib_or_bin(dir_path)?;
-            let crate_id = create_local_crate(&mut context, entry_path, crate_type);
 
+            let crate_id = create_local_crate(&mut context, &entry_path, crate_type);
             let pkg_root = manifest_path.parent().expect("Every manifest path has a parent.");
-            resolve_manifest(&mut context, crate_id, package, pkg_root)?;
-        }
-        Manifest::Workspace(workspace) => {
-            let config = workspace.config;
-            let members = config.members;
-
-            let maybe_local = config
-                .default_member
-                .or_else(|| members.last().cloned())
-                .map(|member| dir_path.join(member));
-
-            let default_member = match maybe_local {
-                Some(member) => member,
-                None => {
-                    return Err(DependencyResolutionError::EmptyWorkspace { path: manifest_path })
-                }
-            };
 
-            let (entry_path, _crate_type) = super::lib_or_bin(default_member)?;
-            let _local = create_local_crate(&mut context, entry_path, CrateType::Workspace);
+            resolve_package_manifest(&mut context, crate_id, package, pkg_root)?;
 
-            for member in members {
-                let path: PathBuf = dir_path.join(member);
-                let (entry_path, crate_type) = super::lib_or_bin(path)?;
-                create_non_local_crate(&mut context, entry_path, crate_type);
-            }
+            crate_id
         }
+        Manifest::Workspace(workspace) => resolve_workspace_manifest(
+            &mut context,
+            package,
+            manifest_path,
+            dir_path,
+            workspace.config,
+        )?,
     };
 
-    Ok(context)
+    Ok((context, crate_id))
 }
 
 // Resolves a config file by recursively resolving the dependencies in the config
@@ -122,7 +125,7 @@ pub(crate) fn resolve_root_manifest(
 // We do not need to add stdlib, as it's implicitly
 // imported. However, it may be helpful to have the stdlib imported by the
 // package manager.
-fn resolve_manifest(
+fn resolve_package_manifest(
     context: &mut Context,
     parent_crate: CrateId,
     manifest: PackageManifest,
@@ -154,11 +157,77 @@ fn resolve_manifest(
             return Err(DependencyResolutionError::RemoteDepWithLocalDep { dependency_path });
         }
         // TODO: Why did it create a new resolver?
-        resolve_manifest(context, crate_id, dep_meta.manifest, &dependency_path)?;
+        resolve_package_manifest(context, crate_id, dep_meta.manifest, &dependency_path)?;
     }
     Ok(())
 }
 
+fn resolve_workspace_manifest(
+    context: &mut Context,
+    mut local_package: Option<String>,
+    manifest_path: PathBuf,
+    dir_path: &Path,
+    workspace: WorkspaceConfig,
+) -> Result<CrateId, DependencyResolutionError> {
+    let members = workspace.members;
+    let mut packages = HashMap::new();
+
+    if members.is_empty() {
+        return Err(DependencyResolutionError::EmptyWorkspace { path: manifest_path });
+    }
+
+    for member in &members {
+        let member_path: PathBuf = dir_path.join(member);
+        let member_member_path = super::find_package_manifest(&member_path)?;
+        let member_manifest = super::manifest::parse(&member_member_path)?;
+
+        match member_manifest {
+            Manifest::Package(inner) => {
+                let name: CrateName = inner
+                    .package
+                    .name
+                    .parse()
+                    .map_err(|_name| DependencyResolutionError::InvalidPackageName)?;
+
+                if packages.insert(name.clone(), member_path).is_some() {
+                    return Err(DependencyResolutionError::PackageCollision(name.into()));
+                }
+
+                if local_package.is_none() && workspace.default_member.as_ref() == Some(member) {
+                    local_package = Some(name.into());
+                }
+            }
+            Manifest::Workspace(_) => {
+                return Err(DependencyResolutionError::MultipleWorkspace {
+                    root: manifest_path,
+                    member: member_member_path,
+                })
+            }
+        }
+    }
+
+    let local_package = match local_package {
+        Some(local_package) => {
+            local_package.parse().map_err(|_| DependencyResolutionError::InvalidPackageName)?
+        }
+        None => packages.keys().last().expect("non-empty packages").clone(),
+    };
+
+    let local_crate = packages
+        .remove(&local_package)
+        .ok_or_else(|| DependencyResolutionError::PackageNotFound(local_package.into()))?;
+
+    let (entry_path, _crate_type) = super::lib_or_bin(local_crate)?;
+    let crate_id = create_local_crate(context, &entry_path, CrateType::Workspace);
+
+    for (_, package_path) in packages.drain() {
+        let (entry_path, crate_type) = super::lib_or_bin(package_path)?;
+        create_non_local_crate(context, &entry_path, crate_type);
+    }
+
+    Ok(crate_id)
+}
+
 /// If the dependency is remote, download the dependency
 /// and return the directory path along with the metadata
 /// Needed to fill the CachedDep struct
diff --git a/crates/nargo_cli/tests/prove_and_verify.rs b/crates/nargo_cli/tests/execute.rs
similarity index 84%
rename from crates/nargo_cli/tests/prove_and_verify.rs
rename to crates/nargo_cli/tests/execute.rs
index d581f75c181..f0ada378698 100644
--- a/crates/nargo_cli/tests/prove_and_verify.rs
+++ b/crates/nargo_cli/tests/execute.rs
@@ -13,5 +13,5 @@ mod tests {
     use super::*;
 
     // include tests generated by `build.rs`
-    include!(concat!(env!("OUT_DIR"), "/prove_and_verify.rs"));
+    include!(concat!(env!("OUT_DIR"), "/execute.rs"));
 }
diff --git a/crates/nargo_cli/tests/target_tests_data/fail/basic/Nargo.toml b/crates/nargo_cli/tests/target_tests_data/fail/basic/Nargo.toml
index 5082c6e12ec..a4994991fcc 100644
--- a/crates/nargo_cli/tests/target_tests_data/fail/basic/Nargo.toml
+++ b/crates/nargo_cli/tests/target_tests_data/fail/basic/Nargo.toml
@@ -1,4 +1,5 @@
 [package]
+name = "fail_basic"
 authors = [""]
 compiler_version = "0.1"
 
diff --git a/crates/nargo_cli/tests/target_tests_data/fail/dup_func/Nargo.toml b/crates/nargo_cli/tests/target_tests_data/fail/dup_func/Nargo.toml
index 5082c6e12ec..625528a8c75 100644
--- a/crates/nargo_cli/tests/target_tests_data/fail/dup_func/Nargo.toml
+++ b/crates/nargo_cli/tests/target_tests_data/fail/dup_func/Nargo.toml
@@ -1,4 +1,5 @@
 [package]
+name = "fail_dup_func"
 authors = [""]
 compiler_version = "0.1"
 
diff --git a/crates/nargo_cli/tests/target_tests_data/pass/basic/Nargo.toml b/crates/nargo_cli/tests/target_tests_data/pass/basic/Nargo.toml
index 5082c6e12ec..6c64f17234f 100644
--- a/crates/nargo_cli/tests/target_tests_data/pass/basic/Nargo.toml
+++ b/crates/nargo_cli/tests/target_tests_data/pass/basic/Nargo.toml
@@ -1,4 +1,5 @@
 [package]
+name = "pass_basic"
 authors = [""]
 compiler_version = "0.1"
 
diff --git a/crates/nargo_cli/tests/target_tests_data/pass/import/Nargo.toml b/crates/nargo_cli/tests/target_tests_data/pass/import/Nargo.toml
index 5082c6e12ec..87856bfb269 100644
--- a/crates/nargo_cli/tests/target_tests_data/pass/import/Nargo.toml
+++ b/crates/nargo_cli/tests/target_tests_data/pass/import/Nargo.toml
@@ -1,4 +1,5 @@
 [package]
+name = "pass_import"
 authors = [""]
 compiler_version = "0.1"
 
diff --git a/crates/nargo_cli/tests/target_tests_data/pass_dev_mode/unused/Nargo.toml b/crates/nargo_cli/tests/target_tests_data/pass_dev_mode/unused/Nargo.toml
index e0b467ce5da..f25b40c494d 100644
--- a/crates/nargo_cli/tests/target_tests_data/pass_dev_mode/unused/Nargo.toml
+++ b/crates/nargo_cli/tests/target_tests_data/pass_dev_mode/unused/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
+name = "pass_dev_mode_unused"
 authors = [""]
 compiler_version = "0.1"
 
-[dependencies]
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/1327_concrete_in_generic/Nargo.toml b/crates/nargo_cli/tests/test_data/1327_concrete_in_generic/Nargo.toml
new file mode 100644
index 00000000000..84bcfa59445
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/1327_concrete_in_generic/Nargo.toml
@@ -0,0 +1,6 @@
+[package]
+name = "1327_concrete_in_generic"
+authors = [""]
+compiler_version = "0.6.0"
+
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/1327_concrete_in_generic/Prover.toml b/crates/nargo_cli/tests/test_data/1327_concrete_in_generic/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/1327_concrete_in_generic/Prover.toml
rename to crates/nargo_cli/tests/test_data/1327_concrete_in_generic/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/1327_concrete_in_generic/src/main.nr b/crates/nargo_cli/tests/test_data/1327_concrete_in_generic/src/main.nr
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/1327_concrete_in_generic/src/main.nr
rename to crates/nargo_cli/tests/test_data/1327_concrete_in_generic/src/main.nr
diff --git a/crates/nargo_cli/tests/test_data/1327_concrete_in_generic/target/main.json b/crates/nargo_cli/tests/test_data/1327_concrete_in_generic/target/main.json
new file mode 100644
index 00000000000..d9592998976
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/1327_concrete_in_generic/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"input","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"input":[1]},"return_type":{"kind":"field"},"return_witnesses":[2]},"bytecode":"H4sIAAAAAAAA/62PwQ2AMAwDU1goaZI2+bEKFen+IyCkIlC/4I/9OtsrACR4dOdtOH4TpcGcuYxFJGoOYtoxezNF0VaMjNT0yMYcJla9eUUn4aCuzn2Al/82Ypq+v/PVcwJ2MvbyJAEAAA==","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/1327_concrete_in_generic/target/witness.tr b/crates/nargo_cli/tests/test_data/1327_concrete_in_generic/target/witness.tr
new file mode 100644
index 00000000000..454a9b75e04
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/1327_concrete_in_generic/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/1_mul/Nargo.toml b/crates/nargo_cli/tests/test_data/1_mul/Nargo.toml
index e0b467ce5da..3a08d792ed5 100644
--- a/crates/nargo_cli/tests/test_data/1_mul/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/1_mul/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
+name = "1_mul"
 authors = [""]
 compiler_version = "0.1"
 
-[dependencies]
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/1_mul/target/c.json b/crates/nargo_cli/tests/test_data/1_mul/target/c.json
new file mode 100644
index 00000000000..c1233b8160b
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/1_mul/target/c.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[],"param_witnesses":{},"return_type":null,"return_witnesses":[]},"bytecode":[155,194,56,97,194,4,0],"proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/1_mul/target/main.json b/crates/nargo_cli/tests/test_data/1_mul/target/main.json
index 08c2d3d29df..f53b31bda01 100644
--- a/crates/nargo_cli/tests/test_data/1_mul/target/main.json
+++ b/crates/nargo_cli/tests/test_data/1_mul/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"},{"name":"y","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"},{"name":"z","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"}],"param_witnesses":{"x":[1],"y":[2],"z":[3]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/9VVW67CIBQ8t49bXzGauACXwClg4c+laGPd/xIsEZQ0+sVgdJKGnoRO5zADbIloR3f8jU/hx31UF5O69HX4xuHoR5EGjjXEvFIclBq6dmDJZ9Ha3mihdH8wbFgbfWmNlINRprO97YRlJQe+aiuvnrjCaRRBH7p3p7GiJ1B6aYJEXg4v/yNHHQenngTFTTi9CQrC0CoD7zrTwpdYU7kGG4nShV4/9CarfU7RuWno+w8Yp7GhJ5A+EY73kcv5yDELISh8sY9qN+Hkf5bD0CYD74Z+44CZgY1E6frU+qX6XGbyIlXXgrAHlYPjXNLrfSjSwIEbvQ9X9N0Xlet7laFvpP8UAd0/2p8YN9ELeU32DAAA","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"},{"name":"y","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"},{"name":"z","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"}],"param_witnesses":{"x":[1],"y":[2],"z":[3]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/1_mul/target/witness.tr b/crates/nargo_cli/tests/test_data/1_mul/target/witness.tr
index f2baa77759d..e01c75d888c 100644
Binary files a/crates/nargo_cli/tests/test_data/1_mul/target/witness.tr and b/crates/nargo_cli/tests/test_data/1_mul/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/2_div/Nargo.toml b/crates/nargo_cli/tests/test_data/2_div/Nargo.toml
index e0b467ce5da..3ddfc94b016 100644
--- a/crates/nargo_cli/tests/test_data/2_div/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/2_div/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
+name = "2_div"
 authors = [""]
 compiler_version = "0.1"
 
-[dependencies]
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/2_div/target/main.json b/crates/nargo_cli/tests/test_data/2_div/target/main.json
index e31b846ca99..cea0d39c0f5 100644
--- a/crates/nargo_cli/tests/test_data/2_div/target/main.json
+++ b/crates/nargo_cli/tests/test_data/2_div/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"},{"name":"y","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"},{"name":"z","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"}],"param_witnesses":{"x":[1],"y":[2],"z":[3]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"},{"name":"y","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"},{"name":"z","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"}],"param_witnesses":{"x":[1],"y":[2],"z":[3]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/+1Yy07DMBDcOn2ktE1bKoQQHHLhbufROjd+hYj0/z+BRNjEWEVC8myUiq5U2Zaa8e7seuLNCxG90pdN2p8wY+qshbeOzNr+l5znO3szowwzNcFhSS4fBdDHaYsx8ziFE9o5PPUSOjNr1yJGonJ5LIrmlDUqV+8yq2pdyqKsj1ppVeryI9N53uhCn6q6OslKFXmjzmWVnw3YDIg1B2JZPucOn37Bhe5h84fGfSD8YeOoowlTHckwU0j+bsKKFdZFixHTAMLabZRSL6wxXZewxkCsJeGFdUm8wrpgwH2k/yesMdCvofgLjTkCxrwA+nUH5C+iCyJKePFH+uz6u3LmUzOKCzUxZ4iJvH18HhNifEFxJWnFgLsmXPFzxb3G5+iHOI2ZU3s7RfvYHQrBzCsAV9nJhpgPrb31dBul1N8qE/r9FiTDTNnvO+hb0BON+i2eGT/VBhhzAswLkj+/vRQMdTsiDr8PLHmGwt22GDsaQAi21CuvMJum3p5jbgsSINYzXYegbIEx74B5BfCn/sKfDDOF/Na7A2LtgfU3VFuF9Nn1996Z39qqQMy9IRSNe6Bxt1Vd3Ad8jljbKiSnkeOjvYX79gnryeDFrh0AAA==","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/2_div/target/witness.tr b/crates/nargo_cli/tests/test_data/2_div/target/witness.tr
index 6db1aeb74ec..575c84704ad 100644
Binary files a/crates/nargo_cli/tests/test_data/2_div/target/witness.tr and b/crates/nargo_cli/tests/test_data/2_div/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/3_add/Nargo.toml b/crates/nargo_cli/tests/test_data/3_add/Nargo.toml
index e0b467ce5da..dd2b3ff8b0e 100644
--- a/crates/nargo_cli/tests/test_data/3_add/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/3_add/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
+name = "3_add"
 authors = [""]
 compiler_version = "0.1"
 
-[dependencies]
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/3_add/target/main.json b/crates/nargo_cli/tests/test_data/3_add/target/main.json
index a28c8d6461a..ad8718ffc05 100644
--- a/crates/nargo_cli/tests/test_data/3_add/target/main.json
+++ b/crates/nargo_cli/tests/test_data/3_add/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"},{"name":"y","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"},{"name":"z","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"}],"param_witnesses":{"x":[1],"y":[2],"z":[3]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/9VWUW6DMAx1A91KgWr73B9HiEkoyd+uMjS4/xEGXbJlbNOk5aWiT0KJJfRiPzuOH4noid6xmz/h1iawxcrOnO3/9RBufXarjAPvgFwCxyVphUhe9pv9zJGHicid0BQIDQqCl8P2P/AqedZ67NuRFb/I1g6mk7obzoYNd6Z7bY1So9Gmt4PtpWWtRp46q6YgCJCPX4TOwH7ugFzA4uKHK+kn48A5uPBRubiWfrF+ZolyEevXHVA//yAsnPduj+5jnhvdxw7gOkoR9yFB3Mj8UwB0/Mj8rAcZsK8mp+0PH8eZo/DBC2c09H3KQyfyuF1xPHQ1c5ShOCV9jrtoQZbDKsLf7Ipu42UEFgSX4CLYsn7jdIEFdhsuCNthbqH+iniu1nFxDfTrhMuF/aupIzWU/8OHr7QCiFcuuTn54IUzml8EkXG4FEKdQOia0lyqFPGn8HPBGyTRHLHEEgAA","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"},{"name":"y","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"},{"name":"z","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"}],"param_witnesses":{"x":[1],"y":[2],"z":[3]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/9VX226DMAx1A/QCqHvbcz8hIUlJ3vYrQ6P//wkDLenSbNKmclxRS8gYIef4+JCYFyJ6pS/bTJcI/pTEIouLEMd3o4ng34KXy0xtgLkELpekzBbmVfGmnHJUGadwQmciyrBIjKvQ0NSKJ2mmlmdjxr4blVbvsvODs9LY4eyUU9bZj85pPTrjej/4Xnpl9Kgu1utLSHYkHmHk/N2Jsws4VQmsuQL2YuX8XWsugDVXQFxbIH9zjT82j+QZqn4k5hTvLrkvgxe/aGLLUBNl6+Q8HolxY+Zq0o4h755w4ueqe4/v0c3mtGZO86kMjNUBDw+2Seow5ajpAZPUvNCJviepmtgnKQc4fa5TxQEovBpX458iXgHWKDZPTCJuphwtPUDEDd3+DrT/EDGyAUtF3ABxtUzCQAu4IdzHViQYRdLr1D4BH4OxCigQAAA=","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/3_add/target/witness.tr b/crates/nargo_cli/tests/test_data/3_add/target/witness.tr
index fe43d762e2a..e684b165451 100644
Binary files a/crates/nargo_cli/tests/test_data/3_add/target/witness.tr and b/crates/nargo_cli/tests/test_data/3_add/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/4_sub/Nargo.toml b/crates/nargo_cli/tests/test_data/4_sub/Nargo.toml
index e0b467ce5da..481edc68308 100644
--- a/crates/nargo_cli/tests/test_data/4_sub/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/4_sub/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
+name = "4_sub"
 authors = [""]
 compiler_version = "0.1"
 
-[dependencies]
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/4_sub/target/main.json b/crates/nargo_cli/tests/test_data/4_sub/target/main.json
index 7253c269c73..0cd34dd035f 100644
--- a/crates/nargo_cli/tests/test_data/4_sub/target/main.json
+++ b/crates/nargo_cli/tests/test_data/4_sub/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"},{"name":"y","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"},{"name":"z","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"}],"param_witnesses":{"x":[1],"y":[2],"z":[3]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/9VVbQ6CMAwtA5RgvINHWPcB2z+vInHc/whC7Mwkxj8tP3gJ6ZqQ1/a9ZrsAwBXeqJZPUbwVudrkNeX53wxF8U5R84BVwWX14FwaTUKLD23iFLx2fhoCBvTBP02wNgUXxjjFUUd0NuHso52JTPH7wnyADaR424WjKY1oSGgohGYW+xRdi7U/eLlCt3I9fgldC/dZCWqpBLl6/oyGZsR/+mkesBFefClfezjG/tU7ecHt6ySoX34QVs4znaXvscwtfY91wnu0x9zdDnNL+g8FpOeX9qfEC7Jq2noVCQAA","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"},{"name":"y","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"},{"name":"z","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"}],"param_witnesses":{"x":[1],"y":[2],"z":[3]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/9VWbQ6CMAwdgwHR6Bk8wroP2P55FYnj/kcQYmfmNP6QLtEmpCshb++9Ng17xtiB3aNaHo75lNQ8q2us47cxOOYzZrktoEqwtByMCaMKoOEilZ+clcZOgwMH1tmrcloHZ9zoJz9KD0YHmK3XM4Lx7bwgHlgWVLjNgiEyT8kNXY1o8JJYC2xoGvWfNHMr1o5Oo/zk35c8FfKEhlCzIOwrgX9Q0L+H5ppQsyDk1RLO36rxZXkk76j0U3JO+XbJucHM38xEW0ATy+7JfTyygou5VJO6Arg9oxv+Urp7+h49Ladf9rROOMa/tTxuSXEzsPYJAAA=","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/4_sub/target/witness.tr b/crates/nargo_cli/tests/test_data/4_sub/target/witness.tr
index 0fd9287fece..d9f10aa2320 100644
Binary files a/crates/nargo_cli/tests/test_data/4_sub/target/witness.tr and b/crates/nargo_cli/tests/test_data/4_sub/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/5_over/Nargo.toml b/crates/nargo_cli/tests/test_data/5_over/Nargo.toml
index e0b467ce5da..8d54313a873 100644
--- a/crates/nargo_cli/tests/test_data/5_over/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/5_over/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
+name = "5_over"
 authors = [""]
 compiler_version = "0.1"
 
-[dependencies]
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/5_over/target/main.json b/crates/nargo_cli/tests/test_data/5_over/target/main.json
index e64aa14a859..a7076380486 100644
--- a/crates/nargo_cli/tests/test_data/5_over/target/main.json
+++ b/crates/nargo_cli/tests/test_data/5_over/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"},{"name":"y","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"}],"param_witnesses":{"x":[1],"y":[2]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"},{"name":"y","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"}],"param_witnesses":{"x":[1],"y":[2]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/81XUW6DMAx1E9YWqvVvn5N2hJgQSP52laGF+x9hsAY1jfrHM6ollESgZ/v5JTFXIvqgmx3mR6XxK1urtF7fHdL332k024xzTCCuocI24vI60TNGVcQMJ2QhWxeFqNKaBItQ4lrTd10c2siWf0wbRu9M58bes2fn3W/rrY2+80MYw2ACdzby5IKdEvA7yRRUY+JsU5ysgTlXwLrsxZ/ZZqyE+NuK9QbkT9OTTU/4vYiMOY/3mM2rNKonmjgK5ESFn5LHKwkeqFJFkiDqRDjxS+V9wtfo4XB6ZU4VPQoVHSvw8kB3QKv584xR0w4d0OLok+4d0OJUFz7RNxni9onTv4UzUHg1LkdxEQNj7UlIxM2McaEdRNzQvbVWyam0iGugiBugiC9CwkD/tjSE3WyU1b+0P+cFO+aEDwAA","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/5_over/target/witness.tr b/crates/nargo_cli/tests/test_data/5_over/target/witness.tr
index 1b2838a8dc4..a2d888f3003 100644
Binary files a/crates/nargo_cli/tests/test_data/5_over/target/witness.tr and b/crates/nargo_cli/tests/test_data/5_over/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/6/Nargo.toml b/crates/nargo_cli/tests/test_data/6/Nargo.toml
index e0b467ce5da..7ef042e85cf 100644
--- a/crates/nargo_cli/tests/test_data/6/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/6/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
+name = "6"
 authors = [""]
 compiler_version = "0.1"
 
-[dependencies]
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/6/target/main.json b/crates/nargo_cli/tests/test_data/6/target/main.json
index 863baece396..9e04a849f70 100644
--- a/crates/nargo_cli/tests/test_data/6/target/main.json
+++ b/crates/nargo_cli/tests/test_data/6/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"array","length":5,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"},{"name":"result","type":{"kind":"array","length":32,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"public"}],"param_witnesses":{"result":[6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37],"x":[1,2,3,4,5]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"array","length":5,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"},{"name":"result","type":{"kind":"array","length":32,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"public"}],"param_witnesses":{"result":[6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37],"x":[1,2,3,4,5]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/6/target/witness.tr b/crates/nargo_cli/tests/test_data/6/target/witness.tr
index 15a5c920495..aa89197defa 100644
Binary files a/crates/nargo_cli/tests/test_data/6/target/witness.tr and b/crates/nargo_cli/tests/test_data/6/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/6_array/Nargo.toml b/crates/nargo_cli/tests/test_data/6_array/Nargo.toml
index e0b467ce5da..ad8fc83dbd7 100644
--- a/crates/nargo_cli/tests/test_data/6_array/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/6_array/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
+name = "6_array"
 authors = [""]
 compiler_version = "0.1"
 
-[dependencies]
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/6_array/Prover.toml b/crates/nargo_cli/tests/test_data/6_array/Prover.toml
index c61cd3b3a95..2e2ed310ba1 100644
--- a/crates/nargo_cli/tests/test_data/6_array/Prover.toml
+++ b/crates/nargo_cli/tests/test_data/6_array/Prover.toml
@@ -5,5 +5,4 @@ t = "10"
 
 #7128
 #15309
-#16349
-
+#16349
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/6_array/src/main.nr b/crates/nargo_cli/tests/test_data/6_array/src/main.nr
index 9593c56524f..3b98a2b99bb 100644
--- a/crates/nargo_cli/tests/test_data/6_array/src/main.nr
+++ b/crates/nargo_cli/tests/test_data/6_array/src/main.nr
@@ -50,5 +50,9 @@ fn main(x: [u32; 5], y: [u32; 5], mut z: u32, t: u32) {
             assert(x_elem != y_elem);
         }
     }
-}
 
+    // Test 7: Arrays of tuples/structs
+    let mut tuple_array = [(1, 2), (3, 4), (5, 6)];
+    tuple_array[1] = (7, 8);
+    assert(tuple_array[1].1 == 8);
+}
diff --git a/crates/nargo_cli/tests/test_data/6_array/target/main.json b/crates/nargo_cli/tests/test_data/6_array/target/main.json
index e2b88070d57..3a434bc8f7a 100644
--- a/crates/nargo_cli/tests/test_data/6_array/target/main.json
+++ b/crates/nargo_cli/tests/test_data/6_array/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"array","length":5,"type":{"kind":"integer","sign":"unsigned","width":32}},"visibility":"private"},{"name":"y","type":{"kind":"array","length":5,"type":{"kind":"integer","sign":"unsigned","width":32}},"visibility":"private"},{"name":"z","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"},{"name":"t","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"}],"param_witnesses":{"t":[12],"x":[1,2,3,4,5],"y":[6,7,8,9,10],"z":[11]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"array","length":5,"type":{"kind":"integer","sign":"unsigned","width":32}},"visibility":"private"},{"name":"y","type":{"kind":"array","length":5,"type":{"kind":"integer","sign":"unsigned","width":32}},"visibility":"private"},{"name":"z","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"},{"name":"t","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"}],"param_witnesses":{"t":[12],"x":[1,2,3,4,5],"y":[6,7,8,9,10],"z":[11]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/6_array/target/witness.tr b/crates/nargo_cli/tests/test_data/6_array/target/witness.tr
index 04de148147a..8a348c2fcda 100644
Binary files a/crates/nargo_cli/tests/test_data/6_array/target/witness.tr and b/crates/nargo_cli/tests/test_data/6_array/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/7/Nargo.toml b/crates/nargo_cli/tests/test_data/7/Nargo.toml
index e0b467ce5da..cd5a4d21b38 100644
--- a/crates/nargo_cli/tests/test_data/7/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/7/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
+name = "7"
 authors = [""]
 compiler_version = "0.1"
 
-[dependencies]
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/7/target/main.json b/crates/nargo_cli/tests/test_data/7/target/main.json
index 4597c070150..aca74d546fd 100644
--- a/crates/nargo_cli/tests/test_data/7/target/main.json
+++ b/crates/nargo_cli/tests/test_data/7/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"array","length":5,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"},{"name":"result","type":{"kind":"array","length":32,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"}],"param_witnesses":{"result":[6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37],"x":[1,2,3,4,5]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/9Wd+7MVUhTHVzd6v9/v9/t59j333HtO7ycRERERdeteIiIiIiIiIiIiIkqTJEmSJEnGH+L/sNd09rj2D37ps2b2PjNrbmum+c76ftf63LmPc8/5W0T+kiuPVr5qqh/btehror511F8T9ddGfZuobxv17aK+fdR3iPqOUd8p6jtHfZeo7xr13aK+e9T3iPqeUd8r6ntHfZ+o7xv1/aK+f9QPiPqBUT8o6gdH/ZCoHxr1w6J+eNSPiPqRUT8q6ke36PU29B5E/r2rsPNwR+F+wt0Mq/7/Mb7G+hrna7yvCb4m+prka7KvKb6m+ir4cr5qfRV91fkq+ar31eCr7Kvia5qv6b5m+Jrpa5av2b7m+Jrra56v+b4W+Foo/320rn6cU/1YLNTX1TU11Da5oltdqK00lkuFulJjfdmVXalcWltbLhabynXlhkpjpaFQcXXFJtdcqhSbC1cebVpoFa7u4caAc13HzVWoqeqo5vUtbkBA70G7FbyfRWAOVr4XGfgm9y+G/LQFsxwLznWD8Pyo5o1G/ARt+o4WS9r8qO/FBr7J/YshP+3ALMeBc90kPD+qebMRP0GbvqMlkjY/6nuJgW9y/2LIT3swy/HgXLcIz49q3mrET9Cm72ippM2P+l5q4Jvcvxjy0wHMcgI4123C86OatxvxE7TpO1omafOjvpcZ+Cb3L4b8dASznAjOdYfw/KjmnUb8BG36jpZL2vyo7+UGvsn9iyE/ncAsJ4Fz3SU8P6p5txE/QZu+oxWSNj/qe4WBb3L/YshPZzDLyeBc9wjPj2rea8RP0KbvaKWkzY/6Xmngm9y/GPLTBcxyCjjXfcLzo5r3G/ETtOk7WiVp86O+Vxn4Jvcvhvx0BbOcCs61Wnh+VLNRbPgJ2vQdrZG0+VHfawx8k/sXQ366gVkWwLnWCs+PajYZ8RO06TtqlrT5Ud/NBr7J/YshP93BLB041wPC86OaDxrxE7TpO1onafOjvtcZ+Cb3L4b89ACzrAXnekh4flTzYSN+gjZ9R+slbX7U93oD3+T+xZCfnmCWRXCuR4TnRzUfNeInaNN3tEHS5kd9bzDwTe5fDPnpBWZZB871mPD8qObjRvwEbfqONkra/KjvjQa+yf2LIT+9wSxL4FxPCM+Paj5pxE/Qpu9ok6TNj/reZOCb3L8Y8tMHzLIenOsp4flRzaeN+Ana9B1tlrT5Ud+bDXyT+xdDfvqCWTaAcz0jPD+q+awRP0GbvqMtkjY/6nuLgW9y/2LITz8wyzI413PC86OazxvxE7TpO9oqafOjvrca+Cb3L4b89AezrIBzvSA8P6r5otjwE7TpO9omafOjvrcZ+Cb3L4b8DACznAbO9ZLw/Kjmy2LDT9Cm72i7pM2P+t5u4JvcvxjyMxDMcjo41yvC86OarxrxE7TpO9ohafOjvncY+Cb3L4b8DAKznAHO9Zrw/Kjm60b8BG36jnZK2vyo750Gvsn9iyE/g8EsZ4JzvSE8P6r5phE/QZu+o12SNj/qe5eBb3L/YsjPEDDLWeBcbwnPj2q+bcRP0KbvaLekzY/63m3gm9y/GPIzFMxyNjjXO8Lzo5rvGvETtOk72iNp86O+9xj4JvcvhvwMA7OcA871nvD8qOb7YsNP0KbvaK+kzY/63mvgm9y/GPIzHMxyLjjXB8Lzo5ofGvETtOk72idp86O+9xn4JvcvhvyMALOcB871kfD8qObHRvwEbfqO9kva/Kjv/Qa+yf2LIT8jwSzng3N9Ijw/qvmpET9Bm76jA5I2P+r7gIFvcv9iyM8oMMsF4FyfCc+Pan4uNvwEbfqODkra/Kjvgwa+yf2LIT+jwSwXgnN9ITw/qvml2PATtOk7OiRp86O+Dxn4Jvcv/8NP4eoe7hDo+TCodTST/MCvr9xBML+vM8kP/PmI2w/mdyyT/MDfb7i9YH7fZJIf+PwEtxvM73gm+YHPL3Q7wfy+zSS/baDWdjC/E5nkB/59n9sK5vddJvmBf5/vNoP5ncwkP/D1ddxGML/vM8kPfH08tx7M71Qm+a0BtZrB/H7IJD/w9endKjC/05nkB76/jFsB5vdjJvmB7w/nloH5nckkP3DP7gyY30+Z5Ad+nnanwfzOZpIf+HWWOwXm93Mm+YHfJ7mTYH7nMskP/DmHOwHm90sm+YE/p3THwfzOZ5If+HsGdwzM79dM8gPfX9sdBfO7kEl+4J7dBTC/3zLJD/w87c6D+V3MJD/w6yx3Dszv90zyA79PcmfB/C5lkh+4Z3cJzO+PTPIDP0+7i2B+lzPJbxGotRjU+jOT/EBO3GXw/sj8aqo6+vywr6r/pp/HF7Tp5/Edge/IwvcRA9+HxYYf2j+9n5aPfwC0Rez2lJQAAA==","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"array","length":5,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"},{"name":"result","type":{"kind":"array","length":32,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"}],"param_witnesses":{"result":[6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37],"x":[1,2,3,4,5]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/7/target/witness.tr b/crates/nargo_cli/tests/test_data/7/target/witness.tr
index 6c66e689246..2abb65d513e 100644
Binary files a/crates/nargo_cli/tests/test_data/7/target/witness.tr and b/crates/nargo_cli/tests/test_data/7/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/7_function/Nargo.toml b/crates/nargo_cli/tests/test_data/7_function/Nargo.toml
index e0b467ce5da..42672a980c8 100644
--- a/crates/nargo_cli/tests/test_data/7_function/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/7_function/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
+name = "7_function"
 authors = [""]
 compiler_version = "0.1"
 
-[dependencies]
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/7_function/src/main.nr b/crates/nargo_cli/tests/test_data/7_function/src/main.nr
index 5a23b493871..26ecf6dda28 100644
--- a/crates/nargo_cli/tests/test_data/7_function/src/main.nr
+++ b/crates/nargo_cli/tests/test_data/7_function/src/main.nr
@@ -88,12 +88,15 @@ fn test_multiple6(a: my2, b: my_struct, c: (my2, my_struct)) {
 }
 
 
-fn foo(a: [Field]) -> [Field] {
+
+fn foo<N>(a: [Field; N]) -> [Field; N] {
     a
 }
-fn bar() -> [Field] {
+
+fn bar() -> [Field; 1] {
     foo([0])
 }
+
 fn main(x: u32 , y: u32 , a: Field, arr1: [u32; 9], arr2: [u32; 9]) {  
     let mut ss: my_struct = my_struct { b: x, a: x+2, };
     test_multiple4(ss);
@@ -134,7 +137,6 @@ fn main(x: u32 , y: u32 , a: Field, arr1: [u32; 9], arr2: [u32; 9]) {
     assert(result[0] == arr1[0] as Field);
 }
 
-
 // Issue #628
 fn arr_to_field(arr: [u32; 9]) -> [Field; 9] {
     let mut as_field: [Field; 9] = [0 as Field; 9];
diff --git a/crates/nargo_cli/tests/test_data/7_function/target/main.json b/crates/nargo_cli/tests/test_data/7_function/target/main.json
index db6c80e3f4d..66db45e2d85 100644
--- a/crates/nargo_cli/tests/test_data/7_function/target/main.json
+++ b/crates/nargo_cli/tests/test_data/7_function/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"},{"name":"y","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"},{"name":"a","type":{"kind":"field"},"visibility":"private"},{"name":"arr1","type":{"kind":"array","length":9,"type":{"kind":"integer","sign":"unsigned","width":32}},"visibility":"private"},{"name":"arr2","type":{"kind":"array","length":9,"type":{"kind":"integer","sign":"unsigned","width":32}},"visibility":"private"}],"param_witnesses":{"a":[3],"arr1":[4,5,6,7,8,9,10,11,12],"arr2":[13,14,15,16,17,18,19,20,21],"x":[1],"y":[2]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"},{"name":"y","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"},{"name":"a","type":{"kind":"field"},"visibility":"private"},{"name":"arr1","type":{"kind":"array","length":9,"type":{"kind":"integer","sign":"unsigned","width":32}},"visibility":"private"},{"name":"arr2","type":{"kind":"array","length":9,"type":{"kind":"integer","sign":"unsigned","width":32}},"visibility":"private"}],"param_witnesses":{"a":[3],"arr1":[4,5,6,7,8,9,10,11,12],"arr2":[13,14,15,16,17,18,19,20,21],"x":[1],"y":[2]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/7_function/target/witness.tr b/crates/nargo_cli/tests/test_data/7_function/target/witness.tr
index 32202c60183..809861d3d97 100644
Binary files a/crates/nargo_cli/tests/test_data/7_function/target/witness.tr and b/crates/nargo_cli/tests/test_data/7_function/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/8_integration/Nargo.toml b/crates/nargo_cli/tests/test_data/8_integration/Nargo.toml
index e0b467ce5da..ca21221bc78 100644
--- a/crates/nargo_cli/tests/test_data/8_integration/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/8_integration/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
+name = "8_integration"
 authors = [""]
 compiler_version = "0.1"
 
-[dependencies]
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/8_integration/target/main.json b/crates/nargo_cli/tests/test_data/8_integration/target/main.json
index b24a5cf2325..2bb782d8cdf 100644
--- a/crates/nargo_cli/tests/test_data/8_integration/target/main.json
+++ b/crates/nargo_cli/tests/test_data/8_integration/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"a","type":{"kind":"array","length":100,"type":{"kind":"integer","sign":"unsigned","width":32}},"visibility":"private"},{"name":"b","type":{"kind":"array","length":100,"type":{"kind":"integer","sign":"unsigned","width":32}},"visibility":"private"},{"name":"c","type":{"kind":"array","length":4,"type":{"kind":"integer","sign":"unsigned","width":32}},"visibility":"private"},{"name":"d","type":{"kind":"array","length":4,"type":{"kind":"integer","sign":"unsigned","width":32}},"visibility":"private"},{"name":"m","type":{"kind":"array","length":32,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"}],"param_witnesses":{"a":[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100],"b":[101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200],"c":[201,202,203,204],"d":[205,206,207,208],"m":[209,210,211,212,213,214,215,216,217,218,219,220,221,222,223,224,225,226,227,228,229,230,231,232,233,234,235,236,237,238,239,240]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"a","type":{"kind":"array","length":100,"type":{"kind":"integer","sign":"unsigned","width":32}},"visibility":"private"},{"name":"b","type":{"kind":"array","length":100,"type":{"kind":"integer","sign":"unsigned","width":32}},"visibility":"private"},{"name":"c","type":{"kind":"array","length":4,"type":{"kind":"integer","sign":"unsigned","width":32}},"visibility":"private"},{"name":"d","type":{"kind":"array","length":4,"type":{"kind":"integer","sign":"unsigned","width":32}},"visibility":"private"},{"name":"m","type":{"kind":"array","length":32,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"}],"param_witnesses":{"a":[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100],"b":[101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200],"c":[201,202,203,204],"d":[205,206,207,208],"m":[209,210,211,212,213,214,215,216,217,218,219,220,221,222,223,224,225,226,227,228,229,230,231,232,233,234,235,236,237,238,239,240]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/8_integration/target/witness.tr b/crates/nargo_cli/tests/test_data/8_integration/target/witness.tr
index b00e525e407..e73ec20bbf1 100644
Binary files a/crates/nargo_cli/tests/test_data/8_integration/target/witness.tr and b/crates/nargo_cli/tests/test_data/8_integration/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/9_conditional/Nargo.toml b/crates/nargo_cli/tests/test_data/9_conditional/Nargo.toml
index e0b467ce5da..7c447ce2f0a 100644
--- a/crates/nargo_cli/tests/test_data/9_conditional/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/9_conditional/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
+name = "9_conditional"
 authors = [""]
 compiler_version = "0.1"
 
-[dependencies]
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/9_conditional/target/main.json b/crates/nargo_cli/tests/test_data/9_conditional/target/main.json
index 93ea7a3ee10..3e84a4c6846 100644
--- a/crates/nargo_cli/tests/test_data/9_conditional/target/main.json
+++ b/crates/nargo_cli/tests/test_data/9_conditional/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"a","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"},{"name":"c","type":{"kind":"array","length":4,"type":{"kind":"integer","sign":"unsigned","width":32}},"visibility":"private"},{"name":"x","type":{"kind":"array","length":5,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"},{"name":"result","type":{"kind":"array","length":32,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"public"}],"param_witnesses":{"a":[1],"c":[2,3,4,5],"result":[11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42],"x":[6,7,8,9,10]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/9_conditional/target/witness.tr b/crates/nargo_cli/tests/test_data/9_conditional/target/witness.tr
index ddb15d90d52..0afa3de90ef 100644
Binary files a/crates/nargo_cli/tests/test_data/9_conditional/target/witness.tr and b/crates/nargo_cli/tests/test_data/9_conditional/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/README.md b/crates/nargo_cli/tests/test_data/README.md
deleted file mode 100644
index 712298a85ff..00000000000
--- a/crates/nargo_cli/tests/test_data/README.md
+++ /dev/null
@@ -1,16 +0,0 @@
-# Noir Test Programs
-
-A suite of Noir programs that have been pre-compiled to ACIR bytecode and witness data. These can be fed into simulators and backends to ensure they produce expected proofs.
-
-The witness data is output in "flat" format, which at the time of writing requires nargo to be compiled with the "flat_witness" feature flag enabled.
-
-```
-nix develop # (hopefully soon optional)
-cargo install --path=crates/nargo_cli --no-default-features --features=flat_witness
-```
-
-Then to recompile:
-
-```
-./rebuild.sh
-```
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/ecdsa_secp256k1/Nargo.toml b/crates/nargo_cli/tests/test_data/arithmetic_binary_operations/Nargo.toml
similarity index 63%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/ecdsa_secp256k1/Nargo.toml
rename to crates/nargo_cli/tests/test_data/arithmetic_binary_operations/Nargo.toml
index 7199d3305bf..4fde96957fc 100644
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/ecdsa_secp256k1/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/arithmetic_binary_operations/Nargo.toml
@@ -1,5 +1,5 @@
 [package]
-name = "ECDSA secp256k1 verification"
+name = "arithmetic_binary_operations"
 authors = [""]
 compiler_version = "0.1"
 
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/arithmetic_binary_operations/Prover.toml b/crates/nargo_cli/tests/test_data/arithmetic_binary_operations/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/arithmetic_binary_operations/Prover.toml
rename to crates/nargo_cli/tests/test_data/arithmetic_binary_operations/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/arithmetic_binary_operations/src/main.nr b/crates/nargo_cli/tests/test_data/arithmetic_binary_operations/src/main.nr
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/arithmetic_binary_operations/src/main.nr
rename to crates/nargo_cli/tests/test_data/arithmetic_binary_operations/src/main.nr
diff --git a/crates/nargo_cli/tests/test_data/arithmetic_binary_operations/target/main.json b/crates/nargo_cli/tests/test_data/arithmetic_binary_operations/target/main.json
new file mode 100644
index 00000000000..6ad87420432
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/arithmetic_binary_operations/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"y","type":{"kind":"field"},"visibility":"private"},{"name":"z","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"x":[1],"y":[2],"z":[3]},"return_type":{"kind":"field"},"return_witnesses":[10]},"bytecode":"H4sIAAAAAAAA/9WVSQ7DIAxFnTRjK/UsNkNidr1Ko5L7H6FCIhJK2YGl1BsjFvb/fkY8AGCC37jF/IoZy0I1SS2NizF+VZ40vVG5jS0auy1MTJbtR7HWng2vbnMrOjLa026d3mOxtmKtrp5HDDNrMrNsBGeJhZHq7ZNzF3Ob2YmhvieCU5/zHJ+ZO5HmrSCs0mUd6ulCEIDYx+U48yn1LaE1LFmXqVuqdfwDRqOA76my7yOu/B7ni7MOTGYB1neo+2ke3gPrW8L+0B36fQEsj335qQgAAA==","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/arithmetic_binary_operations/target/witness.tr b/crates/nargo_cli/tests/test_data/arithmetic_binary_operations/target/witness.tr
new file mode 100644
index 00000000000..1d167a816d6
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/arithmetic_binary_operations/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/array_dynamic/Nargo.toml b/crates/nargo_cli/tests/test_data/array_dynamic/Nargo.toml
index e0b467ce5da..c5e05dfc6d7 100644
--- a/crates/nargo_cli/tests/test_data/array_dynamic/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/array_dynamic/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
+name = "array_dynamic"
 authors = [""]
 compiler_version = "0.1"
 
-[dependencies]
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/array_dynamic/src/main.nr b/crates/nargo_cli/tests/test_data/array_dynamic/src/main.nr
index 69e5fdc93db..b27c96b30c3 100644
--- a/crates/nargo_cli/tests/test_data/array_dynamic/src/main.nr
+++ b/crates/nargo_cli/tests/test_data/array_dynamic/src/main.nr
@@ -21,7 +21,7 @@ fn dyn_array(mut x: [u32; 5], y: Field, z: Field) {
     assert(x[y] == 111);
     assert(x[z] == 101);
     x[z] = 0;
-    assert(x[y] == 111);
+   assert(x[y] == 111);
     assert(x[1] == 0);
     if y as u32 < 10 {
       x[y] = x[y] - 2;
diff --git a/crates/nargo_cli/tests/test_data/array_dynamic/target/main.json b/crates/nargo_cli/tests/test_data/array_dynamic/target/main.json
index 67e93a20e5d..e632943a2ee 100644
--- a/crates/nargo_cli/tests/test_data/array_dynamic/target/main.json
+++ b/crates/nargo_cli/tests/test_data/array_dynamic/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"array","length":5,"type":{"kind":"integer","sign":"unsigned","width":32}},"visibility":"private"},{"name":"z","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"},{"name":"t","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"},{"name":"index","type":{"kind":"array","length":5,"type":{"kind":"field"}},"visibility":"private"},{"name":"index2","type":{"kind":"array","length":5,"type":{"kind":"field"}},"visibility":"private"},{"name":"offset","type":{"kind":"field"},"visibility":"private"},{"name":"sublen","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"index":[8,9,10,11,12],"index2":[13,14,15,16,17],"offset":[18],"sublen":[19],"t":[7],"x":[1,2,3,4,5],"z":[6]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/+1ca3PTRhQ9cV4lMNMONQkUKKZQgkOgWkt2pIYATV/0BYXSQt9gYtMPncKH9u/2t+BNtEZobJiJzsloZ7kzHntnPFfncXevtLL8H4Bn2IuZ0auRv7cK40ZpPFsaz5XG86XxQmm8mI/dsVw08vcb+XtULcxCIVcc9ZJksNEZmNg8ijpZP+1GSbffS01quml3p5PG8SBN0o2sn21EmUnigRl2s3gw3I3Hi9VxdfdSDfsoRcW8xn04NsrRLBrZnCL0DFnoY7xcEVkcF8nKKMdyUZxlvKg4tiD2YCsT8u63Cod54hWR0LNknMSCMMvkIvBBvwUezu4iL5fZqcwx3ck59l6lX1QtTBPcVZXl6w409cfunMeJnE+A1YWzjuNpc76Xf2av3S43e+0+Ca73Ct4nBbxPQFPzbP5sf1yw5+YpojenQZubjx1Pm/N9kUcuN7tGz6Dec9PyPiPgfRp+zE22Py7Yc7NF9OYs+H3T5vxA5JHLza7Rc6j33LS8zwl4n4Ufc5Ppj6vT86PXhyK8Ljfbrwuod51a3hcEvM/Djzpl++NCee26T286uTdmlejzRQLHfAe0p96QbBKxohQV8473Faw3Fx35Rj5oiQSxB1sFf/Kvgrv4K4uixSuKAURFsTbK0S4WRVtYFPZga4KiWMPBrLRVcbaIWrbJRVCRo+sAcVE/9tXOZaIXVwi58qudxPG0OT+CZu643Oy5E4E7dxS8IwHvK9CsGWz+bH9csM8iu0RvesRcQ0/0i4m5EqJ+TzzRzxBzdYi5/vJEP+I8MU+I9cfUz/Vpu75s5J/Z67XLze5XKerdpy3vVMC7h4Pp0zXyx6gvTN8VaUrAOL4m+XiUI3PkG/mgVRjbL/xfOjj7go0olMnI4pBwyXdBMtS/2K6OcmwWi22zVGxXD6DYiEKZTbI4JFzS3ZXN6rnG+9hbRFzXeF7Er5usTA2j/cUYK0pByhtZb6458o180JoiSFQtdgthSyD0FvyYVO8QtbxOxHUD3A7oNPtEVEcuN7uOtsl1pOC9LeDN9B/QzO9tgZ5svzGl3qvy/9QTnJ8RvVHi/JyHs6PE+QUPZ6zE+SUPZ6LAdxR75x3sbb6jBIz5I2oD5knyTWLdzOV+2McCFzA5WHpOq8+oWhjF+snG+JYAoy/+EPuGzJ9DCNcfYr+U+bOEcP0hnifI/DmMcP0hnh/J/DmC2vsj437TA4zXofGHfa79lSc4vwZ/3VDg/IaHU3qt+i0Pp/Ra9TsezqSIs1HCGVULxoMEY863CLkGE347XWfOt0Wc2fX4PfxYL++Au16y8dnaUTwj8bfInxo+eDTmfJeIK0T9fqixfopniNqCvP+IeUfVYveZrEsC3k/hx3xpEznfI+J65ol+xPo2T4lesPVTPByq6PM/Bsr7J9S/v6wL8v4LP9aJdSLn+0RcKv3YPj/g4Uzmc3/t+9uYHCx9p+kRVQuj2J9jY5yBprZ88Ie4Lynzp4Fw/SHux8r8mUW4/hD3oWX+zCFcf4j77zJ/5lF7f2Tcm6g/xuMI159bHmA8hXDXt9se+KO65wS8Wd8YGFsI1587HmBU/WmiD/7c9QDjJYTbf4j3HmX+3EO484d9n0GBcR3hzh/2/RAFxvsId/488ADjZWj8Yd8b+dkTnL/QcL78h8BsnL+Cv74pcP5Gw5kNlTh/5+kp/e3zHzScHek8+pOnp/Q32g9pOPtSPR/x9EyUOPs8nKm9dzGfv5YwOUjHkp3jKfoeGyOv5/l3Dk7sozJ/eD3UP3+IfVnmD68n++cPsc/L/HmIcP0hnjfI/Omj9v549V8cbIwG4fpzyAOMHYTrz5IHGGOE689hDzAmCNefIx5g7ELnz3P9sBSg14QAAA==","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"array","length":5,"type":{"kind":"integer","sign":"unsigned","width":32}},"visibility":"private"},{"name":"z","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"},{"name":"t","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"},{"name":"index","type":{"kind":"array","length":5,"type":{"kind":"field"}},"visibility":"private"},{"name":"index2","type":{"kind":"array","length":5,"type":{"kind":"field"}},"visibility":"private"},{"name":"offset","type":{"kind":"field"},"visibility":"private"},{"name":"sublen","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"index":[8,9,10,11,12],"index2":[13,14,15,16,17],"offset":[18],"sublen":[19],"t":[7],"x":[1,2,3,4,5],"z":[6]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/array_dynamic/target/witness.tr b/crates/nargo_cli/tests/test_data/array_dynamic/target/witness.tr
index 35ea28c6d84..44f38a81561 100644
Binary files a/crates/nargo_cli/tests/test_data/array_dynamic/target/witness.tr and b/crates/nargo_cli/tests/test_data/array_dynamic/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/array_len/Nargo.toml b/crates/nargo_cli/tests/test_data/array_len/Nargo.toml
index e0b467ce5da..9e417be06ee 100644
--- a/crates/nargo_cli/tests/test_data/array_len/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/array_len/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
+name = "array_len"
 authors = [""]
 compiler_version = "0.1"
 
-[dependencies]
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/array_len/Prover.toml b/crates/nargo_cli/tests/test_data/array_len/Prover.toml
index 3c3295e6848..a5ffe607b73 100644
--- a/crates/nargo_cli/tests/test_data/array_len/Prover.toml
+++ b/crates/nargo_cli/tests/test_data/array_len/Prover.toml
@@ -1,2 +1,3 @@
 len3 = [1, 2, 3]
 len4 = [1, 2, 3, 4]
+x = 123
diff --git a/crates/nargo_cli/tests/test_data/array_len/src/main.nr b/crates/nargo_cli/tests/test_data/array_len/src/main.nr
index 9099cfa2144..65c2295cefb 100644
--- a/crates/nargo_cli/tests/test_data/array_len/src/main.nr
+++ b/crates/nargo_cli/tests/test_data/array_len/src/main.nr
@@ -1,18 +1,18 @@
 use dep::std;
 
-fn len_plus_1<T>(array: [T]) -> Field {
+fn len_plus_1<T, N>(array: [T; N]) -> Field {
     array.len() + 1
 }
 
-fn add_lens<T>(a: [T], b: [Field]) -> Field {
+fn add_lens<T, N, M>(a: [T; N], b: [Field; M]) -> Field {
     a.len() + b.len()
 }
 
-fn nested_call(b: [Field]) -> Field {
+fn nested_call<N>(b: [Field; N]) -> Field {
     len_plus_1(b)
 }
 
-fn main(len3: [u8; 3], len4: [Field; 4]) {
+fn main(x: Field, len3: [u8; 3], len4: [Field; 4]) {
     assert(len_plus_1(len3) == 4);
     assert(len_plus_1(len4) == 5);
     assert(add_lens(len3, len4) == 7);
@@ -20,4 +20,9 @@ fn main(len3: [u8; 3], len4: [Field; 4]) {
 
     // std::array::len returns a comptime value
     assert(len4[len3.len()] == 4);
+
+    // Regression for #1023, ensure .len still works after calling to_le_bytes on a witness.
+    // This was needed because normally .len is evaluated before acir-gen where to_le_bytes
+    // on a witness is only evaluated during/after acir-gen.
+    assert(x.to_le_bytes(8).len() != 0);
 }
diff --git a/crates/nargo_cli/tests/test_data/array_len/target/main.json b/crates/nargo_cli/tests/test_data/array_len/target/main.json
index edaf53ec61f..cfa010d9788 100644
--- a/crates/nargo_cli/tests/test_data/array_len/target/main.json
+++ b/crates/nargo_cli/tests/test_data/array_len/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"len3","type":{"kind":"array","length":3,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"},{"name":"len4","type":{"kind":"array","length":4,"type":{"kind":"field"}},"visibility":"private"}],"param_witnesses":{"len3":[1,2,3],"len4":[4,5,6,7]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/7WRQQ4DIQhFrV3UTi8DoiPuepWa0fsfoe2MJmS2gz8hPyx44cPLGOPModuvbHcnenvq72JmyHZ/d4drwodgEawh1OQrEn7A58IRQiwrI2PkuHkmqhw45ZITZAxUscVMrcOcAqu2XdvI+Wc+xd00sw/2mXv1DovejjAr9zIht1PObSb9Xfs/Ul8ul/wL6AMAAA==","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"len3","type":{"kind":"array","length":3,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"},{"name":"len4","type":{"kind":"array","length":4,"type":{"kind":"field"}},"visibility":"private"}],"param_witnesses":{"len3":[1,2,3],"len4":[4,5,6,7]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/81U2w7CIAxlY+5m4re0A7by5q+4DP7/E9y0JpUYX4TEk5BSSE+v6VkpNaonqv3ULHuh14muWT+xnU7sNf8desN/Db+1++nUO2qWV5bwG7ATXAZma8MyBTR4g8mv5MC6dSYkdOS2iYwJZGnxq1/AozUBo/MmMlmfgSvEBzbNNUlRZc6/z8cFMt5B3Jukd3IO2gI5qcRPWsfLh7eszks0aSjAO6p8w18q7zF/j0BQ/nVNOxHja1l+W44H7lYCBc+lBQAA","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/array_len/target/witness.tr b/crates/nargo_cli/tests/test_data/array_len/target/witness.tr
index 4afd0d4406e..c98090370a3 100644
Binary files a/crates/nargo_cli/tests/test_data/array_len/target/witness.tr and b/crates/nargo_cli/tests/test_data/array_len/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/array_neq/Nargo.toml b/crates/nargo_cli/tests/test_data/array_neq/Nargo.toml
index e0b467ce5da..a697bd06f0d 100644
--- a/crates/nargo_cli/tests/test_data/array_neq/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/array_neq/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
+name = "array_neq"
 authors = [""]
 compiler_version = "0.1"
 
-[dependencies]
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/array_neq/target/main.json b/crates/nargo_cli/tests/test_data/array_neq/target/main.json
index 6b218cee436..67c2223df62 100644
--- a/crates/nargo_cli/tests/test_data/array_neq/target/main.json
+++ b/crates/nargo_cli/tests/test_data/array_neq/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"a","type":{"kind":"array","length":32,"type":{"kind":"field"}},"visibility":"private"},{"name":"b","type":{"kind":"array","length":32,"type":{"kind":"field"}},"visibility":"private"}],"param_witnesses":{"a":[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32],"b":[33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"a","type":{"kind":"array","length":32,"type":{"kind":"field"}},"visibility":"private"},{"name":"b","type":{"kind":"array","length":32,"type":{"kind":"field"}},"visibility":"private"}],"param_witnesses":{"a":[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32],"b":[33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/array_neq/target/witness.tr b/crates/nargo_cli/tests/test_data/array_neq/target/witness.tr
index b6e6f0d2193..591e397db8d 100644
Binary files a/crates/nargo_cli/tests/test_data/array_neq/target/witness.tr and b/crates/nargo_cli/tests/test_data/array_neq/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/array_sort/Nargo.toml b/crates/nargo_cli/tests/test_data/array_sort/Nargo.toml
index 670888e37cd..7adf0793369 100644
--- a/crates/nargo_cli/tests/test_data/array_sort/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/array_sort/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
+name = "array_sort"
 authors = [""]
 compiler_version = "0.6.0"
 
-[dependencies]
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/array_sort/target/main.json b/crates/nargo_cli/tests/test_data/array_sort/target/main.json
index 67fd91f9699..22dc7dc63eb 100644
--- a/crates/nargo_cli/tests/test_data/array_sort/target/main.json
+++ b/crates/nargo_cli/tests/test_data/array_sort/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"xs","type":{"kind":"array","length":3,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"}],"param_witnesses":{"xs":[1,2,3]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"xs","type":{"kind":"array","length":3,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"}],"param_witnesses":{"xs":[1,2,3]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/array_sort/target/witness.tr b/crates/nargo_cli/tests/test_data/array_sort/target/witness.tr
index cbf1b7b662d..e886e599a5a 100644
Binary files a/crates/nargo_cli/tests/test_data/array_sort/target/witness.tr and b/crates/nargo_cli/tests/test_data/array_sort/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/assert/Nargo.toml b/crates/nargo_cli/tests/test_data/assert/Nargo.toml
index e0b467ce5da..238d13b2fd0 100644
--- a/crates/nargo_cli/tests/test_data/assert/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/assert/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
+name = "assert"
 authors = [""]
 compiler_version = "0.1"
 
-[dependencies]
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/assert/target/main.json b/crates/nargo_cli/tests/test_data/assert/target/main.json
index f0096b54230..2185644bd18 100644
--- a/crates/nargo_cli/tests/test_data/assert/target/main.json
+++ b/crates/nargo_cli/tests/test_data/assert/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"x":[1]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/7WRQQ6FMAhEsV/vAwUs7P5VbKz3P4KbmhhdSmcDq5d5mQUAFngn9fvvF7+FphuLcRVpJTdi2jB7NUXRuhoZqemejbmZWPHqBZ2EGx3qfHRYCmZdvr/+T8HuF/vJ/dp9juuIo7znAd4p2BsG7R69zz0nK7QH/7gDAAA=","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"x":[1]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/82SMQ7DIAxFTSAdexYbQzBbr1JUcv8jtAODRbPVSP2LEUjP/v7sALDDt7ZRH6PibyKnWIxHSr3ETkxPjLVJxpTbISSUJb+iMHdJUmqrBSsl7nTmyueAbYYs/2G4C//O2P9mx0I9r1fnMGWn328LPMHUZ97j/eLOtPmKkPwCbgC7D7vKd7DPCBXyr3fqphm13hKQ6RMhBQAA","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/assert/target/witness.tr b/crates/nargo_cli/tests/test_data/assert/target/witness.tr
index ab7b16733b0..87be1158f1b 100644
Binary files a/crates/nargo_cli/tests/test_data/assert/target/witness.tr and b/crates/nargo_cli/tests/test_data/assert/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/assert_statement/Nargo.toml b/crates/nargo_cli/tests/test_data/assert_statement/Nargo.toml
new file mode 100644
index 00000000000..6910160df8a
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/assert_statement/Nargo.toml
@@ -0,0 +1,6 @@
+[package]
+name = "assert_statement"
+authors = [""]
+compiler_version = "0.1"
+
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/assert_statement/Prover.toml b/crates/nargo_cli/tests/test_data/assert_statement/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/assert_statement/Prover.toml
rename to crates/nargo_cli/tests/test_data/assert_statement/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/assert_statement/src/main.nr b/crates/nargo_cli/tests/test_data/assert_statement/src/main.nr
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/assert_statement/src/main.nr
rename to crates/nargo_cli/tests/test_data/assert_statement/src/main.nr
diff --git a/crates/nargo_cli/tests/test_data/assert_statement/target/main.json b/crates/nargo_cli/tests/test_data/assert_statement/target/main.json
new file mode 100644
index 00000000000..1a9ccc17efe
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/assert_statement/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"y","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"x":[1],"y":[2]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/81TMQ7DIAw0JGTsW2wMwWz9SlHJ/59QqaISStlipNxixHC+O9sbADj4x9Lqs1W8BjIdF+MeQk2+EtMLfS4SMcSyCwlFiW8vzFWCpFxywkyBKx0x89HIrCLXoufxy2UGWRrlLDU193rXwdsOdmKb4AlOfc45PgZ/qs1nDGmdwOtAb/ln+Xb6M8KO8taZ2k5jfzw/fADLYG+4cQUAAA==","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/assert_statement/target/witness.tr b/crates/nargo_cli/tests/test_data/assert_statement/target/witness.tr
new file mode 100644
index 00000000000..05fde3ae664
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/assert_statement/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/assign_ex/Nargo.toml b/crates/nargo_cli/tests/test_data/assign_ex/Nargo.toml
index d9434868157..626db95708d 100644
--- a/crates/nargo_cli/tests/test_data/assign_ex/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/assign_ex/Nargo.toml
@@ -1,7 +1,6 @@
+[package]
+name = "assign_ex"
+authors = [""]
+compiler_version = "0.1"
 
-        [package]
-        authors = [""]
-        compiler_version = "0.1"
-    
-        [dependencies]
-    
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/assign_ex/target/main.json b/crates/nargo_cli/tests/test_data/assign_ex/target/main.json
index 5b562609a35..9955f3ec8d6 100644
--- a/crates/nargo_cli/tests/test_data/assign_ex/target/main.json
+++ b/crates/nargo_cli/tests/test_data/assign_ex/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"y","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"x":[1],"y":[2]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/82TTQ4CIQyFO4Ojo6dp+RnKzqtIhPsfwWAgIbqkJPM2ZfWF1y+9A8AD/qPqfNaJY6FFkLV2LIOHtcnrRIZeqENkh9bFg4nJsXtrNiaxZR9i8BjImkTZBZMrTAmwUv4mrd3uLvW9CO+xsX+5o3vY5P6Is3pvE3or4d4wyfvZ/RTeOsHPFcTuM7f7LMzbJE+NLb2HHc7tv/TeJ/vHwUAX6f7Sfvp8AJYlbxukBwAA","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"y","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"x":[1],"y":[2]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/+2UwQ7CIAyGO7bh9OCztAO2cvNVXIT3fwQzgwmZ3FaMiesFwuGj/dv+ZwC4wGe06bylE/cFNYIslbEMTtaGeQxk6I6jX9ihdcvExOTYPUY2JrDl2S9+Rk/WBIrOm5hgrQArxFeEldUUtGyEtWzlWJjn2xXuqjATukJNsPlnq+O18Cb6eY0mdRW4PcgNf626e/keYYb8O01Xnipw9+aqQcz84rfMT0Md8ztl98P8djJ1ElSaO8BvL+pa9yDfo6rmJ6mpynLMl+cdT6hUcv5uCgAA","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/assign_ex/target/witness.tr b/crates/nargo_cli/tests/test_data/assign_ex/target/witness.tr
index 85a46677eba..61d1e648a1c 100644
Binary files a/crates/nargo_cli/tests/test_data/assign_ex/target/witness.tr and b/crates/nargo_cli/tests/test_data/assign_ex/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/bit_and/Nargo.toml b/crates/nargo_cli/tests/test_data/bit_and/Nargo.toml
index e0b467ce5da..85fa0fe68bf 100644
--- a/crates/nargo_cli/tests/test_data/bit_and/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/bit_and/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
+name = "bit_and"
 authors = [""]
 compiler_version = "0.1"
 
-[dependencies]
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/bit_and/target/main.json b/crates/nargo_cli/tests/test_data/bit_and/target/main.json
index 96fe1a07f50..ff2a2efd56c 100644
--- a/crates/nargo_cli/tests/test_data/bit_and/target/main.json
+++ b/crates/nargo_cli/tests/test_data/bit_and/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"y","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"x":[1],"y":[2]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"y","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"x":[1],"y":[2]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/bit_and/target/witness.tr b/crates/nargo_cli/tests/test_data/bit_and/target/witness.tr
index df4e5986faf..577b19650f8 100644
Binary files a/crates/nargo_cli/tests/test_data/bit_and/target/witness.tr and b/crates/nargo_cli/tests/test_data/bit_and/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/bit_shifts_comptime/Nargo.toml b/crates/nargo_cli/tests/test_data/bit_shifts_comptime/Nargo.toml
index e0b467ce5da..ee49e18e2fa 100644
--- a/crates/nargo_cli/tests/test_data/bit_shifts_comptime/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/bit_shifts_comptime/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
+name = "bit_shifts_comptime"
 authors = [""]
 compiler_version = "0.1"
 
-[dependencies]
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/bit_shifts_comptime/target/main.json b/crates/nargo_cli/tests/test_data/bit_shifts_comptime/target/main.json
index 7e77b917355..31861cc70c0 100644
--- a/crates/nargo_cli/tests/test_data/bit_shifts_comptime/target/main.json
+++ b/crates/nargo_cli/tests/test_data/bit_shifts_comptime/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"integer","sign":"unsigned","width":64},"visibility":"private"}],"param_witnesses":{"x":[1]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/9VVWw6DIBDcYlv7+utFWIEKf71KTfH+R6hEMNT0qw6JTmIkkgzM7K5zI6I7jdgNj4jvZ7ambJ/iXoBchmaH45I0w5+8PP9QRR8mc0RGDjaEw2HVD14lH1r7tvGs+CUb11kjtekeli0ba96NVcpbbVvXuVY61spzb5zqMxGgO34ZXYHu6fsRwIZgAW6CEv4JcP8IYM/sYXW1nHQGzgOVmZ3EjZ6dI2FrX0L3sYDuPZXpebR+ZH0KBx6vMPDm0PXAcZr5ADdBxEOS4eFdZ2ckVAULsDCs3jXhhu1E2wgYpOYzrhZTwATOS1yjhzdxo3+0V1p3wATd1wK6z7SNgEHXJ8cHOTRCf34NAAA=","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"integer","sign":"unsigned","width":64},"visibility":"private"}],"param_witnesses":{"x":[1]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/+1VUW6DMAw1hFJYp/3sIjFJSvIz7SpDDfc/whqVqKnVr2JXVOqTEIFIz/Gz4/cJAN9wQXV+6uX9W6yh2IdlL0Gvw1DxcWkgeJAX6Y+kgSI6cIqAWfQsdv5WRYwMJVgAo4/WxnGIaPBPD2HyTls3HT16dN6dBm9M9NaPYQqjDtqaiLMLZl7yqB/nQsKlFcg0Rs1cO8WYc8PAFecEj3cbFtgvMDZ8XLo8765YN6R2CfketAI5AYlDdfwCwWEgVaSdAG8LfM0vlXfLX6ObgbJlTYXdGzfo3hR2f+bo4AnunQL9wNW9O7idWAlKIPbaZrk4xnzaMzZeB6/h3pw593y1eJp79yDj3h/F+u3eKzn7RVBu3gNs271T3gf+Gom6N6emFTljiX/W0KRotA8AAA==","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/bit_shifts_comptime/target/witness.tr b/crates/nargo_cli/tests/test_data/bit_shifts_comptime/target/witness.tr
index ce4e9ff16c3..343cc4642c5 100644
Binary files a/crates/nargo_cli/tests/test_data/bit_shifts_comptime/target/witness.tr and b/crates/nargo_cli/tests/test_data/bit_shifts_comptime/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/bit_shifts_runtime/Nargo.toml b/crates/nargo_cli/tests/test_data/bit_shifts_runtime/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data/bit_shifts_runtime/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/bit_shifts_runtime/Prover.toml b/crates/nargo_cli/tests/test_data/bit_shifts_runtime/Prover.toml
deleted file mode 100644
index 67bf6a6a234..00000000000
--- a/crates/nargo_cli/tests/test_data/bit_shifts_runtime/Prover.toml
+++ /dev/null
@@ -1,2 +0,0 @@
-x = 64
-y = 1
diff --git a/crates/nargo_cli/tests/test_data/bit_shifts_runtime/src/main.nr b/crates/nargo_cli/tests/test_data/bit_shifts_runtime/src/main.nr
deleted file mode 100644
index 903a5f35463..00000000000
--- a/crates/nargo_cli/tests/test_data/bit_shifts_runtime/src/main.nr
+++ /dev/null
@@ -1,12 +0,0 @@
-fn main(x: u64, y: u64) {
-	// These are currently unimplemented and panic with "ShiftLeft and ShiftRight operations with shifts which are only known at runtime are not yet implemented."
-	// See: https://github.com/noir-lang/noir/issues/1265
-		
-	// runtime shifts on comptime values
-	assert(64 << y == 128);
-	assert(64 >> y == 32);
-
-	// runtime shifts on runtime values
-	assert(x << y == 128);
-	assert(x >> y == 32);
-}
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/ec_baby_jubjub/Nargo.toml b/crates/nargo_cli/tests/test_data/blackbox_func_simple_call/Nargo.toml
similarity index 65%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/ec_baby_jubjub/Nargo.toml
rename to crates/nargo_cli/tests/test_data/blackbox_func_simple_call/Nargo.toml
index 4a5c2a916f0..83ef3cb9f72 100644
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/ec_baby_jubjub/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/blackbox_func_simple_call/Nargo.toml
@@ -1,5 +1,5 @@
 [package]
-name = "Baby Jubjub sanity checks"
+name = "blackbox_func_simple_call"
 authors = [""]
 compiler_version = "0.1"
 
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/blackbox_func_simple_call/Prover.toml b/crates/nargo_cli/tests/test_data/blackbox_func_simple_call/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/blackbox_func_simple_call/Prover.toml
rename to crates/nargo_cli/tests/test_data/blackbox_func_simple_call/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/blackbox_func_simple_call/src/main.nr b/crates/nargo_cli/tests/test_data/blackbox_func_simple_call/src/main.nr
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/blackbox_func_simple_call/src/main.nr
rename to crates/nargo_cli/tests/test_data/blackbox_func_simple_call/src/main.nr
diff --git a/crates/nargo_cli/tests/test_data/blackbox_func_simple_call/target/main.json b/crates/nargo_cli/tests/test_data/blackbox_func_simple_call/target/main.json
new file mode 100644
index 00000000000..e7711b24f31
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/blackbox_func_simple_call/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"x":[1]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/12JSQoAMAgDp5uH/v+9pYo5iAMhJGPAJBmeq376l7apKT7YntNc5wNgQ27IZAAAAA==","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/blackbox_func_simple_call/target/witness.tr b/crates/nargo_cli/tests/test_data/blackbox_func_simple_call/target/witness.tr
new file mode 100644
index 00000000000..9a54a5c3a5a
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/blackbox_func_simple_call/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/bool_not/Nargo.toml b/crates/nargo_cli/tests/test_data/bool_not/Nargo.toml
index d9434868157..bb778dbd2b2 100644
--- a/crates/nargo_cli/tests/test_data/bool_not/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/bool_not/Nargo.toml
@@ -1,7 +1,6 @@
+[package]
+name = "bool_not"
+authors = [""]
+compiler_version = "0.1"
 
-        [package]
-        authors = [""]
-        compiler_version = "0.1"
-    
-        [dependencies]
-    
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/bool_not/target/main.json b/crates/nargo_cli/tests/test_data/bool_not/target/main.json
index 2952fadc861..fea9a1e1cbd 100644
--- a/crates/nargo_cli/tests/test_data/bool_not/target/main.json
+++ b/crates/nargo_cli/tests/test_data/bool_not/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"integer","sign":"unsigned","width":1},"visibility":"private"}],"param_witnesses":{"x":[1]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/7WSMRLDMAgEkeLkPSCEBV2+Ek3k/z8hjTLWuDVcQ3dzO8sTAF5wJs37nhfvhdLsvPYy7rWOVgYxfbBYV8EqfVdSEpVvUeahVZt1a2hUedAhxscsTn4bccGHHLjzbld29JIX3keQ+3+3t/vN2X0E9xbAnSHm5735vf2s+QF6Gh7msAQAAA==","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"integer","sign":"unsigned","width":1},"visibility":"private"}],"param_witnesses":{"x":[1]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/81SWwoDIQyMj+5nz5L4WONfr1Kpe/8jtLB+pLJ/jdABiUSYzGS8AcAGJ8zn2FENfMOO+hg14p5SL6FTpCeG2jhjym1nYsqcX4Fj7Jy41FYLVkqx05FrPPCEUeSyggt/A7kL7yB6WnMUNaPU68TdT9nJ922BJ5jmzHu8X/RUh68IyS3g9aD3+Vf59voZoaD8652aSaPEG568Nu0xBQAA","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/bool_not/target/witness.tr b/crates/nargo_cli/tests/test_data/bool_not/target/witness.tr
index ab7b16733b0..87be1158f1b 100644
Binary files a/crates/nargo_cli/tests/test_data/bool_not/target/witness.tr and b/crates/nargo_cli/tests/test_data/bool_not/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/bool_or/Nargo.toml b/crates/nargo_cli/tests/test_data/bool_or/Nargo.toml
index d9434868157..7f59fb62cbc 100644
--- a/crates/nargo_cli/tests/test_data/bool_or/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/bool_or/Nargo.toml
@@ -1,7 +1,6 @@
+[package]
+name = "bool_or"
+authors = [""]
+compiler_version = "0.1"
 
-        [package]
-        authors = [""]
-        compiler_version = "0.1"
-    
-        [dependencies]
-    
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/bool_or/target/main.json b/crates/nargo_cli/tests/test_data/bool_or/target/main.json
index e27daa45d0e..3d60f796d35 100644
--- a/crates/nargo_cli/tests/test_data/bool_or/target/main.json
+++ b/crates/nargo_cli/tests/test_data/bool_or/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"integer","sign":"unsigned","width":1},"visibility":"private"},{"name":"y","type":{"kind":"integer","sign":"unsigned","width":1},"visibility":"private"}],"param_witnesses":{"x":[1],"y":[2]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/+2VTQ6CMBCFB6ogkehVOv2BdudVJJb7H0GblGjcGd8kEJ1NWb3MxzftnIjoTM+qynkpp/6uuCqZ77lWD86l0SS2fNUmTsFr56chcGAf/M0Ea1NwYYxTHHVkZxPPPtq5BFe4HrUEd/3IqAW4a2FuhJfcoxKYI6QbFK8Cu6Xy73Ykcx+XbLT3Pa37PmbuvQC3AnOTkHdpP/934zPe5jd9mLX6OG7ARyOQ25PM+6XAfbbAuQG65p7w+z+zHso3eg8s2eg56mjd+z9zdwLcLW1j/6P9vNYdlOBNQEQOAAA=","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"integer","sign":"unsigned","width":1},"visibility":"private"},{"name":"y","type":{"kind":"integer","sign":"unsigned","width":1},"visibility":"private"}],"param_witnesses":{"x":[1],"y":[2]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/+1W2wqDMAyN98nE/UprW23f9iuT6f9/wja0kIkvw9OhYEBS83CSnJOW1ER0o8mi9xfPPmL/PkbM32evRKv10DWDVPIhGtdbI7TpWyutNNY8G6vUYLXtXO864aRWgxyNU6OYzOdIFrhim8kIiBUD+03AWF4PbhGYywSHJXi96co5ZjE/E3mAnmiRZ8ljvRKDJg8hUhoANyPcwIbqO8NrJBjk4Tg9H+Xf+s3Bc3MQPZq96nE9gB55ANyKwrxfCbjOAjg3QK1lBezxX8sVkMuv5erCzudytRGzmAlF45a07+Xq03eJ1yjocoXkNGY18svj7QUuV6DaPg8AAA==","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/bool_or/target/witness.tr b/crates/nargo_cli/tests/test_data/bool_or/target/witness.tr
index 18bddf334a0..cc166997403 100644
Binary files a/crates/nargo_cli/tests/test_data/bool_or/target/witness.tr and b/crates/nargo_cli/tests/test_data/bool_or/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/brillig_acir_as_brillig/Nargo.toml b/crates/nargo_cli/tests/test_data/brillig_acir_as_brillig/Nargo.toml
new file mode 100644
index 00000000000..162794d7c5c
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_acir_as_brillig/Nargo.toml
@@ -0,0 +1,6 @@
+[package]
+name = "brillig_acir_as_brillig"
+authors = [""]
+compiler_version = "0.1"
+
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_acir_as_brillig/Prover.toml b/crates/nargo_cli/tests/test_data/brillig_acir_as_brillig/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_acir_as_brillig/Prover.toml
rename to crates/nargo_cli/tests/test_data/brillig_acir_as_brillig/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_acir_as_brillig/src/main.nr b/crates/nargo_cli/tests/test_data/brillig_acir_as_brillig/src/main.nr
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_acir_as_brillig/src/main.nr
rename to crates/nargo_cli/tests/test_data/brillig_acir_as_brillig/src/main.nr
diff --git a/crates/nargo_cli/tests/test_data/brillig_acir_as_brillig/target/main.json b/crates/nargo_cli/tests/test_data/brillig_acir_as_brillig/target/main.json
new file mode 100644
index 00000000000..8200f09e496
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_acir_as_brillig/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"}],"param_witnesses":{"x":[1]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/brillig_acir_as_brillig/target/witness.tr b/crates/nargo_cli/tests/test_data/brillig_acir_as_brillig/target/witness.tr
new file mode 100644
index 00000000000..3e61478b2cf
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/brillig_acir_as_brillig/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/brillig_arrays/Nargo.toml b/crates/nargo_cli/tests/test_data/brillig_arrays/Nargo.toml
new file mode 100644
index 00000000000..be36814c2b3
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_arrays/Nargo.toml
@@ -0,0 +1,6 @@
+[package]
+name = "brillig_arrays"
+authors = [""]
+compiler_version = "0.1"
+
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_arrays/Prover.toml b/crates/nargo_cli/tests/test_data/brillig_arrays/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_arrays/Prover.toml
rename to crates/nargo_cli/tests/test_data/brillig_arrays/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_arrays/src/main.nr b/crates/nargo_cli/tests/test_data/brillig_arrays/src/main.nr
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_arrays/src/main.nr
rename to crates/nargo_cli/tests/test_data/brillig_arrays/src/main.nr
diff --git a/crates/nargo_cli/tests/test_data/brillig_arrays/target/main.json b/crates/nargo_cli/tests/test_data/brillig_arrays/target/main.json
new file mode 100644
index 00000000000..a5f207c6271
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_arrays/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"array","length":3,"type":{"kind":"field"}},"visibility":"private"}],"param_witnesses":{"x":[1,2,3]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/brillig_arrays/target/witness.tr b/crates/nargo_cli/tests/test_data/brillig_arrays/target/witness.tr
new file mode 100644
index 00000000000..2d9b4cf245b
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/brillig_arrays/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/brillig_assert/Nargo.toml b/crates/nargo_cli/tests/test_data/brillig_assert/Nargo.toml
new file mode 100644
index 00000000000..0b21db6224a
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_assert/Nargo.toml
@@ -0,0 +1,6 @@
+[package]
+name = "brillig_assert"
+authors = [""]
+compiler_version = "0.1"
+
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/assert/Prover.toml b/crates/nargo_cli/tests/test_data/brillig_assert/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/assert/Prover.toml
rename to crates/nargo_cli/tests/test_data/brillig_assert/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_assert/src/main.nr b/crates/nargo_cli/tests/test_data/brillig_assert/src/main.nr
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_assert/src/main.nr
rename to crates/nargo_cli/tests/test_data/brillig_assert/src/main.nr
diff --git a/crates/nargo_cli/tests/test_data/brillig_assert/target/main.json b/crates/nargo_cli/tests/test_data/brillig_assert/target/main.json
new file mode 100644
index 00000000000..e37c4ea5994
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_assert/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"x":[1]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/81WbQ6DIAyt4ueyeRYQUPjnVWaG97/Aks0IWSXul2XZS0hr1Pb1tTU2AHCBDfn7ZPBB8Cdv+TmIjC4WhwhEcftVAxbpQC5C7s/TJ/qWlCVsgOSDUm7snZDizns7G82VngcjjNBGP3ojpTPKjHa2I7dCSScWbaVbNuQEsRZPjNHVyA+bB/TDTMkZ8y2Qf/W29TOCUSF/IuJR0evES8S1RZxDPR1scx6uG29v/j3qHWiRxuxA33CvhoQfATgQIsQ+u0wFYawSaBfmF4tJyHm3mHjhiqh3Kxh6jromiPLEOnaQeFhTNCmFUDXQDX+qumv6Hu1+h/5Z0yziiPECFhQbR4sKAAA=","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/brillig_assert/target/witness.tr b/crates/nargo_cli/tests/test_data/brillig_assert/target/witness.tr
new file mode 100644
index 00000000000..fdd97d01fec
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/brillig_assert/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/brillig_assert_fail/Nargo.toml b/crates/nargo_cli/tests/test_data/brillig_assert_fail/Nargo.toml
new file mode 100644
index 00000000000..eed13cc504f
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_assert_fail/Nargo.toml
@@ -0,0 +1,6 @@
+[package]
+name = "brillig_assert_fail"
+authors = [""]
+compiler_version = "0.1"
+
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_assert_fail/Prover.toml b/crates/nargo_cli/tests/test_data/brillig_assert_fail/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_assert_fail/Prover.toml
rename to crates/nargo_cli/tests/test_data/brillig_assert_fail/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_assert_fail/src/main.nr b/crates/nargo_cli/tests/test_data/brillig_assert_fail/src/main.nr
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_assert_fail/src/main.nr
rename to crates/nargo_cli/tests/test_data/brillig_assert_fail/src/main.nr
diff --git a/crates/nargo_cli/tests/test_data/brillig_blake2s/Nargo.toml b/crates/nargo_cli/tests/test_data/brillig_blake2s/Nargo.toml
new file mode 100644
index 00000000000..25457595d0e
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_blake2s/Nargo.toml
@@ -0,0 +1,6 @@
+[package]
+name = "brillig_blake2s"
+authors = [""]
+compiler_version = "0.1"
+
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_blake2s/Prover.toml b/crates/nargo_cli/tests/test_data/brillig_blake2s/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_blake2s/Prover.toml
rename to crates/nargo_cli/tests/test_data/brillig_blake2s/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_blake2s/src/main.nr b/crates/nargo_cli/tests/test_data/brillig_blake2s/src/main.nr
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_blake2s/src/main.nr
rename to crates/nargo_cli/tests/test_data/brillig_blake2s/src/main.nr
diff --git a/crates/nargo_cli/tests/test_data/brillig_blake2s/target/main.json b/crates/nargo_cli/tests/test_data/brillig_blake2s/target/main.json
new file mode 100644
index 00000000000..b904e3a0c52
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_blake2s/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"array","length":5,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"},{"name":"result","type":{"kind":"array","length":32,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"}],"param_witnesses":{"result":[6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37],"x":[1,2,3,4,5]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/brillig_blake2s/target/witness.tr b/crates/nargo_cli/tests/test_data/brillig_blake2s/target/witness.tr
new file mode 100644
index 00000000000..2abb65d513e
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/brillig_blake2s/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/brillig_calls/Nargo.toml b/crates/nargo_cli/tests/test_data/brillig_calls/Nargo.toml
new file mode 100644
index 00000000000..3a9f6752568
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_calls/Nargo.toml
@@ -0,0 +1,6 @@
+[package]
+name = "brillig_calls"
+authors = [""]
+compiler_version = "0.1"
+
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_calls/Prover.toml b/crates/nargo_cli/tests/test_data/brillig_calls/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_calls/Prover.toml
rename to crates/nargo_cli/tests/test_data/brillig_calls/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_calls/src/main.nr b/crates/nargo_cli/tests/test_data/brillig_calls/src/main.nr
similarity index 72%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_calls/src/main.nr
rename to crates/nargo_cli/tests/test_data/brillig_calls/src/main.nr
index 795fc02c35f..fed84f80545 100644
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_calls/src/main.nr
+++ b/crates/nargo_cli/tests/test_data/brillig_calls/src/main.nr
@@ -5,6 +5,19 @@ fn main(x: u32)  {
     assert(entry_point(x) == 2);
     swap_entry_point(x, x + 1);
     assert(deep_entry_point(x) == 4);
+    multiple_values_entry_point(x);
+}
+
+unconstrained fn returns_multiple_values(x : u32) -> (u32, u32, u32, u32) {
+    (x + 1, x + 2, x + 3, x + 4)
+}
+
+unconstrained fn multiple_values_entry_point(x: u32) {
+    let (a, b, c, d) = returns_multiple_values(x);
+    assert(a == x + 1);
+    assert(b == x + 2);
+    assert(c == x + 3);
+    assert(d == x + 4);
 }
 
 unconstrained fn inner(x : u32) -> u32 {
diff --git a/crates/nargo_cli/tests/test_data/brillig_calls/target/main.json b/crates/nargo_cli/tests/test_data/brillig_calls/target/main.json
new file mode 100644
index 00000000000..91e3a0157d9
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_calls/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"}],"param_witnesses":{"x":[1]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/brillig_calls/target/witness.tr b/crates/nargo_cli/tests/test_data/brillig_calls/target/witness.tr
new file mode 100644
index 00000000000..3e61478b2cf
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/brillig_calls/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/brillig_calls_array/Nargo.toml b/crates/nargo_cli/tests/test_data/brillig_calls_array/Nargo.toml
new file mode 100644
index 00000000000..38e1bc8d076
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_calls_array/Nargo.toml
@@ -0,0 +1,6 @@
+[package]
+name = "brillig_calls_array"
+authors = [""]
+compiler_version = "0.1"
+
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_calls_array/Prover.toml b/crates/nargo_cli/tests/test_data/brillig_calls_array/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_calls_array/Prover.toml
rename to crates/nargo_cli/tests/test_data/brillig_calls_array/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_calls_array/src/main.nr b/crates/nargo_cli/tests/test_data/brillig_calls_array/src/main.nr
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_calls_array/src/main.nr
rename to crates/nargo_cli/tests/test_data/brillig_calls_array/src/main.nr
diff --git a/crates/nargo_cli/tests/test_data/brillig_calls_array/target/main.json b/crates/nargo_cli/tests/test_data/brillig_calls_array/target/main.json
new file mode 100644
index 00000000000..084ba896c05
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_calls_array/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"array","length":3,"type":{"kind":"integer","sign":"unsigned","width":32}},"visibility":"private"}],"param_witnesses":{"x":[1,2,3]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/+2by3LaMBSGj28YY2yTkKSZrth2ZzAkZscT9B2aKXmI7rrrrn2zvkwfoJWrM/wcBG2nUhATa4axrdv59Eu+6EgMiSin3yH49Qv1cQbXobiO9HWiy0WifKR/AcRzHoI4FTb6WP9fmAf26qpdMYYXwBhZZAygv2M4f6+PmR4vGAZwvrHD0Qzs61QnwJoBM7enpN19hfGqTGS5z1BnrJfAFrIEZ2bJgIEgLhJa4fjgNKX7O0iPDWU4b2zIh21PHLQd7Wzgmm2NgCH2gCU0sAzssnTPqpR2IQJbzMFMKaQNLWui6sgMHEPgYPsZaIdlZgbWTJfFcop/bJd/oeooDPxj4Of7vAD+QvAzaw7MpSin4ip9XkIcj5cKNFBtje22tRszyQ77YJyOaP+ZQORk7Hb3USL0k+M3o91YQJbMMgu3W2qSgSY4ll1qMhKaDMEeM+UGlsIuS3dPlHSoSQG2+f4oHWtSCk3GYI81qQwsV3ZZGmVnQvvh1Hv5Cliu7bJ09/EUbDEX28khHZ/9U7scXf9ci/bzNfL9LWt+QazVmVkziJtAXCiYVf/LcWr14ckhtFx3DHU19cNyuX1cbOfN/EO9WD+1q3q5enpo5+181a4+Ltqm2bbL9nH9tH6s1/Nls50/r9bNs64ssVDX9rkLbWQSlOxPGhN7de1NGnEyKD/0VcAXse02kbAjdSzJ8WB10UkuhErJ3uB31e7Ufh/V2O8+a9p74g4ZX5snjkT4oY+X7oHj2VZJr2cWqo4zOpyFRpCHZx4FvYwnhXU55UkZ0G4muLHDsUDvDOuSAgPrwnmmQhfXHppQ9IfJQ6M4SrscDXp9WBe2W4IunOet0MX2+D3mCa8s2zk1y2VbyBJ5xBJ7xJJ4xDLwiCX1iGXoEUvmEcvII5bcI5axRyyFRyylRyzBmVmOrcyiB5Hj5EqQemd8g3T29IWGeiaGfNh2yx7xru1oZwPXbAtXZicesJQesRQesYw9Ysk9Yhl5xJJ5xDL0iCX1iGXgEUviEUvsEUvkEUtoYLG8WvwQgE32W/A3A9uKIM8nfWS/hQv/3w3tgsn/xz6lG9DFhf/vRugyBXusC+f5LHRx4f+7o0Nd0P93q8/vgNOF/+9O6HILDKwL5/kidHHh/7unQ13Q//dGn9+DLi78f/dCF7aL/j/O8xV0cbSjq8GdmRxOzUkc7o6suV4CLQjs5JCO/krXu8s2tO97I8N5z2qH9ZhP2sVOXBIsZNBFauYDi+sdyv/C4nrn9p9YjvlG5L9g0DeCa3bfIV3eA1jPwJAP2546aDva2cA1rqUFgu+cLLFHLJFHLKGBxfK3X/fuxLVfHrcvvPbbfYOa1qxGcGT7+A83LDMzsKrjWJRz8I3WfStWBv4S+NnvVgF/JfhxrZ/5J6KciuM5k2kHJqf1u/n73fwz6nfz97v5zUHV0e/mPy9rv5tfb44k2v/LuQw/AWJXNkDbPgAA","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/brillig_calls_array/target/witness.tr b/crates/nargo_cli/tests/test_data/brillig_calls_array/target/witness.tr
new file mode 100644
index 00000000000..375119e60e3
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/brillig_calls_array/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/brillig_calls_conditionals/Nargo.toml b/crates/nargo_cli/tests/test_data/brillig_calls_conditionals/Nargo.toml
new file mode 100644
index 00000000000..771d014c490
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_calls_conditionals/Nargo.toml
@@ -0,0 +1,6 @@
+[package]
+name = "brillig_calls_conditionals"
+authors = [""]
+compiler_version = "0.1"
+
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_calls_conditionals/Prover.toml b/crates/nargo_cli/tests/test_data/brillig_calls_conditionals/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_calls_conditionals/Prover.toml
rename to crates/nargo_cli/tests/test_data/brillig_calls_conditionals/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_calls_conditionals/src/main.nr b/crates/nargo_cli/tests/test_data/brillig_calls_conditionals/src/main.nr
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_calls_conditionals/src/main.nr
rename to crates/nargo_cli/tests/test_data/brillig_calls_conditionals/src/main.nr
diff --git a/crates/nargo_cli/tests/test_data/brillig_calls_conditionals/target/main.json b/crates/nargo_cli/tests/test_data/brillig_calls_conditionals/target/main.json
new file mode 100644
index 00000000000..323ec175852
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_calls_conditionals/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"array","length":3,"type":{"kind":"integer","sign":"unsigned","width":32}},"visibility":"private"}],"param_witnesses":{"x":[1,2,3]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/brillig_calls_conditionals/target/witness.tr b/crates/nargo_cli/tests/test_data/brillig_calls_conditionals/target/witness.tr
new file mode 100644
index 00000000000..0e83c17cc8d
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/brillig_calls_conditionals/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/main_bool_arg/Nargo.toml b/crates/nargo_cli/tests/test_data/brillig_cast/Nargo.toml
similarity index 75%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/main_bool_arg/Nargo.toml
rename to crates/nargo_cli/tests/test_data/brillig_cast/Nargo.toml
index fb93b9aa2a7..dc6b7bff66c 100644
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/main_bool_arg/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/brillig_cast/Nargo.toml
@@ -1,6 +1,6 @@
 [package]
+name = "brillig_cast"
 authors = [""]
 compiler_version = "0.1"
 
 [dependencies]
-    
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_cast/Prover.toml b/crates/nargo_cli/tests/test_data/brillig_cast/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_cast/Prover.toml
rename to crates/nargo_cli/tests/test_data/brillig_cast/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_cast/src/main.nr b/crates/nargo_cli/tests/test_data/brillig_cast/src/main.nr
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_cast/src/main.nr
rename to crates/nargo_cli/tests/test_data/brillig_cast/src/main.nr
diff --git a/crates/nargo_cli/tests/test_data/brillig_cast/target/main.json b/crates/nargo_cli/tests/test_data/brillig_cast/target/main.json
new file mode 100644
index 00000000000..7c2348cceb4
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_cast/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[],"param_witnesses":{},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/brillig_cast/target/witness.tr b/crates/nargo_cli/tests/test_data/brillig_cast/target/witness.tr
new file mode 100644
index 00000000000..4e90289d5e1
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/brillig_cast/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/brillig_conditional/Nargo.toml b/crates/nargo_cli/tests/test_data/brillig_conditional/Nargo.toml
new file mode 100644
index 00000000000..bb54f910f77
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_conditional/Nargo.toml
@@ -0,0 +1,6 @@
+[package]
+name = "brillig_conditional"
+authors = [""]
+compiler_version = "0.1"
+
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/bool_not/Prover.toml b/crates/nargo_cli/tests/test_data/brillig_conditional/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/bool_not/Prover.toml
rename to crates/nargo_cli/tests/test_data/brillig_conditional/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_conditional/src/main.nr b/crates/nargo_cli/tests/test_data/brillig_conditional/src/main.nr
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_conditional/src/main.nr
rename to crates/nargo_cli/tests/test_data/brillig_conditional/src/main.nr
diff --git a/crates/nargo_cli/tests/test_data/brillig_conditional/target/main.json b/crates/nargo_cli/tests/test_data/brillig_conditional/target/main.json
new file mode 100644
index 00000000000..c40c6906e2f
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_conditional/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"x":[1]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/81W0Y6DIBBcAWu9S0zuT0Cgwlt/5czh///AJXdGjFvSPnVoOgkBjdmZnV02nonogzaI/9XQgf18zbt+DqbBxdJUABR3XD2QhQ9wE0Rev5noEamsWACrL86laUzGmm89xjl47fx8CSYYH/zPGKxNwYUpznHS0TibzOKjTcsGAYi1ZGESl6O+WzzCNzNSM9er2Pkr733uEY4TO19BOk54n3TLtPZM857PQFuf78+fzIczy1Vhdfmejvul2D4wzhbL6Thne4ezp8Mryd4JpmlFRxUHFI8pitjPXnQFjNUCC/OqoQHUfDM0+DBQRe1WSPYdOicqeEofB6rcrDWKVMOojnDNXyvvDl+jm1+1d/a0KTRy/AEWFX4ZJwsAAA==","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/brillig_conditional/target/witness.tr b/crates/nargo_cli/tests/test_data/brillig_conditional/target/witness.tr
new file mode 100644
index 00000000000..9462cea454b
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/brillig_conditional/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/brillig_ecdsa/Nargo.toml b/crates/nargo_cli/tests/test_data/brillig_ecdsa/Nargo.toml
new file mode 100644
index 00000000000..855646aec2c
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_ecdsa/Nargo.toml
@@ -0,0 +1,6 @@
+[package]
+name = "brillig_ecdsa"
+authors = [""]
+compiler_version = "0.1"
+
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_ecdsa/Prover.toml b/crates/nargo_cli/tests/test_data/brillig_ecdsa/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_ecdsa/Prover.toml
rename to crates/nargo_cli/tests/test_data/brillig_ecdsa/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_ecdsa/src/main.nr b/crates/nargo_cli/tests/test_data/brillig_ecdsa/src/main.nr
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_ecdsa/src/main.nr
rename to crates/nargo_cli/tests/test_data/brillig_ecdsa/src/main.nr
diff --git a/crates/nargo_cli/tests/test_data/brillig_ecdsa/target/main.json b/crates/nargo_cli/tests/test_data/brillig_ecdsa/target/main.json
new file mode 100644
index 00000000000..353f0145505
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_ecdsa/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"hashed_message","type":{"kind":"array","length":32,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"},{"name":"pub_key_x","type":{"kind":"array","length":32,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"},{"name":"pub_key_y","type":{"kind":"array","length":32,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"},{"name":"signature","type":{"kind":"array","length":64,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"}],"param_witnesses":{"hashed_message":[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32],"pub_key_x":[33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64],"pub_key_y":[65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96],"signature":[97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/brillig_ecdsa/target/witness.tr b/crates/nargo_cli/tests/test_data/brillig_ecdsa/target/witness.tr
new file mode 100644
index 00000000000..5fe202b72f0
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/brillig_ecdsa/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/brillig_field_binary_operations/Nargo.toml b/crates/nargo_cli/tests/test_data/brillig_field_binary_operations/Nargo.toml
new file mode 100644
index 00000000000..632b97a07bc
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_field_binary_operations/Nargo.toml
@@ -0,0 +1,6 @@
+[package]
+name = "brillig_field_binary_operations"
+authors = [""]
+compiler_version = "0.1"
+
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_field_binary_operations/Prover.toml b/crates/nargo_cli/tests/test_data/brillig_field_binary_operations/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_field_binary_operations/Prover.toml
rename to crates/nargo_cli/tests/test_data/brillig_field_binary_operations/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_field_binary_operations/src/main.nr b/crates/nargo_cli/tests/test_data/brillig_field_binary_operations/src/main.nr
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_field_binary_operations/src/main.nr
rename to crates/nargo_cli/tests/test_data/brillig_field_binary_operations/src/main.nr
diff --git a/crates/nargo_cli/tests/test_data/brillig_field_binary_operations/target/main.json b/crates/nargo_cli/tests/test_data/brillig_field_binary_operations/target/main.json
new file mode 100644
index 00000000000..e08b7dc3b1d
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_field_binary_operations/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[],"param_witnesses":{},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/brillig_field_binary_operations/target/witness.tr b/crates/nargo_cli/tests/test_data/brillig_field_binary_operations/target/witness.tr
new file mode 100644
index 00000000000..908ac53760e
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/brillig_field_binary_operations/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/brillig_fns_as_values/Nargo.toml b/crates/nargo_cli/tests/test_data/brillig_fns_as_values/Nargo.toml
new file mode 100644
index 00000000000..3586fbf4dc0
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_fns_as_values/Nargo.toml
@@ -0,0 +1,6 @@
+[package]
+name = "brillig_fns_as_values"
+authors = [""]
+compiler_version = "0.1"
+
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_fns_as_values/Prover.toml b/crates/nargo_cli/tests/test_data/brillig_fns_as_values/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_fns_as_values/Prover.toml
rename to crates/nargo_cli/tests/test_data/brillig_fns_as_values/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_fns_as_values/src/main.nr b/crates/nargo_cli/tests/test_data/brillig_fns_as_values/src/main.nr
similarity index 78%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_fns_as_values/src/main.nr
rename to crates/nargo_cli/tests/test_data/brillig_fns_as_values/src/main.nr
index 5af542301ec..bae24b8c4b1 100644
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_fns_as_values/src/main.nr
+++ b/crates/nargo_cli/tests/test_data/brillig_fns_as_values/src/main.nr
@@ -4,9 +4,12 @@ struct MyStruct {
 
 fn main(x: u32)  {
     assert(wrapper(increment, x) == x + 1);
+    assert(wrapper(increment_acir, x) == x + 1);
     assert(wrapper(decrement, x) == x - 1);
     assert(wrapper_with_struct(MyStruct { operation: increment }, x) == x + 1);
     assert(wrapper_with_struct(MyStruct { operation: decrement }, x) == x - 1);
+    // https://github.com/noir-lang/noir/issues/1975
+    assert(increment(x) == x + 1);
 }
 
 unconstrained fn wrapper(func: fn (u32) -> u32, param: u32) -> u32 {
@@ -26,3 +29,8 @@ unconstrained fn wrapper_with_struct(my_struct: MyStruct, param: u32) -> u32 {
     func(param)
 }
 
+
+
+fn increment_acir(x: u32) -> u32 {
+    x + 1
+}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/brillig_fns_as_values/target/main.json b/crates/nargo_cli/tests/test_data/brillig_fns_as_values/target/main.json
new file mode 100644
index 00000000000..4c7bbf189bd
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_fns_as_values/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"}],"param_witnesses":{"x":[1]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/brillig_fns_as_values/target/witness.tr b/crates/nargo_cli/tests/test_data/brillig_fns_as_values/target/witness.tr
new file mode 100644
index 00000000000..981a689c7e3
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/brillig_fns_as_values/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/brillig_hash_to_field/Nargo.toml b/crates/nargo_cli/tests/test_data/brillig_hash_to_field/Nargo.toml
new file mode 100644
index 00000000000..d04836585d4
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_hash_to_field/Nargo.toml
@@ -0,0 +1,6 @@
+[package]
+name = "brillig_hash_to_field"
+authors = [""]
+compiler_version = "0.1"
+
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_hash_to_field/Prover.toml b/crates/nargo_cli/tests/test_data/brillig_hash_to_field/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_hash_to_field/Prover.toml
rename to crates/nargo_cli/tests/test_data/brillig_hash_to_field/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_hash_to_field/src/main.nr b/crates/nargo_cli/tests/test_data/brillig_hash_to_field/src/main.nr
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_hash_to_field/src/main.nr
rename to crates/nargo_cli/tests/test_data/brillig_hash_to_field/src/main.nr
diff --git a/crates/nargo_cli/tests/test_data/brillig_hash_to_field/target/main.json b/crates/nargo_cli/tests/test_data/brillig_hash_to_field/target/main.json
new file mode 100644
index 00000000000..e41dbd47e1a
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_hash_to_field/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"input","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"input":[1]},"return_type":{"kind":"field"},"return_witnesses":[2]},"bytecode":"H4sIAAAAAAAA/7WTUQ6AIAxDhwiEaPzxIngD7n8qs0iTZvLn7M+WkeyVolFEgjyK1LMw66O2b7qC367Gfhfqz1Grmasy9d3JR/bPqSXyWif3PMb56vw+yooi02/A5ibEVy/J10vDXgi+wNnofCEf2TmTQEzsTcT7i7uPO0fDAlvfqkxmyKJQff3b3TEcMQD0auQG4TTtV2UEAAA=","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/brillig_hash_to_field/target/witness.tr b/crates/nargo_cli/tests/test_data/brillig_hash_to_field/target/witness.tr
new file mode 100644
index 00000000000..4c41f9a8bb1
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/brillig_hash_to_field/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/brillig_identity_function/Nargo.toml b/crates/nargo_cli/tests/test_data/brillig_identity_function/Nargo.toml
new file mode 100644
index 00000000000..c7af537cbde
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_identity_function/Nargo.toml
@@ -0,0 +1,6 @@
+[package]
+name = "brillig_identity_function"
+authors = [""]
+compiler_version = "0.1"
+
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_identity_function/Prover.toml b/crates/nargo_cli/tests/test_data/brillig_identity_function/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_identity_function/Prover.toml
rename to crates/nargo_cli/tests/test_data/brillig_identity_function/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_identity_function/src/main.nr b/crates/nargo_cli/tests/test_data/brillig_identity_function/src/main.nr
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_identity_function/src/main.nr
rename to crates/nargo_cli/tests/test_data/brillig_identity_function/src/main.nr
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_identity_function/target/c.json b/crates/nargo_cli/tests/test_data/brillig_identity_function/target/c.json
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_identity_function/target/c.json
rename to crates/nargo_cli/tests/test_data/brillig_identity_function/target/c.json
diff --git a/crates/nargo_cli/tests/test_data/brillig_identity_function/target/main.json b/crates/nargo_cli/tests/test_data/brillig_identity_function/target/main.json
new file mode 100644
index 00000000000..da00ec0cd3c
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_identity_function/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"x":[1]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/brillig_identity_function/target/witness.tr b/crates/nargo_cli/tests/test_data/brillig_identity_function/target/witness.tr
new file mode 100644
index 00000000000..f58a9a214f5
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/brillig_identity_function/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/brillig_integer_binary_operations/Nargo.toml b/crates/nargo_cli/tests/test_data/brillig_integer_binary_operations/Nargo.toml
new file mode 100644
index 00000000000..11360984c59
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_integer_binary_operations/Nargo.toml
@@ -0,0 +1,6 @@
+[package]
+name = "brillig_integer_binary_operations"
+authors = [""]
+compiler_version = "0.1"
+
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_integer_binary_operations/Prover.toml b/crates/nargo_cli/tests/test_data/brillig_integer_binary_operations/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_integer_binary_operations/Prover.toml
rename to crates/nargo_cli/tests/test_data/brillig_integer_binary_operations/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_integer_binary_operations/src/main.nr b/crates/nargo_cli/tests/test_data/brillig_integer_binary_operations/src/main.nr
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_integer_binary_operations/src/main.nr
rename to crates/nargo_cli/tests/test_data/brillig_integer_binary_operations/src/main.nr
diff --git a/crates/nargo_cli/tests/test_data/brillig_integer_binary_operations/target/main.json b/crates/nargo_cli/tests/test_data/brillig_integer_binary_operations/target/main.json
new file mode 100644
index 00000000000..f7b5b675d9f
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_integer_binary_operations/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[],"param_witnesses":{},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/brillig_integer_binary_operations/target/witness.tr b/crates/nargo_cli/tests/test_data/brillig_integer_binary_operations/target/witness.tr
new file mode 100644
index 00000000000..ce15e1dc0ec
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/brillig_integer_binary_operations/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/brillig_keccak/Nargo.toml b/crates/nargo_cli/tests/test_data/brillig_keccak/Nargo.toml
new file mode 100644
index 00000000000..f247567f4ee
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_keccak/Nargo.toml
@@ -0,0 +1,6 @@
+[package]
+name = "brillig_keccak"
+authors = [""]
+compiler_version = "0.1"
+
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_keccak/Prover.toml b/crates/nargo_cli/tests/test_data/brillig_keccak/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_keccak/Prover.toml
rename to crates/nargo_cli/tests/test_data/brillig_keccak/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_keccak/src/main.nr b/crates/nargo_cli/tests/test_data/brillig_keccak/src/main.nr
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_keccak/src/main.nr
rename to crates/nargo_cli/tests/test_data/brillig_keccak/src/main.nr
diff --git a/crates/nargo_cli/tests/test_data/brillig_keccak/target/main.json b/crates/nargo_cli/tests/test_data/brillig_keccak/target/main.json
new file mode 100644
index 00000000000..fae667945ae
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_keccak/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"result","type":{"kind":"array","length":32,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"}],"param_witnesses":{"result":[2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33],"x":[1]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/brillig_keccak/target/witness.tr b/crates/nargo_cli/tests/test_data/brillig_keccak/target/witness.tr
new file mode 100644
index 00000000000..7373c9eda25
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/brillig_keccak/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/main_return/Nargo.toml b/crates/nargo_cli/tests/test_data/brillig_loop/Nargo.toml
similarity index 75%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/main_return/Nargo.toml
rename to crates/nargo_cli/tests/test_data/brillig_loop/Nargo.toml
index fb93b9aa2a7..5a9ae5eabd7 100644
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/main_return/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/brillig_loop/Nargo.toml
@@ -1,6 +1,6 @@
 [package]
+name = "brillig_loop"
 authors = [""]
 compiler_version = "0.1"
 
 [dependencies]
-    
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_loop/Prover.toml b/crates/nargo_cli/tests/test_data/brillig_loop/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_loop/Prover.toml
rename to crates/nargo_cli/tests/test_data/brillig_loop/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_loop/src/main.nr b/crates/nargo_cli/tests/test_data/brillig_loop/src/main.nr
similarity index 63%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_loop/src/main.nr
rename to crates/nargo_cli/tests/test_data/brillig_loop/src/main.nr
index 7240264b2a8..e469248239e 100644
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_loop/src/main.nr
+++ b/crates/nargo_cli/tests/test_data/brillig_loop/src/main.nr
@@ -3,6 +3,7 @@
 // The features being tested is basic looping on brillig
 fn main(sum: u32){
     assert(loop(4) == sum);
+    assert(plain_loop() == sum);
 }
 
 unconstrained fn loop(x: u32) -> u32 {
@@ -12,3 +13,11 @@ unconstrained fn loop(x: u32) -> u32 {
     }
     sum
 }
+
+unconstrained fn plain_loop() -> u32 {
+    let mut sum = 0;
+    for i in 0..4 {
+        sum = sum + i;
+    }
+    sum
+}
diff --git a/crates/nargo_cli/tests/test_data/brillig_loop/target/main.json b/crates/nargo_cli/tests/test_data/brillig_loop/target/main.json
new file mode 100644
index 00000000000..9810a0ceca1
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_loop/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"sum","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"}],"param_witnesses":{"sum":[1]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/brillig_loop/target/witness.tr b/crates/nargo_cli/tests/test_data/brillig_loop/target/witness.tr
new file mode 100644
index 00000000000..2c6ad2a37f5
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/brillig_loop/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/brillig_modulo/Nargo.toml b/crates/nargo_cli/tests/test_data/brillig_modulo/Nargo.toml
new file mode 100644
index 00000000000..95aa9e7de29
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_modulo/Nargo.toml
@@ -0,0 +1,6 @@
+[package]
+name = "brillig_modulo"
+authors = [""]
+compiler_version = "0.1"
+
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_modulo/Prover.toml b/crates/nargo_cli/tests/test_data/brillig_modulo/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_modulo/Prover.toml
rename to crates/nargo_cli/tests/test_data/brillig_modulo/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_modulo/src/main.nr b/crates/nargo_cli/tests/test_data/brillig_modulo/src/main.nr
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_modulo/src/main.nr
rename to crates/nargo_cli/tests/test_data/brillig_modulo/src/main.nr
diff --git a/crates/nargo_cli/tests/test_data/brillig_modulo/target/main.json b/crates/nargo_cli/tests/test_data/brillig_modulo/target/main.json
new file mode 100644
index 00000000000..28c1c1c791a
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_modulo/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[],"param_witnesses":{},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/brillig_modulo/target/witness.tr b/crates/nargo_cli/tests/test_data/brillig_modulo/target/witness.tr
new file mode 100644
index 00000000000..1c2eb70c848
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/brillig_modulo/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/brillig_nested_arrays/Nargo.toml b/crates/nargo_cli/tests/test_data/brillig_nested_arrays/Nargo.toml
new file mode 100644
index 00000000000..d26a247aa98
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_nested_arrays/Nargo.toml
@@ -0,0 +1,6 @@
+[package]
+name = "brillig_nested_arrays"
+authors = [""]
+compiler_version = "0.6.0"
+
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/pred_eq/Prover.toml b/crates/nargo_cli/tests/test_data/brillig_nested_arrays/Prover.toml
similarity index 50%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/pred_eq/Prover.toml
rename to crates/nargo_cli/tests/test_data/brillig_nested_arrays/Prover.toml
index 465ef562de4..26fdbc19975 100644
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/pred_eq/Prover.toml
+++ b/crates/nargo_cli/tests/test_data/brillig_nested_arrays/Prover.toml
@@ -1,2 +1,2 @@
-x = "1"
+x = "0"
 y = "1"
diff --git a/crates/nargo_cli/tests/test_data/brillig_nested_arrays/src/main.nr b/crates/nargo_cli/tests/test_data/brillig_nested_arrays/src/main.nr
new file mode 100644
index 00000000000..e182585f5e5
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_nested_arrays/src/main.nr
@@ -0,0 +1,30 @@
+struct Header {
+    params: [Field; 3],
+}
+
+struct MyNote {
+    plain: Field,
+    array: [Field; 2],
+    header: Header,
+}
+
+unconstrained fn access_nested(notes: [MyNote; 2], x: Field, y: Field) -> Field {
+    notes[x].array[y] + notes[y].array[x] + notes[x].plain + notes[y].header.params[x]
+}
+
+unconstrained fn create_inside_brillig(x: Field, y: Field) {
+    let header = Header { params: [1, 2, 3]};
+    let note0 = MyNote { array: [1, 2], plain : 3, header };
+    let note1 = MyNote { array: [4, 5], plain : 6, header };
+    assert(access_nested([note0, note1], x, y) == (2 + 4 + 3 + 1));
+}
+
+fn main(x: Field, y: Field) {
+    let header = Header { params: [1, 2, 3]};
+    let note0 = MyNote { array: [1, 2], plain : 3, header };
+    let note1 = MyNote { array: [4, 5], plain : 6, header };
+
+    create_inside_brillig(x, y);
+    assert(access_nested([note0, note1], x, y) == (2 + 4 + 3 + 1));
+}
+
diff --git a/crates/nargo_cli/tests/test_data/brillig_nested_arrays/target/main.json b/crates/nargo_cli/tests/test_data/brillig_nested_arrays/target/main.json
new file mode 100644
index 00000000000..a627c0cfa54
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_nested_arrays/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"y","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"x":[1],"y":[2]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/+2c63bbNgzH6btl+SZf0nZZsy7r9tmSbMf+5ldpNucZ9mB7oe1JNmrGzt8IrDgxUHM94jk9oUwG/AECaYYE2nHOddy/pfHPv7p7XmqHn7vDz8VlJa3pyVpYctaNOH25O8BGB7sjfyS8hzbUd0pMbX2bLVrAOjzUW7pjrL19msw+Nfa8g3oLbNg2sGFHV2buZXSBvwn8vsTQ3oG2ri5HMU+539FzF8aNdMfNInesvy9l7zcClp4uS/F+Y2W7ehl94CddiT2G9hh06ytz1GBMkkvPfbtxMy9j8IL+A4Fj8BX1Rz7sI83FHtPDwA9L52LPzkZ55I7196VsLg6AZajLYjYXR8BPuhJ7DO04F0fKHDUYk+TS8wjGtZiL5+rfD0B/i+/ac/XvXFl/x/pIa9GQ6WEwD0vXoqHduGtuC0n/kcBh8a5O6Y++OtYdt9gXof6+lK3FY2BJdFmKtXiiK3PpZUyBn3Ql9hjaJ6DbVJejeL+JO7YpPU/txl15GbMX9J8JHLOvqD/yYR9pLiZMDwM/LJ2Lid24r94XIYvy+zLbF82Bn3Ql9hjacV80V+aouWOf28HzHMa12Bedq38/AP0t9kXn6t+5sv6O9ZHWohnTw2rdPLUWod2o1IFF+VwqLVuL2gJLIyCWZkAshmeHr2bpBMTSDYglCoilFxBLHBBLPyCWQUAsw4BYRgGxjANiSQJimQTEMg2IpXZllsg9//svgvYmfEZ7wTp8RnvZBnxWF8ag9hl8RrJJht+z/HXmeDOhn7UtcZwdPON9Ro3xXZNlGhDLJCCWJCCWcUAso4BYhgGxDAJi6QfEEgfE0guIJQqIpRsQSycgllZALM2AWBoBsdQFlhtdli84pn8PtL+kcRrQ/ufhp/8+6NjYpji/Jt+su+PzTSoYY0Y2aoHdOqyf/13lWLeUc9D4EXwmnRljzFSP9bO6D5HORTGObShwxsA5EPpJsRdNeJZiQCx8ZQTc/P7Al0TQbQScY9bPylcSwXboK1OBMwHOCetn5SvSPT76ylzgnAKndMdzA3XSowG/Mxf6YX3IZFr50jvQS1p3Prjnur8DPd6zfla+hBw0PvrSrcD5ATi/Y/2sfOlW4ERf+ihw3gLn90I/rJOPvAc9LPziDhilNeaToMcd6PED62flF8hB46Nf3Aucn4DzR9bPyi/uBU70i88C5z1w/iT0+xnq1I5rzGehH9Y/Mpnebr+wfni2R21+r8HPD9VeasMdJ5n0nVyUxsut9DCSm1W8RbF6b2sjuUsjuSsjuf9rf6iSAC/nxAW+AfU/Dj/xMgcva66UIPhrW9+eFglz64jpj7biNnHONGluYbApK/wbg02lQwA8uHBCHS8RfcHEJQxy0t5QGtg4xeBbskVZMhcGCCknSBVB+Xw/dc0EKeVkh8L3xsDPE2TwAgP7YZ3sg4lUY6iTPbQTNQxsnJ6yx+gN9hiW2IPXaf52oS1m8gzmWm6wJmSvnb94AKvsI0UgPx5IEotjLFQME3yK+audqONlTICfbDqGZ/Ij7Id1sg8mokygTvbQTu4wsHF6yh7JG+wxfsEe2glgBjbOTtlD2z94XdqPxEyewdqztlgjyU5U6ky31+zPcH2X9mfK7A8GNl5esr5bJE3ipQmxOMZCBQNPlRMci/VdOWmwWN8x+YVsOoFnHmDC6zy5ERNmcD3TTrQ0sHF6yh7TN9hjUmIPXi9bzwwvBbcGa8Lqkr+vlH2k2J/hdw2xOMZCxTAxtpi/ygluxfzFS0oegIX+eupik+yDCZk3UCd7aCfnGdg4PWWP+RvsMXvBHsrsmYGNs1P20PYPXi/7e5PkSUHqfq/yO7RToX70n4JVAT/H41cBP1XADytVwA/Uq4Cfi0oV8AP1KuDnv1IF/ED9mwn4QZl1ZdkNkJUv1svl/iHbp3n6ZZFtHzerxXL1uN6km3S1Wf2WbfJ8v1luHraP24fFNl3m+/Rptc2fDsKaCrL2T0V5aEgGdfoBAU09WUcBAS2o8yAAX/CLRVsnx8bhdhw6Y2e1eEktA7ltp+f8Vnq39d+RaYSNpk3xtAonD5W/AX7Wo+3vXAAA","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/brillig_nested_arrays/target/witness.tr b/crates/nargo_cli/tests/test_data/brillig_nested_arrays/target/witness.tr
new file mode 100644
index 00000000000..ce3a9267de0
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/brillig_nested_arrays/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_shield/Nargo.toml b/crates/nargo_cli/tests/test_data/brillig_not/Nargo.toml
similarity index 75%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/simple_shield/Nargo.toml
rename to crates/nargo_cli/tests/test_data/brillig_not/Nargo.toml
index 5082c6e12ec..1a714218b06 100644
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_shield/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/brillig_not/Nargo.toml
@@ -1,4 +1,5 @@
 [package]
+name = "brillig_not"
 authors = [""]
 compiler_version = "0.1"
 
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/bool_or/Prover.toml b/crates/nargo_cli/tests/test_data/brillig_not/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/bool_or/Prover.toml
rename to crates/nargo_cli/tests/test_data/brillig_not/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_not/src/main.nr b/crates/nargo_cli/tests/test_data/brillig_not/src/main.nr
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_not/src/main.nr
rename to crates/nargo_cli/tests/test_data/brillig_not/src/main.nr
diff --git a/crates/nargo_cli/tests/test_data/brillig_not/target/main.json b/crates/nargo_cli/tests/test_data/brillig_not/target/main.json
new file mode 100644
index 00000000000..76c5ee452e2
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_not/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"y","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"x":[1],"y":[2]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/+1WW26DMBBc3iFQ+tOD2BiC+ctVigr3v0ClxoqtLsj9qBhHicRKEasgzY5nd/G8E9EH3SO+/SL6DZdf7VPsCxnhsARtAoTbJjeMdKMDXAQjtCn0bQvFfxRNAjZAiUvXzUM7SyU/RTtOuhddP1201LLX/VerlZp1p4dxGgcxyk7NculHNS/3SABYiyWW4s4oEl/zCD/MSM6cb8byyj5LOyM8cpZfQTxyvE4iY1xLxtmdp7HvU3B/zDkS1vuI1YgZH/df4tHavSso4AeBPKI47L2LlQGxcnq9JUVy5nwLlm+HyoQbpgALtZoXn44NBR7WEE0qAuCeCDf8oc59wvdoZY2eWdPQdjMOpCmQY2tumzM9wG6aQtxu+oqi7WYMGBZnN0vg4J3p9W4yJGfOt/Lkh938dxx200QFxKqBZ37UkgI5r5b0jeWH3dyJWVtB0bgNPbfdrG2zwD0KajeRmsaM4/Z2M/EDo2jqqAoVAAA=","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/brillig_not/target/witness.tr b/crates/nargo_cli/tests/test_data/brillig_not/target/witness.tr
new file mode 100644
index 00000000000..22a4493bb46
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/brillig_not/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/brillig_oracle/Nargo.toml b/crates/nargo_cli/tests/test_data/brillig_oracle/Nargo.toml
new file mode 100644
index 00000000000..647a37e0b9e
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_oracle/Nargo.toml
@@ -0,0 +1,6 @@
+[package]
+name = "brillig_oracle"
+authors = [""]
+compiler_version = "0.1"
+
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_oracle/Prover.toml b/crates/nargo_cli/tests/test_data/brillig_oracle/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_oracle/Prover.toml
rename to crates/nargo_cli/tests/test_data/brillig_oracle/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_oracle/src/main.nr b/crates/nargo_cli/tests/test_data/brillig_oracle/src/main.nr
similarity index 60%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_oracle/src/main.nr
rename to crates/nargo_cli/tests/test_data/brillig_oracle/src/main.nr
index 53356c80ab9..84dcb1a0915 100644
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_oracle/src/main.nr
+++ b/crates/nargo_cli/tests/test_data/brillig_oracle/src/main.nr
@@ -2,31 +2,9 @@ use dep::std::slice;
 
 // Tests oracle usage in brillig/unconstrained functions
 fn main(x: Field)  {
-    // call through a brillig wrapper
-    oracle_print_array_wrapper([x, x]);
-
-    // TODO(#1615) Nargo currently only supports resolving one foreign call
-    // oracle_print_wrapper(x);
-
     get_number_sequence_wrapper(20);
 }
 
-// TODO(#1911)
-#[oracle(oracle_print_impl)]
-unconstrained fn oracle_print(_x : Field) -> Field {}
-
-unconstrained fn oracle_print_wrapper(x: Field) {
-    oracle_print(x);
-}
-
-// TODO(#1911)
-#[oracle(oracle_print_array_impl)]
-unconstrained fn oracle_print_array(_arr : [Field; 2]) -> Field {}
-
-unconstrained fn oracle_print_array_wrapper(arr: [Field; 2]) {
-    oracle_print_array(arr);
-}
-
 // TODO(#1911): This function does not need to be an oracle but acts 
 // as a useful test while we finalize code generation for slices in Brillig
 #[oracle(get_number_sequence)]
diff --git a/crates/nargo_cli/tests/test_data/brillig_oracle/target/main.json b/crates/nargo_cli/tests/test_data/brillig_oracle/target/main.json
new file mode 100644
index 00000000000..c9c3056a712
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_oracle/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"x":[1]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/7WV3U7CQBCFl9bWFoQCFYl60wsvvDKt+gB9ExLNxitJLOLz28aZ8Lk2JoTtJJudzM7POWcgDYwxI/NjIfw+q+UuT7Lq2e37KHfansB5i73PL8sYPH31jNoekfSaCZfQ4ZK0Jxf/zX5utvv3F9tsdvZjb7evViEFKD2Tm2sJemKkwrrYHCSsPVFNQTXGvAliideZ1VPH9Rz9C2DQWSFy7oErEz+VQ+tqb8XvVtLYL9vs7H+r0RZjuY9dzRg0hlgN16ASrBAbYjUX6F8AA1ejOTfAdS2+rm1mDqZ/gQl0mzp5Q/HR/iPhkzhYOp2zHswL+Po7yYB/3pO3gB7Kbw4N9P1O7qnwzr3yLquO6xK4CvDNwUljS+BeoY6+7jCCBpdOXgo/Qu0V+rs1Id4fzPC6rM1vXRQnddHYGrhVqz9f1dojuN4BrX0DQXJnVdsHAAA=","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/brillig_oracle/target/witness.tr b/crates/nargo_cli/tests/test_data/brillig_oracle/target/witness.tr
new file mode 100644
index 00000000000..3fead7f6b2e
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/brillig_oracle/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/brillig_pedersen/Nargo.toml b/crates/nargo_cli/tests/test_data/brillig_pedersen/Nargo.toml
new file mode 100644
index 00000000000..f36c705654a
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_pedersen/Nargo.toml
@@ -0,0 +1,6 @@
+[package]
+name = "brillig_pedersen"
+authors = [""]
+compiler_version = "0.1"
+
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_pedersen/Prover.toml b/crates/nargo_cli/tests/test_data/brillig_pedersen/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_pedersen/Prover.toml
rename to crates/nargo_cli/tests/test_data/brillig_pedersen/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_pedersen/src/main.nr b/crates/nargo_cli/tests/test_data/brillig_pedersen/src/main.nr
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_pedersen/src/main.nr
rename to crates/nargo_cli/tests/test_data/brillig_pedersen/src/main.nr
diff --git a/crates/nargo_cli/tests/test_data/brillig_pedersen/target/main.json b/crates/nargo_cli/tests/test_data/brillig_pedersen/target/main.json
new file mode 100644
index 00000000000..105856982cb
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_pedersen/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"y","type":{"kind":"field"},"visibility":"private"},{"name":"salt","type":{"kind":"field"},"visibility":"private"},{"name":"out_x","type":{"kind":"field"},"visibility":"private"},{"name":"out_y","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"out_x":[4],"out_y":[5],"salt":[3],"x":[1],"y":[2]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/brillig_pedersen/target/witness.tr b/crates/nargo_cli/tests/test_data/brillig_pedersen/target/witness.tr
new file mode 100644
index 00000000000..860141e7ad9
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/brillig_pedersen/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/brillig_recursion/Nargo.toml b/crates/nargo_cli/tests/test_data/brillig_recursion/Nargo.toml
new file mode 100644
index 00000000000..60baa6b4d71
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_recursion/Nargo.toml
@@ -0,0 +1,6 @@
+[package]
+name = "brillig_recursion"
+authors = [""]
+compiler_version = "0.1"
+
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_recursion/Prover.toml b/crates/nargo_cli/tests/test_data/brillig_recursion/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_recursion/Prover.toml
rename to crates/nargo_cli/tests/test_data/brillig_recursion/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_recursion/src/main.nr b/crates/nargo_cli/tests/test_data/brillig_recursion/src/main.nr
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_recursion/src/main.nr
rename to crates/nargo_cli/tests/test_data/brillig_recursion/src/main.nr
diff --git a/crates/nargo_cli/tests/test_data/brillig_recursion/target/main.json b/crates/nargo_cli/tests/test_data/brillig_recursion/target/main.json
new file mode 100644
index 00000000000..a3cea1a4fe8
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_recursion/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"}],"param_witnesses":{"x":[1]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/brillig_recursion/target/witness.tr b/crates/nargo_cli/tests/test_data/brillig_recursion/target/witness.tr
new file mode 100644
index 00000000000..aab7ddd1f05
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/brillig_recursion/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_references/Nargo.toml b/crates/nargo_cli/tests/test_data/brillig_references/Nargo.toml
similarity index 55%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_references/Nargo.toml
rename to crates/nargo_cli/tests/test_data/brillig_references/Nargo.toml
index 09a8dd8e8c8..a636a71aead 100644
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_references/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/brillig_references/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
+name = "brillig_references"
 authors = [""]
 compiler_version = "0.5.1"
 
-[dependencies]
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_references/Prover.toml b/crates/nargo_cli/tests/test_data/brillig_references/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_references/Prover.toml
rename to crates/nargo_cli/tests/test_data/brillig_references/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_references/src/main.nr b/crates/nargo_cli/tests/test_data/brillig_references/src/main.nr
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_references/src/main.nr
rename to crates/nargo_cli/tests/test_data/brillig_references/src/main.nr
diff --git a/crates/nargo_cli/tests/test_data/brillig_references/target/main.json b/crates/nargo_cli/tests/test_data/brillig_references/target/main.json
new file mode 100644
index 00000000000..8729f33b589
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_references/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"x":[1]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/brillig_references/target/witness.tr b/crates/nargo_cli/tests/test_data/brillig_references/target/witness.tr
new file mode 100644
index 00000000000..bf62ea672eb
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/brillig_references/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/brillig_scalar_mul/Nargo.toml b/crates/nargo_cli/tests/test_data/brillig_scalar_mul/Nargo.toml
new file mode 100644
index 00000000000..50793a51e41
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_scalar_mul/Nargo.toml
@@ -0,0 +1,6 @@
+[package]
+name = "brillig_scalar_mul"
+authors = [""]
+compiler_version = "0.1"
+
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_scalar_mul/Prover.toml b/crates/nargo_cli/tests/test_data/brillig_scalar_mul/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_scalar_mul/Prover.toml
rename to crates/nargo_cli/tests/test_data/brillig_scalar_mul/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_scalar_mul/src/main.nr b/crates/nargo_cli/tests/test_data/brillig_scalar_mul/src/main.nr
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_scalar_mul/src/main.nr
rename to crates/nargo_cli/tests/test_data/brillig_scalar_mul/src/main.nr
diff --git a/crates/nargo_cli/tests/test_data/brillig_scalar_mul/target/main.json b/crates/nargo_cli/tests/test_data/brillig_scalar_mul/target/main.json
new file mode 100644
index 00000000000..0b7c2c6728e
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_scalar_mul/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"a","type":{"kind":"field"},"visibility":"private"},{"name":"a_pub_x","type":{"kind":"field"},"visibility":"public"},{"name":"a_pub_y","type":{"kind":"field"},"visibility":"public"},{"name":"b","type":{"kind":"field"},"visibility":"private"},{"name":"b_pub_x","type":{"kind":"field"},"visibility":"public"},{"name":"b_pub_y","type":{"kind":"field"},"visibility":"public"}],"param_witnesses":{"a":[1],"a_pub_x":[2],"a_pub_y":[3],"b":[4],"b_pub_x":[5],"b_pub_y":[6]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/brillig_scalar_mul/target/witness.tr b/crates/nargo_cli/tests/test_data/brillig_scalar_mul/target/witness.tr
new file mode 100644
index 00000000000..3204207ec63
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/brillig_scalar_mul/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/brillig_schnorr/Nargo.toml b/crates/nargo_cli/tests/test_data/brillig_schnorr/Nargo.toml
new file mode 100644
index 00000000000..15f6ad5004e
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_schnorr/Nargo.toml
@@ -0,0 +1,6 @@
+[package]
+name = "brillig_schnorr"
+authors = [""]
+compiler_version = "0.1"
+
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_schnorr/Prover.toml b/crates/nargo_cli/tests/test_data/brillig_schnorr/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_schnorr/Prover.toml
rename to crates/nargo_cli/tests/test_data/brillig_schnorr/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_schnorr/src/main.nr b/crates/nargo_cli/tests/test_data/brillig_schnorr/src/main.nr
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_schnorr/src/main.nr
rename to crates/nargo_cli/tests/test_data/brillig_schnorr/src/main.nr
diff --git a/crates/nargo_cli/tests/test_data/brillig_schnorr/target/main.json b/crates/nargo_cli/tests/test_data/brillig_schnorr/target/main.json
new file mode 100644
index 00000000000..f5676095ab1
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_schnorr/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"message","type":{"kind":"array","length":10,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"},{"name":"pub_key_x","type":{"kind":"field"},"visibility":"private"},{"name":"pub_key_y","type":{"kind":"field"},"visibility":"private"},{"name":"signature","type":{"kind":"array","length":64,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"}],"param_witnesses":{"message":[1,2,3,4,5,6,7,8,9,10],"pub_key_x":[11],"pub_key_y":[12],"signature":[13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/brillig_schnorr/target/witness.tr b/crates/nargo_cli/tests/test_data/brillig_schnorr/target/witness.tr
new file mode 100644
index 00000000000..67be3f493a9
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/brillig_schnorr/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/brillig_sha256/Nargo.toml b/crates/nargo_cli/tests/test_data/brillig_sha256/Nargo.toml
new file mode 100644
index 00000000000..78fe4cf5c7b
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_sha256/Nargo.toml
@@ -0,0 +1,6 @@
+[package]
+name = "brillig_sha256"
+authors = [""]
+compiler_version = "0.1"
+
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_sha256/Prover.toml b/crates/nargo_cli/tests/test_data/brillig_sha256/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_sha256/Prover.toml
rename to crates/nargo_cli/tests/test_data/brillig_sha256/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_sha256/src/main.nr b/crates/nargo_cli/tests/test_data/brillig_sha256/src/main.nr
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_sha256/src/main.nr
rename to crates/nargo_cli/tests/test_data/brillig_sha256/src/main.nr
diff --git a/crates/nargo_cli/tests/test_data/brillig_sha256/target/main.json b/crates/nargo_cli/tests/test_data/brillig_sha256/target/main.json
new file mode 100644
index 00000000000..89566631d2e
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_sha256/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"result","type":{"kind":"array","length":32,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"}],"param_witnesses":{"result":[2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33],"x":[1]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/brillig_sha256/target/witness.tr b/crates/nargo_cli/tests/test_data/brillig_sha256/target/witness.tr
new file mode 100644
index 00000000000..94082c71dfc
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/brillig_sha256/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/brillig_slices/Nargo.toml b/crates/nargo_cli/tests/test_data/brillig_slices/Nargo.toml
new file mode 100644
index 00000000000..3bf54c7d667
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_slices/Nargo.toml
@@ -0,0 +1,6 @@
+[package]
+name = "brillig_slices"
+authors = [""]
+compiler_version = "0.6.0"
+
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/slices/Prover.toml b/crates/nargo_cli/tests/test_data/brillig_slices/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/slices/Prover.toml
rename to crates/nargo_cli/tests/test_data/brillig_slices/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data/brillig_slices/src/main.nr b/crates/nargo_cli/tests/test_data/brillig_slices/src/main.nr
new file mode 100644
index 00000000000..34a9afcd515
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_slices/src/main.nr
@@ -0,0 +1,76 @@
+use dep::std::slice;
+use dep::std;
+
+unconstrained fn main(x: Field, y: Field) {
+    let mut slice: [Field] = [y, x];
+    assert(slice.len() == 2);
+
+    slice = slice.push_back(7);
+    assert(slice.len() == 3);
+    assert(slice[0] == y);
+    assert(slice[1] == x);
+    assert(slice[2] == 7);
+
+    // Array set on slice target
+    slice[0] = x;
+    slice[1] = y;
+    slice[2] = 1;
+
+    assert(slice[0] == x);
+    assert(slice[1] == y);
+    assert(slice[2] == 1);
+
+    slice = push_front_to_slice(slice, 2);
+    assert(slice.len() == 4);
+    assert(slice[0] == 2);
+    assert(slice[1] == x);
+    assert(slice[2] == y);
+    assert(slice[3] == 1);
+
+    let (item, popped_front_slice) = slice.pop_front();
+    slice = popped_front_slice;
+    assert(item == 2);
+
+    assert(slice.len() == 3);
+    assert(slice[0] == x);
+    assert(slice[1] == y);
+    assert(slice[2] == 1);
+
+    let (popped_back_slice, another_item) = slice.pop_back();
+    slice = popped_back_slice;
+    assert(another_item == 1);
+
+    assert(slice.len() == 2);
+    assert(slice[0] == x);
+    assert(slice[1] == y);
+
+    slice = slice.insert(1, 2);
+    assert(slice.len() == 3);
+    assert(slice[0] == x);
+    assert(slice[1] == 2);
+    assert(slice[2] == y);
+
+    let (removed_slice, should_be_2) = slice.remove(1);
+    slice = removed_slice;
+    assert(should_be_2 == 2);
+
+    assert(slice.len() == 2);
+    assert(slice[0] == x);
+    assert(slice[1] == y);
+
+    let (slice_with_only_x, should_be_y) = slice.remove(1);
+    slice = slice_with_only_x;
+    assert(should_be_y == y);
+
+    assert(slice.len() == 1);
+    assert(slice[0] == x);
+
+    let (empty_slice, should_be_x) = slice.remove(0);
+    assert(should_be_x == x);
+    assert(empty_slice.len() == 0);
+}
+
+// Tests slice passing to/from functions
+unconstrained fn push_front_to_slice<T>(slice: [T], item: T) -> [T] {
+    slice.push_front(item)
+}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/brillig_slices/target/main.json b/crates/nargo_cli/tests/test_data/brillig_slices/target/main.json
new file mode 100644
index 00000000000..e14ecc59178
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_slices/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"y","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"x":[1],"y":[2]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/brillig_slices/target/witness.tr b/crates/nargo_cli/tests/test_data/brillig_slices/target/witness.tr
new file mode 100644
index 00000000000..3530c6f59c1
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/brillig_slices/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/brillig_to_be_bytes/Nargo.toml b/crates/nargo_cli/tests/test_data/brillig_to_be_bytes/Nargo.toml
new file mode 100644
index 00000000000..dafefbfe266
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_to_be_bytes/Nargo.toml
@@ -0,0 +1,6 @@
+[package]
+name = "brillig_to_be_bytes"
+authors = [""]
+compiler_version = "0.1"
+
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/to_be_bytes/Prover.toml b/crates/nargo_cli/tests/test_data/brillig_to_be_bytes/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/to_be_bytes/Prover.toml
rename to crates/nargo_cli/tests/test_data/brillig_to_be_bytes/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/to_be_bytes/src/main.nr b/crates/nargo_cli/tests/test_data/brillig_to_be_bytes/src/main.nr
similarity index 85%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/to_be_bytes/src/main.nr
rename to crates/nargo_cli/tests/test_data/brillig_to_be_bytes/src/main.nr
index f5831e8c524..508725407d0 100644
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/to_be_bytes/src/main.nr
+++ b/crates/nargo_cli/tests/test_data/brillig_to_be_bytes/src/main.nr
@@ -1,6 +1,6 @@
 use dep::std;
 
-fn main(x : Field) -> pub [u8; 31] {
+unconstrained fn main(x : Field) -> pub [u8; 31] {
     // The result of this byte array will be big-endian
     let byte_array = x.to_be_bytes(31);
     let mut bytes = [0; 31];
diff --git a/crates/nargo_cli/tests/test_data/brillig_to_be_bytes/target/main.json b/crates/nargo_cli/tests/test_data/brillig_to_be_bytes/target/main.json
new file mode 100644
index 00000000000..b81be8c30fd
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_to_be_bytes/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"x":[1]},"return_type":{"kind":"array","length":31,"type":{"kind":"integer","sign":"unsigned","width":8}},"return_witnesses":[2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/brillig_to_be_bytes/target/witness.tr b/crates/nargo_cli/tests/test_data/brillig_to_be_bytes/target/witness.tr
new file mode 100644
index 00000000000..0d48d549824
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/brillig_to_be_bytes/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/to_bits/Nargo.toml b/crates/nargo_cli/tests/test_data/brillig_to_bits/Nargo.toml
similarity index 56%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/to_bits/Nargo.toml
rename to crates/nargo_cli/tests/test_data/brillig_to_bits/Nargo.toml
index 5a02ffe4729..b6d1c94d830 100644
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/to_bits/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/brillig_to_bits/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
+name = "brillig_to_bits"
 authors = [""]
 compiler_version = "0.7.0"
 
-[dependencies]
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/to_bits/src/main.nr b/crates/nargo_cli/tests/test_data/brillig_to_bits/src/main.nr
similarity index 94%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/to_bits/src/main.nr
rename to crates/nargo_cli/tests/test_data/brillig_to_bits/src/main.nr
index feeb5089d13..65b0e5ca86c 100644
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/to_bits/src/main.nr
+++ b/crates/nargo_cli/tests/test_data/brillig_to_bits/src/main.nr
@@ -1,6 +1,6 @@
 use dep::std;
 
-fn main() {
+unconstrained fn main() {
     let field = 1000;
     let be_bits = field.to_be_bits(16);
     let le_bits = field.to_le_bits(16);
diff --git a/crates/nargo_cli/tests/test_data/brillig_to_bits/target/main.json b/crates/nargo_cli/tests/test_data/brillig_to_bits/target/main.json
new file mode 100644
index 00000000000..01a973d5190
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_to_bits/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[],"param_witnesses":{},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/brillig_to_bits/target/witness.tr b/crates/nargo_cli/tests/test_data/brillig_to_bits/target/witness.tr
new file mode 100644
index 00000000000..4e90289d5e1
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/brillig_to_bits/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/ecdsa_secp256r1/Nargo.toml b/crates/nargo_cli/tests/test_data/brillig_to_bytes_integration/Nargo.toml
similarity index 63%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/ecdsa_secp256r1/Nargo.toml
rename to crates/nargo_cli/tests/test_data/brillig_to_bytes_integration/Nargo.toml
index eb88f055647..75085d945c5 100644
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/ecdsa_secp256r1/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/brillig_to_bytes_integration/Nargo.toml
@@ -1,5 +1,5 @@
 [package]
-name = "ECDSA secp256r1 verification"
+name = "brillig_to_bytes_integration"
 authors = [""]
 compiler_version = "0.1"
 
diff --git a/crates/nargo_cli/tests/test_data/brillig_to_bytes_integration/Prover.toml b/crates/nargo_cli/tests/test_data/brillig_to_bytes_integration/Prover.toml
new file mode 100644
index 00000000000..23f7acea449
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_to_bytes_integration/Prover.toml
@@ -0,0 +1,2 @@
+x = "2040124"
+_y = "0x2000000000000000000000000000000000000000000000000000000000000000"
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/to_bytes_integration/src/main.nr b/crates/nargo_cli/tests/test_data/brillig_to_bytes_integration/src/main.nr
similarity index 76%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/to_bytes_integration/src/main.nr
rename to crates/nargo_cli/tests/test_data/brillig_to_bytes_integration/src/main.nr
index f76df026db7..964f4b49bf5 100644
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/to_bytes_integration/src/main.nr
+++ b/crates/nargo_cli/tests/test_data/brillig_to_bytes_integration/src/main.nr
@@ -1,8 +1,10 @@
 use dep::std;
 
-fn main(x : Field, a: Field)  {
+unconstrained fn main(x : Field, _y: Field)  {
+    // The result of this byte array will be big-endian
     let y: Field = 2040124;
     let be_byte_array = y.to_be_bytes(31);
+    // The result of this byte array will be little-endian
     let le_byte_array = x.to_le_bytes(31);
     
     assert(le_byte_array[0] == 60);
@@ -21,5 +23,5 @@ fn main(x : Field, a: Field)  {
     assert(z_bits[0] == 0);
     assert(p_bits[100] == z_bits[100]);
 
-    a.to_le_bits(std::field::modulus_num_bits() as u32);
-}
+   _y.to_le_bits(std::field::modulus_num_bits() as u32);
+}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/brillig_to_bytes_integration/target/main.json b/crates/nargo_cli/tests/test_data/brillig_to_bytes_integration/target/main.json
new file mode 100644
index 00000000000..e1467696dd2
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_to_bytes_integration/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"_y","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"_y":[2],"x":[1]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/brillig_to_bytes_integration/target/witness.tr b/crates/nargo_cli/tests/test_data/brillig_to_bytes_integration/target/witness.tr
new file mode 100644
index 00000000000..b3813a1f976
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/brillig_to_bytes_integration/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/brillig_to_le_bytes/Nargo.toml b/crates/nargo_cli/tests/test_data/brillig_to_le_bytes/Nargo.toml
new file mode 100644
index 00000000000..16954f119d5
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_to_le_bytes/Nargo.toml
@@ -0,0 +1,6 @@
+[package]
+name = "brillig_to_le_bytes"
+authors = [""]
+compiler_version = "0.1"
+
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/to_le_bytes/Prover.toml b/crates/nargo_cli/tests/test_data/brillig_to_le_bytes/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/to_le_bytes/Prover.toml
rename to crates/nargo_cli/tests/test_data/brillig_to_le_bytes/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/to_le_bytes/src/main.nr b/crates/nargo_cli/tests/test_data/brillig_to_le_bytes/src/main.nr
similarity index 89%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/to_le_bytes/src/main.nr
rename to crates/nargo_cli/tests/test_data/brillig_to_le_bytes/src/main.nr
index a5476ec13bf..3afa65d9eff 100644
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/to_le_bytes/src/main.nr
+++ b/crates/nargo_cli/tests/test_data/brillig_to_le_bytes/src/main.nr
@@ -1,6 +1,6 @@
 use dep::std;
 
-fn main(x : Field) -> pub [u8; 4] {
+unconstrained fn main(x : Field) -> pub [u8; 4] {
     // The result of this byte array will be little-endian
     let byte_array = x.to_le_bytes(31);
     let mut first_four_bytes = [0; 4];
diff --git a/crates/nargo_cli/tests/test_data/brillig_to_le_bytes/target/main.json b/crates/nargo_cli/tests/test_data/brillig_to_le_bytes/target/main.json
new file mode 100644
index 00000000000..1f531fc39e3
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_to_le_bytes/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"x":[1]},"return_type":{"kind":"array","length":4,"type":{"kind":"integer","sign":"unsigned","width":8}},"return_witnesses":[2,3,4,5]},"bytecode":"H4sIAAAAAAAA/+2ZS27bMBCGx1YsWZadtGn8fuQKUpsDcNllt90XWXfXZYCeoKteoJueMigoa+BPDOugyKhxgAxgcEgO5/9nSFEUnYpIT/aSQKdom2vK8mlS9ex8lT1wPGv0fhOLrw8Qx++mzBsbSgrdGXFL7XNXDsA1B2eN57zpT0xxq9sigpUi5zY4+7UhkbkQYJFLckJces/MJZeHz28u7edC2/S5SNDWj/jT/gHKH+hPI76ziG8dn0Z4ZZGxzKWOcU1ZPk3qXBLHoa5YI3DIToBLckJc+hEuQ1su77m2BJwoDvoQXEa2XG48l/wfuIzApbDlUr9TxsY+vY8J+GusBUrtHyO2iS2Pev0VQU61PgHua/ymuK/xy8uJP0db+sxcCnl4Fu2Ay00h8XVgjFPmERx/RvkIzAvj2LzPS+M4/Ny9kYPcIa5LxNIF7tsA9yLA9Tbn4HAHrjo2gc1XzMOnRh8FcWh5ZRpPdet9TOUgeoa9Ao93jT4Fj6kpj/KD9zm39VmfaWbSlmNnmjniW9pyqdfNCv4dMIi7tsWtiNtrfoqh7Qn0L3KQNXRdi8rZr4tFxI76LBhToH/RccxL8HCoK5Z/1j7DZhHhPQVv7ddnwa8tzpuWiw5imUs7lnnAme+oWXdc6ndUiD2K5CFH/xxt/WBsJu11xG+hFfQB4lTMZWDXwTqq9w/y8HJs/1iDy9aWS71/7ODfAYO417a4FXF1/1AMbU+gf5eDXEPXOVbOfg43ETvqq2BMgf5NxzFvwcOhrlh+//gGm02EN8/W2r8E740xb++D+28RcMsRB/es3X/M3w7c0iBfHXCp96wQu6vcbx/JvbapXXjuNr1PrfZnfc1x7J5S5diexj1d78J4N55bci73+xzvlpy0v7u0NL5zqoir+xzfN5pD1X/BVu38/N0jT2ewGSN398EYtRlCpx8dG+o6j/yW1376yh7h18F9Q51P3ic61MfA/4kYhpG4wrtZniOGaAvvjjOJ/M/nDIOTAOBvf8z9AQM5SZh9HAAA","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/brillig_to_le_bytes/target/witness.tr b/crates/nargo_cli/tests/test_data/brillig_to_le_bytes/target/witness.tr
new file mode 100644
index 00000000000..3a194cc0031
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/brillig_to_le_bytes/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/brillig_top_level/Nargo.toml b/crates/nargo_cli/tests/test_data/brillig_top_level/Nargo.toml
new file mode 100644
index 00000000000..e1779a1d3b2
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_top_level/Nargo.toml
@@ -0,0 +1,6 @@
+[package]
+name = "brillig_top_level"
+authors = [""]
+compiler_version = "0.1"
+
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_top_level/Prover.toml b/crates/nargo_cli/tests/test_data/brillig_top_level/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_top_level/Prover.toml
rename to crates/nargo_cli/tests/test_data/brillig_top_level/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_top_level/src/main.nr b/crates/nargo_cli/tests/test_data/brillig_top_level/src/main.nr
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_top_level/src/main.nr
rename to crates/nargo_cli/tests/test_data/brillig_top_level/src/main.nr
diff --git a/crates/nargo_cli/tests/test_data/brillig_top_level/target/main.json b/crates/nargo_cli/tests/test_data/brillig_top_level/target/main.json
new file mode 100644
index 00000000000..80be2b055af
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/brillig_top_level/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"array","type":{"kind":"array","length":3,"type":{"kind":"field"}},"visibility":"private"},{"name":"x","type":{"kind":"field"},"visibility":"public"}],"param_witnesses":{"array":[1,2,3],"x":[4]},"return_type":{"kind":"array","length":2,"type":{"kind":"field"}},"return_witnesses":[5,6]},"bytecode":"H4sIAAAAAAAA/9WUbQ6DIAyGy4cgmuwEO4RuF+D+p5o4Gt5Vsz8rWXwTApRqn1ZsJCJDb7lt2Lo2dY9iv1zn5TetRu9dSy9GewFG14GxB6dX5DTAyHd22EYA/nudE7W7bMBm6VP4bNbhfAb9Oi4lzwh5sDifG9RDnnEdpm144Reo1SDrsK6Sw0Es1njCOQBnFH4B8s46nI8kOIqM2GdYJ2CZdFn2f3CmY304zgznHjhmXY69P08if2Sgk/U31vhn1gS2EWxWMBdO+e1VmzVRa1wOgnk6NrMXDKpTAaEHAAA=","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/brillig_top_level/target/witness.tr b/crates/nargo_cli/tests/test_data/brillig_top_level/target/witness.tr
new file mode 100644
index 00000000000..38bdf1f7263
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/brillig_top_level/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/cast_bool/Nargo.toml b/crates/nargo_cli/tests/test_data/cast_bool/Nargo.toml
index d9434868157..0f7103580df 100644
--- a/crates/nargo_cli/tests/test_data/cast_bool/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/cast_bool/Nargo.toml
@@ -1,7 +1,6 @@
+[package]
+name = "cast_bool"
+authors = [""]
+compiler_version = "0.1"
 
-        [package]
-        authors = [""]
-        compiler_version = "0.1"
-    
-        [dependencies]
-    
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/cast_bool/target/main.json b/crates/nargo_cli/tests/test_data/cast_bool/target/main.json
index 1296aef707e..d157823f59d 100644
--- a/crates/nargo_cli/tests/test_data/cast_bool/target/main.json
+++ b/crates/nargo_cli/tests/test_data/cast_bool/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"y","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"x":[1],"y":[2]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/82STQ6DIBCFR62t3oZhQIZdr1JSvP8RGhtIiC6ZSXybYfWF97MCwApXTeW+yzV9wqFhkdmcy8FmJPwYGxN743zaGBk9+69losyOQ0wxmIiOMu4+0l5goyBrkvP4/1fN7lHeg3COlX3m9uYwC+ag5XtW8C3ZPzQaFfvpZT0VNn8wX0qbr2zp7he49+YP34uCb8n+oZG0f+l+Wv0AhcF06fgGAAA=","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"y","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"x":[1],"y":[2]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/+1USxLCIAxNf9huPAvhU8LOq8hI738ERwcdrOwaHBZmkwyLl7yX8BYAWOA7hpQvKctjgV2GpeVqTHQqosarVD6QlcaGlZDQkr0p0jqSIeeDd9Kj0RE36/WWwHpGrIGP4xOrK2jZMWvJOXM+71io+8JNiAqcYNdnr+O58MbavMaSxgq4E/Adfy3eE/+OZAb5PsoWNRXAa06/MBQBdQzllNV/QzmIKZKg3LgztG0oD94z/44+DKVlTftsxvzzvOIOhKdrBcIJAAA=","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/cast_bool/target/witness.tr b/crates/nargo_cli/tests/test_data/cast_bool/target/witness.tr
index e900bf74c3b..2147178e3c7 100644
Binary files a/crates/nargo_cli/tests/test_data/cast_bool/target/witness.tr and b/crates/nargo_cli/tests/test_data/cast_bool/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/comptime_array_access/Nargo.toml b/crates/nargo_cli/tests/test_data/comptime_array_access/Nargo.toml
index e0b467ce5da..c0f183dd74e 100644
--- a/crates/nargo_cli/tests/test_data/comptime_array_access/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/comptime_array_access/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
+name = "comptime_array_access"
 authors = [""]
 compiler_version = "0.1"
 
-[dependencies]
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/comptime_array_access/target/main.json b/crates/nargo_cli/tests/test_data/comptime_array_access/target/main.json
index dd3211589ab..5e17d6d504e 100644
--- a/crates/nargo_cli/tests/test_data/comptime_array_access/target/main.json
+++ b/crates/nargo_cli/tests/test_data/comptime_array_access/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"a","type":{"kind":"array","length":3,"type":{"kind":"field"}},"visibility":"private"}],"param_witnesses":{"a":[1,2,3]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/2NhwA0AnYOnhhwAAAA=","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"a","type":{"kind":"array","length":3,"type":{"kind":"field"}},"visibility":"private"}],"param_witnesses":{"a":[1,2,3]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/81UUQrDIAzN2ur+dpbEaI1/u8pk9v5H2EodhDK2jyr0gTzNR/KSJ7kCgIUNpvJY+fI+g3qDiq+4V2acvS/RFWJ6oEtZAvqQZyGhIOHphLmIl5hyipjIc6ElJF5ww6Ry4UGMSt8vzXgM1FKz1mvUfao8qNjHC9uhJ9jV2c/x9iXWtHgPk0yHvBbaff5efdv2HqFKeeqZ/ltgK15vGI6d+QQAAA==","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/comptime_array_access/target/witness.tr b/crates/nargo_cli/tests/test_data/comptime_array_access/target/witness.tr
index 2d9b4cf245b..5e9a938686f 100644
Binary files a/crates/nargo_cli/tests/test_data/comptime_array_access/target/witness.tr and b/crates/nargo_cli/tests/test_data/comptime_array_access/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/comptime_fail/Nargo.toml b/crates/nargo_cli/tests/test_data/comptime_fail/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data/comptime_fail/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/comptime_fail/src/main.nr b/crates/nargo_cli/tests/test_data/comptime_fail/src/main.nr
deleted file mode 100644
index ad9ecc2f689..00000000000
--- a/crates/nargo_cli/tests/test_data/comptime_fail/src/main.nr
+++ /dev/null
@@ -1,15 +0,0 @@
-fn main(x: Field) {
-    let my_const = 2;
-    let array = [0, 1, 2, 3];
-
-    // Error here:
-    let foo = my_const + x;
-    assert(array[foo] == x);
-
-    let my_const2 = 3;
-    assert(array[my_const2] == 3);
-
-    // Using a comptime variable where a non-comptime variable is expected should be fine
-    main(my_const2);
-    assert(x != 0);
-}
diff --git a/crates/nargo_cli/tests/test_data/comptime_recursion_regression/Nargo.toml b/crates/nargo_cli/tests/test_data/comptime_recursion_regression/Nargo.toml
index e0b467ce5da..b0fa20dec39 100644
--- a/crates/nargo_cli/tests/test_data/comptime_recursion_regression/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/comptime_recursion_regression/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
+name = "comptime_recursion_regression"
 authors = [""]
 compiler_version = "0.1"
 
-[dependencies]
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/comptime_recursion_regression/target/main.json b/crates/nargo_cli/tests/test_data/comptime_recursion_regression/target/main.json
index 4b8ae4f77df..4f84ce47bb7 100644
--- a/crates/nargo_cli/tests/test_data/comptime_recursion_regression/target/main.json
+++ b/crates/nargo_cli/tests/test_data/comptime_recursion_regression/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"y","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"x":[1],"y":[2]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/82SQQ7CMAwE3ZaW8hs7ThrnxleISP7/BBSRSAiOtSX2Yp9GHnlvALDDb+Y+733iudD0wWI8vC/RFWJ6oEtZAvqQDyGhIOHphLmIl5hyipjIc6EaEtcOWxRZw7MxL32flN0H+5t79vZV70a08l4NvBdlb6vOz4rOmwKr1HeGZ2NejTo/2Nq/3+G/O9+8dwPvDWw63/ICqwIj+wQGAAA=","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"y","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"x":[1],"y":[2]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/2NmQAAmKM2IxEYGAAQwco4sAAAA","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/comptime_recursion_regression/target/witness.tr b/crates/nargo_cli/tests/test_data/comptime_recursion_regression/target/witness.tr
index 71e198a88d5..145cbf8e447 100644
Binary files a/crates/nargo_cli/tests/test_data/comptime_recursion_regression/target/witness.tr and b/crates/nargo_cli/tests/test_data/comptime_recursion_regression/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/config.toml b/crates/nargo_cli/tests/test_data/config.toml
index b191daf23db..88776ed03d2 100644
--- a/crates/nargo_cli/tests/test_data/config.toml
+++ b/crates/nargo_cli/tests/test_data/config.toml
@@ -1,7 +1,5 @@
-# List of tests to be excluded (i.e not run), as their directory name in test_data
-# Exclude "sha2_byte" due to relatively long computation time and "sha2_blocks" due to very long computation time.
-exclude = ["bit_shifts_runtime", "comptime_fail", "sha2_blocks", "sha2_byte"]
+exclude = []
 
 
-# List of tests (as their directory name in test_data) expecting to fail: if the test pass, we report an error.
-fail = ["range_fail"]
+# List of tests (as their directory name) expecting to fail: if the test pass, we report an error.
+fail = ["brillig_assert_fail", "dep_impl_primitive"]
diff --git a/crates/nargo_cli/tests/test_data/constant_return/Nargo.toml b/crates/nargo_cli/tests/test_data/constant_return/Nargo.toml
new file mode 100644
index 00000000000..00772d41ef0
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/constant_return/Nargo.toml
@@ -0,0 +1,6 @@
+[package]
+name = "constant_return"
+authors = [""]
+compiler_version = "0.1"
+
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/constant_return/Prover.toml b/crates/nargo_cli/tests/test_data/constant_return/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/constant_return/Prover.toml
rename to crates/nargo_cli/tests/test_data/constant_return/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/constant_return/src/main.nr b/crates/nargo_cli/tests/test_data/constant_return/src/main.nr
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/constant_return/src/main.nr
rename to crates/nargo_cli/tests/test_data/constant_return/src/main.nr
diff --git a/crates/nargo_cli/tests/test_data/constant_return/target/main.json b/crates/nargo_cli/tests/test_data/constant_return/target/main.json
new file mode 100644
index 00000000000..cbfa43b65ad
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/constant_return/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"_x","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"_x":[1]},"return_type":{"kind":"field"},"return_witnesses":[2]},"bytecode":"H4sIAAAAAAAA/6WOwQ2AMAwDU1goaZI2+bEKFen+IyAESBU8ex9bftheASDBnzfbHmUsIlFzENOO2ZspirZiZKSmRzbmMLHqzSs6CQd1de54swxdOIemz8fRXzsnEg36itQAAAA=","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/constant_return/target/witness.tr b/crates/nargo_cli/tests/test_data/constant_return/target/witness.tr
new file mode 100644
index 00000000000..2a69317d1c3
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/constant_return/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/contracts/Nargo.toml b/crates/nargo_cli/tests/test_data/contracts/Nargo.toml
index e0b467ce5da..08f5ea12655 100644
--- a/crates/nargo_cli/tests/test_data/contracts/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/contracts/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
+name = "contracts"
 authors = [""]
 compiler_version = "0.1"
 
-[dependencies]
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/contracts/src/main.nr b/crates/nargo_cli/tests/test_data/contracts/src/main.nr
index 53e094eb4cc..c8d70cc2d0e 100644
--- a/crates/nargo_cli/tests/test_data/contracts/src/main.nr
+++ b/crates/nargo_cli/tests/test_data/contracts/src/main.nr
@@ -5,4 +5,6 @@ fn main(x : Field, y : pub Field) {
 contract Foo {
     fn double(x: Field) -> pub Field { x * 2 }
     fn triple(x: Field) -> pub Field { x * 3 }
+    internal fn quadruple(x: Field) -> pub Field { x * 4 }
+    open internal fn skibbidy(x: Field) -> pub Field { x * 5 }
 }
diff --git a/crates/nargo_cli/tests/test_data/contracts/target/main.json b/crates/nargo_cli/tests/test_data/contracts/target/main.json
index e14f4ddc544..672eaff3bc9 100644
--- a/crates/nargo_cli/tests/test_data/contracts/target/main.json
+++ b/crates/nargo_cli/tests/test_data/contracts/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"y","type":{"kind":"field"},"visibility":"public"}],"param_witnesses":{"x":[1],"y":[2]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/7WRQQ7DIAwECSl9j41xsG/9SlHN/59QKSISSo5x9mKfVruz7xBCClet437GhXvKy+RFsJViNRsSfiFrE4bCbRMUZOFfFiKTIlWbVlAsZNhZyfouiw5efQRb/TpCnNi9xr/4csTD++x7l0Ny5PBU7/RAb8/9wyTv/p77HNnilPcPK4i5HQgEAAA=","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"y","type":{"kind":"field"},"visibility":"public"}],"param_witnesses":{"x":[1],"y":[2]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/81TMQ7DIAyEJGTsW2wMwWz9SlHN/59QKaISStlqpNxii+F8dza7McaZX6ytPluF/+Btx0VwhCDJCxK+wOfCEUIsByNj5Pj2TCQcOOWSE2QMJFhjJqknZFHgqk3Yqufx5LKDLK1ulqipude7DfplcBP7BE/mMuea42Pwpjp8xpK2CbzO6B3/LN9Of0fQUd46U9tp/Pb9J/oAW/It2nEFAAA=","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/contracts/target/witness.tr b/crates/nargo_cli/tests/test_data/contracts/target/witness.tr
index 4590635ff7c..9b6d4b799b4 100644
Binary files a/crates/nargo_cli/tests/test_data/contracts/target/witness.tr and b/crates/nargo_cli/tests/test_data/contracts/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/workspace/crates/b/Nargo.toml b/crates/nargo_cli/tests/test_data/debug_logs/Nargo.toml
similarity index 60%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/workspace/crates/b/Nargo.toml
rename to crates/nargo_cli/tests/test_data/debug_logs/Nargo.toml
index dc0c2f8917c..9c8a7404060 100644
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/workspace/crates/b/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/debug_logs/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
+name = "debug_logs"
 authors = [""]
 compiler_version = "0.8.0"
 
-[dependencies]
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/vectors/Prover.toml b/crates/nargo_cli/tests/test_data/debug_logs/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/vectors/Prover.toml
rename to crates/nargo_cli/tests/test_data/debug_logs/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data/debug_logs/src/main.nr b/crates/nargo_cli/tests/test_data/debug_logs/src/main.nr
new file mode 100644
index 00000000000..29386feb98c
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/debug_logs/src/main.nr
@@ -0,0 +1,22 @@
+use dep::std;
+
+fn main(x : Field, y : pub Field) {
+
+    std::println("*** println ***");
+    std::println(x);
+    std::println([x, y]);
+    
+    let s = myStruct { y: x, x: y };
+    let foo = fooStruct { my_struct: s, foo: 15 };
+    std::println(foo);
+}
+
+struct myStruct {
+    y: Field,
+    x: Field,
+}
+
+struct fooStruct {
+    my_struct: myStruct,
+    foo: Field,
+}
diff --git a/crates/nargo_cli/tests/test_data/debug_logs/target/main.json b/crates/nargo_cli/tests/test_data/debug_logs/target/main.json
new file mode 100644
index 00000000000..3f38a77685a
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/debug_logs/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"y","type":{"kind":"field"},"visibility":"public"}],"param_witnesses":{"x":[1],"y":[2]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/debug_logs/target/witness.tr b/crates/nargo_cli/tests/test_data/debug_logs/target/witness.tr
new file mode 100644
index 00000000000..3530c6f59c1
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/debug_logs/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/dep_impl_primitive/Nargo.toml b/crates/nargo_cli/tests/test_data/dep_impl_primitive/Nargo.toml
new file mode 100644
index 00000000000..946d14cf275
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/dep_impl_primitive/Nargo.toml
@@ -0,0 +1,7 @@
+[package]
+name = "dep_impl_primitive"
+authors = [""]
+compiler_version = "0.8.0"
+
+[dependencies]
+bad_impl = { path = "../../test_libraries/bad_impl" }
diff --git a/crates/nargo_cli/tests/test_data/comptime_fail/Prover.toml b/crates/nargo_cli/tests/test_data/dep_impl_primitive/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data/comptime_fail/Prover.toml
rename to crates/nargo_cli/tests/test_data/dep_impl_primitive/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data/dep_impl_primitive/src/main.nr b/crates/nargo_cli/tests/test_data/dep_impl_primitive/src/main.nr
new file mode 100644
index 00000000000..ff9a40da18e
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/dep_impl_primitive/src/main.nr
@@ -0,0 +1,5 @@
+use dep::bad_impl;
+
+fn main(x : Field) {
+    x.something();
+}
diff --git a/crates/nargo_cli/tests/test_data/diamond_deps_0/Nargo.toml b/crates/nargo_cli/tests/test_data/diamond_deps_0/Nargo.toml
index d5094940130..ae9457e2286 100644
--- a/crates/nargo_cli/tests/test_data/diamond_deps_0/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/diamond_deps_0/Nargo.toml
@@ -1,7 +1,8 @@
 [package]
+name = "diamond_deps_0"
 authors = [""]
 compiler_version = "0.7.1"
 
 [dependencies]
 dep1 = { path = "../../test_libraries/diamond_deps_1" }
-dep2 = { path = "../../test_libraries/diamond_deps_2" }
\ No newline at end of file
+dep2 = { path = "../../test_libraries/diamond_deps_2" }
diff --git a/crates/nargo_cli/tests/test_data/diamond_deps_0/target/main.json b/crates/nargo_cli/tests/test_data/diamond_deps_0/target/main.json
index 94d4ea0d36c..ca1d2ed97b2 100644
--- a/crates/nargo_cli/tests/test_data/diamond_deps_0/target/main.json
+++ b/crates/nargo_cli/tests/test_data/diamond_deps_0/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"y","type":{"kind":"field"},"visibility":"public"}],"param_witnesses":{"x":[1],"y":[2]},"return_type":{"kind":"field"},"return_witnesses":[3]},"bytecode":"H4sIAAAAAAAA/62QQQ6AIAwEEXxQS1tob35FYvn/E4wJJiQeZS9zm2xmDyFs4bs0eAzCv+VtoStOLoLC7DU7Ep6QrakASyuKiqJyZSVyZa3WrIIhk2MXoz5kad0vejvGqenjvwH0cBkOZAEAAA==","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"y","type":{"kind":"field"},"visibility":"public"}],"param_witnesses":{"x":[1],"y":[2]},"return_type":{"kind":"field"},"return_witnesses":[3]},"bytecode":"H4sIAAAAAAAA/62QUQ6AIAxDQTzQxjbY/ryKxHH/IxgTTEj8lP60X69N9xBCDF+l4cdw+KccF7K2iUVQmL1mR8ITsjUVYGlFUVFUrqxErqzVmlUwZHLsYtQHLK3bRe+Pcfp0m/LTdQNwRaP0cAEAAA==","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/distinct_keyword/Nargo.toml b/crates/nargo_cli/tests/test_data/distinct_keyword/Nargo.toml
new file mode 100644
index 00000000000..e843cdfb74c
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/distinct_keyword/Nargo.toml
@@ -0,0 +1,6 @@
+[package]
+name = "distinct_keyword"
+authors = [""]
+compiler_version = "0.1"
+
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/distinct_keyword/Prover.toml b/crates/nargo_cli/tests/test_data/distinct_keyword/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/distinct_keyword/Prover.toml
rename to crates/nargo_cli/tests/test_data/distinct_keyword/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/distinct_keyword/src/main.nr b/crates/nargo_cli/tests/test_data/distinct_keyword/src/main.nr
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/distinct_keyword/src/main.nr
rename to crates/nargo_cli/tests/test_data/distinct_keyword/src/main.nr
diff --git a/crates/nargo_cli/tests/test_data/distinct_keyword/target/main.json b/crates/nargo_cli/tests/test_data/distinct_keyword/target/main.json
new file mode 100644
index 00000000000..ad8ebce2475
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/distinct_keyword/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"public"}],"param_witnesses":{"x":[1]},"return_type":{"kind":"array","length":2,"type":{"kind":"field"}},"return_witnesses":[3,4]},"bytecode":"H4sIAAAAAAAA/9WRQQ6AIAwEEfU/LW2lvfkVifj/JxgSTEg8Cgf3srftTnd1zs3uLV99rw7fhFOTRbAx5xgyEh4QLKkAS9oUFUXlDEqUlTVasgiGTBkvMbpqmO/YaySz78g89+sFf9l5GcA8Nf6wl9+WWzcyyYCuDAMAAA==","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/distinct_keyword/target/witness.tr b/crates/nargo_cli/tests/test_data/distinct_keyword/target/witness.tr
new file mode 100644
index 00000000000..d79dfba9359
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/distinct_keyword/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/double_verify_proof/Prover.toml b/crates/nargo_cli/tests/test_data/double_verify_proof/Prover.toml
deleted file mode 100644
index 3b4ca3c198f..00000000000
--- a/crates/nargo_cli/tests/test_data/double_verify_proof/Prover.toml
+++ /dev/null
@@ -1,6 +0,0 @@
-input_aggregation_object = ["0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0"]
-key_hash = "0x284158f92a5305f662f78fc36a397fb8eb44d229fd22152e2dc085cad142c3c2"
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\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/double_verify_proof/src/main.nr b/crates/nargo_cli/tests/test_data/double_verify_proof/src/main.nr
deleted file mode 100644
index 7c5b5289661..00000000000
--- a/crates/nargo_cli/tests/test_data/double_verify_proof/src/main.nr
+++ /dev/null
@@ -1,32 +0,0 @@
-use dep::std;
-
-fn main(
-    verification_key : [Field; 114], 
-    proof : [Field; 94], 
-    public_inputs : [Field; 1], 
-    key_hash : Field, 
-    input_aggregation_object : [Field; 16],
-    proof_b : [Field; 94],
-) -> pub [Field; 16] {
-    let output_aggregation_object_a = std::verify_proof(
-        verification_key, 
-        proof, 
-        public_inputs, 
-        key_hash, 
-        input_aggregation_object
-    );
-
-    let output_aggregation_object = std::verify_proof(
-        verification_key,
-        proof_b,
-        public_inputs,
-        key_hash,
-        output_aggregation_object_a
-    );
-
-    let mut output = [0; 16];
-    for i in 0..16 {
-        output[i] = output_aggregation_object[i];
-    }
-    output
-}
diff --git a/crates/nargo_cli/tests/test_data/double_verify_proof/target/main.json b/crates/nargo_cli/tests/test_data/double_verify_proof/target/main.json
deleted file mode 100644
index 82e0528eb67..00000000000
--- a/crates/nargo_cli/tests/test_data/double_verify_proof/target/main.json
+++ /dev/null
@@ -1 +0,0 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"verification_key","type":{"kind":"array","length":114,"type":{"kind":"field"}},"visibility":"private"},{"name":"proof","type":{"kind":"array","length":94,"type":{"kind":"field"}},"visibility":"private"},{"name":"public_inputs","type":{"kind":"array","length":1,"type":{"kind":"field"}},"visibility":"private"},{"name":"key_hash","type":{"kind":"field"},"visibility":"private"},{"name":"input_aggregation_object","type":{"kind":"array","length":16,"type":{"kind":"field"}},"visibility":"private"},{"name":"proof_b","type":{"kind":"array","length":94,"type":{"kind":"field"}},"visibility":"private"}],"param_witnesses":{"input_aggregation_object":[211,212,213,214,215,216,217,218,219,220,221,222,223,224,225,226],"key_hash":[210],"proof":[115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200,201,202,203,204,205,206,207,208],"proof_b":[227,228,229,230,231,232,233,234,235,236,237,238,239,240,241,242,243,244,245,246,247,248,249,250,251,252,253,254,255,256,257,258,259,260,261,262,263,264,265,266,267,268,269,270,271,272,273,274,275,276,277,278,279,280,281,282,283,284,285,286,287,288,289,290,291,292,293,294,295,296,297,298,299,300,301,302,303,304,305,306,307,308,309,310,311,312,313,314,315,316,317,318,319,320],"public_inputs":[209],"verification_key":[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114]},"return_type":{"kind":"array","length":16,"type":{"kind":"field"}},"return_witnesses":[337,338,339,340,341,342,343,344,345,346,347,348,349,350,351,352]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/double_verify_proof/target/witness.tr b/crates/nargo_cli/tests/test_data/double_verify_proof/target/witness.tr
deleted file mode 100644
index 82e8cf3ff57..00000000000
Binary files a/crates/nargo_cli/tests/test_data/double_verify_proof/target/witness.tr and /dev/null differ
diff --git a/crates/nargo_cli/tests/test_data/ec_baby_jubjub/Nargo.toml b/crates/nargo_cli/tests/test_data/ec_baby_jubjub/Nargo.toml
index 4a5c2a916f0..41f8cb35a32 100644
--- a/crates/nargo_cli/tests/test_data/ec_baby_jubjub/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/ec_baby_jubjub/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
-name = "Baby Jubjub sanity checks"
+name = "ec_baby_jubjub"
+description = "Baby Jubjub sanity checks"
 authors = [""]
 compiler_version = "0.1"
 
diff --git a/crates/nargo_cli/tests/test_data/ec_baby_jubjub/target/main.json b/crates/nargo_cli/tests/test_data/ec_baby_jubjub/target/main.json
index 2be12380b65..4c3bb072cb3 100644
--- a/crates/nargo_cli/tests/test_data/ec_baby_jubjub/target/main.json
+++ b/crates/nargo_cli/tests/test_data/ec_baby_jubjub/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[],"param_witnesses":{},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/93MoREAAAjDwHAsxAjsPxUGW1XXN3EpoNH2O6aU9wH6j0WLMAEAAA==","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[],"param_witnesses":{},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/2NkIAwAQGbG/yQAAAA=","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/ecdsa_secp256k1/Nargo.toml b/crates/nargo_cli/tests/test_data/ecdsa_secp256k1/Nargo.toml
index 7199d3305bf..19d9a69f5e3 100644
--- a/crates/nargo_cli/tests/test_data/ecdsa_secp256k1/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/ecdsa_secp256k1/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
-name = "ECDSA secp256k1 verification"
+name = "ecdsa_secp256k1"
+description = "ECDSA secp256k1 verification"
 authors = [""]
 compiler_version = "0.1"
 
diff --git a/crates/nargo_cli/tests/test_data/ecdsa_secp256k1/target/main.json b/crates/nargo_cli/tests/test_data/ecdsa_secp256k1/target/main.json
index fa3a361e1ad..ace2a68331d 100644
--- a/crates/nargo_cli/tests/test_data/ecdsa_secp256k1/target/main.json
+++ b/crates/nargo_cli/tests/test_data/ecdsa_secp256k1/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"message","type":{"kind":"array","length":38,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"},{"name":"hashed_message","type":{"kind":"array","length":32,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"},{"name":"pub_key_x","type":{"kind":"array","length":32,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"},{"name":"pub_key_y","type":{"kind":"array","length":32,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"},{"name":"signature","type":{"kind":"array","length":64,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"}],"param_witnesses":{"hashed_message":[39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70],"message":[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38],"pub_key_x":[71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102],"pub_key_y":[103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134],"signature":[135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"message","type":{"kind":"array","length":38,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"},{"name":"hashed_message","type":{"kind":"array","length":32,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"},{"name":"pub_key_x","type":{"kind":"array","length":32,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"},{"name":"pub_key_y","type":{"kind":"array","length":32,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"},{"name":"signature","type":{"kind":"array","length":64,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"}],"param_witnesses":{"hashed_message":[39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70],"message":[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38],"pub_key_x":[71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102],"pub_key_y":[103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134],"signature":[135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/ecdsa_secp256k1/target/witness.tr b/crates/nargo_cli/tests/test_data/ecdsa_secp256k1/target/witness.tr
index 510e6886e48..e05a88a992a 100644
Binary files a/crates/nargo_cli/tests/test_data/ecdsa_secp256k1/target/witness.tr and b/crates/nargo_cli/tests/test_data/ecdsa_secp256k1/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/ecdsa_secp256r1/Nargo.toml b/crates/nargo_cli/tests/test_data/ecdsa_secp256r1/Nargo.toml
index eb88f055647..7d45332ae49 100644
--- a/crates/nargo_cli/tests/test_data/ecdsa_secp256r1/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/ecdsa_secp256r1/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
-name = "ECDSA secp256r1 verification"
+name = "ecdsa_secp256r1"
+description = "ECDSA secp256r1 verification"
 authors = [""]
 compiler_version = "0.1"
 
diff --git a/crates/nargo_cli/tests/test_data/ecdsa_secp256r1/Prover.toml b/crates/nargo_cli/tests/test_data/ecdsa_secp256r1/Prover.toml
index 60dac3997f9..a45f799877b 100644
--- a/crates/nargo_cli/tests/test_data/ecdsa_secp256r1/Prover.toml
+++ b/crates/nargo_cli/tests/test_data/ecdsa_secp256r1/Prover.toml
@@ -17,3 +17,4 @@ signature = [
     144, 138, 7,   39,  139, 67,  176, 236, 123, 135, 39,  120, 193, 78, 7,  132 
 ]
 
+
diff --git a/crates/nargo_cli/tests/test_data/ecdsa_secp256r1/src/main.nr b/crates/nargo_cli/tests/test_data/ecdsa_secp256r1/src/main.nr
index 5e96bb4f03d..058f4ca8fb1 100644
--- a/crates/nargo_cli/tests/test_data/ecdsa_secp256r1/src/main.nr
+++ b/crates/nargo_cli/tests/test_data/ecdsa_secp256r1/src/main.nr
@@ -1,5 +1,6 @@
 use dep::std;
 
+
 fn main(hashed_message : [u8;32], pub_key_x : [u8;32], pub_key_y : [u8;32], signature : [u8;64]) {
      let valid_signature = std::ecdsa_secp256r1::verify_signature(pub_key_x, pub_key_y, signature, hashed_message);
      assert(valid_signature);
diff --git a/crates/nargo_cli/tests/test_data/ecdsa_secp256r1/target/main.json b/crates/nargo_cli/tests/test_data/ecdsa_secp256r1/target/main.json
index 33c4bc632bb..e9337ff2520 100644
--- a/crates/nargo_cli/tests/test_data/ecdsa_secp256r1/target/main.json
+++ b/crates/nargo_cli/tests/test_data/ecdsa_secp256r1/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"hashed_message","type":{"kind":"array","length":32,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"},{"name":"pub_key_x","type":{"kind":"array","length":32,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"},{"name":"pub_key_y","type":{"kind":"array","length":32,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"},{"name":"signature","type":{"kind":"array","length":64,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"}],"param_witnesses":{"hashed_message":[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32],"pub_key_x":[33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64],"pub_key_y":[65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96],"signature":[97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"hashed_message","type":{"kind":"array","length":32,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"},{"name":"pub_key_x","type":{"kind":"array","length":32,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"},{"name":"pub_key_y","type":{"kind":"array","length":32,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"},{"name":"signature","type":{"kind":"array","length":64,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"}],"param_witnesses":{"hashed_message":[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32],"pub_key_x":[33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64],"pub_key_y":[65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96],"signature":[97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/eddsa/Nargo.toml b/crates/nargo_cli/tests/test_data/eddsa/Nargo.toml
deleted file mode 100644
index 48db376fb19..00000000000
--- a/crates/nargo_cli/tests/test_data/eddsa/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.3.2"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/eddsa/Prover.toml b/crates/nargo_cli/tests/test_data/eddsa/Prover.toml
deleted file mode 100644
index 53555202ca6..00000000000
--- a/crates/nargo_cli/tests/test_data/eddsa/Prover.toml
+++ /dev/null
@@ -1,3 +0,0 @@
-_priv_key_a = 123
-_priv_key_b = 456
-msg = 789
diff --git a/crates/nargo_cli/tests/test_data/eddsa/src/main.nr b/crates/nargo_cli/tests/test_data/eddsa/src/main.nr
deleted file mode 100644
index 8de38011aaf..00000000000
--- a/crates/nargo_cli/tests/test_data/eddsa/src/main.nr
+++ /dev/null
@@ -1,55 +0,0 @@
-use dep::std::compat;
-use dep::std::ec::consts::te::baby_jubjub;
-use dep::std::hash;
-use dep::std::eddsa::eddsa_poseidon_verify;
-use dep::std;
-
-fn main(msg: pub Field, _priv_key_a: Field, _priv_key_b: Field) {
-    // Skip this test for non-bn254 backends
-    if compat::is_bn254() {
-        let bjj = baby_jubjub();
-
-        let pub_key_a = bjj.curve.mul(_priv_key_a, bjj.curve.gen);
-        // let pub_key_b = bjj.curve.mul(_priv_key_b, bjj.curve.gen);
-
-        // Manually computed as fields can't use modulo. Importantantly the commitment is within
-        // the subgroup order. Note that choice of hash is flexible for this step.
-        // let r_a = hash::pedersen([_priv_key_a, msg])[0] % bjj.suborder; // modulus computed manually
-        let r_a = 1414770703199880747815475415092878800081323795074043628810774576767372531818;
-        // let r_b = hash::pedersen([_priv_key_b, msg])[0] % bjj.suborder; // modulus computed manually
-        let r_b = 571799555715456644614141527517766533395606396271089506978608487688924659618;
-
-        let r8_a = bjj.curve.mul(r_a, bjj.base8);
-        let r8_b = bjj.curve.mul(r_b, bjj.base8);
-
-        // let h_a: [Field; 6] = hash::poseidon::bn254::hash_5([
-        //     r8_a.x,
-        //     r8_a.y,
-        //     pub_key_a.x,
-        //     pub_key_a.y,
-        //     msg,
-        // ]);
-
-        // let h_b: [Field; 6] = hash::poseidon::bn254::hash_5([
-        //     r8_b.x,
-        //     r8_b.y,
-        //     pub_key_b.x,
-        //     pub_key_b.y,
-        //     msg,
-        // ]);
-
-        // let s_a = (r_a + _priv_key_a * h_a) % bjj.suborder; // modulus computed manually
-        let s_a =  30333430637424319196043722294837632681219980330991241982145549329256671548;
-        // let s_b = (r_b + _priv_key_b * h_b) % bjj.suborder; // modulus computed manually
-        let s_b = 1646085314320208098241070054368798527940102577261034947654839408482102287019;
-
-        // User A verifies their signature over the message
-        assert(eddsa_poseidon_verify(pub_key_a.x, pub_key_a.y, s_a, r8_a.x, r8_a.y, msg));
-
-        // User B's signature over the message can't be used with user A's pub key
-        assert(!eddsa_poseidon_verify(pub_key_a.x, pub_key_a.y, s_b, r8_b.x, r8_b.y, msg));
-
-        // User A's signature over the message can't be used with another message
-        assert(!eddsa_poseidon_verify(pub_key_a.x, pub_key_a.y, s_a, r8_a.x, r8_a.y, msg + 1));
-    }
-}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/eddsa/target/main.json b/crates/nargo_cli/tests/test_data/eddsa/target/main.json
deleted file mode 100644
index aebe7444fda..00000000000
--- a/crates/nargo_cli/tests/test_data/eddsa/target/main.json
+++ /dev/null
@@ -1 +0,0 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"msg","type":{"kind":"field"},"visibility":"public"},{"name":"_priv_key_a","type":{"kind":"field"},"visibility":"private"},{"name":"_priv_key_b","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"_priv_key_a":[2],"_priv_key_b":[3],"msg":[1]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/eddsa/target/witness.tr b/crates/nargo_cli/tests/test_data/eddsa/target/witness.tr
deleted file mode 100644
index ec4a639312b..00000000000
Binary files a/crates/nargo_cli/tests/test_data/eddsa/target/witness.tr and /dev/null differ
diff --git a/crates/nargo_cli/tests/test_data/generics/Nargo.toml b/crates/nargo_cli/tests/test_data/generics/Nargo.toml
index d9434868157..32fc2017336 100644
--- a/crates/nargo_cli/tests/test_data/generics/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/generics/Nargo.toml
@@ -1,7 +1,6 @@
+[package]
+name = "generics"
+authors = [""]
+compiler_version = "0.1"
 
-        [package]
-        authors = [""]
-        compiler_version = "0.1"
-    
-        [dependencies]
-    
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/generics/target/main.json b/crates/nargo_cli/tests/test_data/generics/target/main.json
index 422705257f0..2d0e3ea1a9e 100644
--- a/crates/nargo_cli/tests/test_data/generics/target/main.json
+++ b/crates/nargo_cli/tests/test_data/generics/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"y","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"x":[1],"y":[2]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/9WUQW4CMQxFTSktpaW0lC65QzxJmGTHVRgx3P8IyGiMRqCsYkseb5LV1///xfkHgD08z3w4j8Pp6gZnIy3vDiH0bdOjx5NrcpeiC7E7JEwYUzw3yfs+hdTmLrcuY/A9XmL2l0HsRVBrLpfx5ou7ex3uM+EeWftRt7aHhWAPWrkXCrkl+cNopPNL8yn5rO3zDWT3nIY035V6ZW3pHpZge58o91KZv6sc5k8+P5T4s7Z0Dyvj/Cn3agLvHgrcDfFBTZ+fgj55n0jzq+DX1Q2ytnQPa7C9T5R7bZv//T8ln99K/FlbuoeNcf6UezOBdw8F7ob4qP6nPyC/T6T5W/Dr6gZZW7qHLdjeJ8q9nQh/8vmnxJ+1pXvYGedPuXcTePegxF2az3iuQ4uV+PQTAAA=","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"y","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"x":[1],"y":[2]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/+1USQ7CMAx0VwoH3hJnaZwbXyEi/f8TECiVrJJbHakIfLGVw3g8duYMABf4jC7nW85qX2DDsIyarU1eJzR4VzpEcsq6OBMSOnIPTcYksuRDDF4FtCbh4oJZMlgriNXJzfjGagpaNsJaSnLmfPtC3RZuYqwwE2z6bHW8Ft5Em9dYUl8BdwC546819yC/I8UgD6/pGr9ioiN8n4lKcuZ8T6z+m+hOzDELKo07wbFN9DX3JL+jqiYqqWnLOPLPs8YTFPqSLLYKAAA=","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/generics/target/witness.tr b/crates/nargo_cli/tests/test_data/generics/target/witness.tr
index 7b11091fa26..5ea3587e89a 100644
Binary files a/crates/nargo_cli/tests/test_data/generics/target/witness.tr and b/crates/nargo_cli/tests/test_data/generics/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/global_consts/Nargo.toml b/crates/nargo_cli/tests/test_data/global_consts/Nargo.toml
index d9434868157..2338ec92e6b 100644
--- a/crates/nargo_cli/tests/test_data/global_consts/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/global_consts/Nargo.toml
@@ -1,7 +1,6 @@
+[package]
+name = "global_consts"
+authors = [""]
+compiler_version = "0.1"
 
-        [package]
-        authors = [""]
-        compiler_version = "0.1"
-    
-        [dependencies]
-    
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/global_consts/target/main.json b/crates/nargo_cli/tests/test_data/global_consts/target/main.json
index 7562f572446..82fa7bb94c7 100644
--- a/crates/nargo_cli/tests/test_data/global_consts/target/main.json
+++ b/crates/nargo_cli/tests/test_data/global_consts/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"a","type":{"kind":"array","length":32,"type":{"kind":"field"}},"visibility":"private"},{"name":"b","type":{"kind":"array","length":32,"type":{"kind":"field"}},"visibility":"private"},{"name":"c","type":{"kind":"array","length":3,"type":{"kind":"field"}},"visibility":"public"},{"name":"d","type":{"kind":"array","length":5,"type":{"kind":"field"}},"visibility":"private"}],"param_witnesses":{"a":[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32],"b":[33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64],"c":[65,66,67],"d":[68,69,70,71,72]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"a","type":{"kind":"array","length":32,"type":{"kind":"field"}},"visibility":"private"},{"name":"b","type":{"kind":"array","length":32,"type":{"kind":"field"}},"visibility":"private"},{"name":"c","type":{"kind":"array","length":3,"type":{"kind":"field"}},"visibility":"public"},{"name":"d","type":{"kind":"array","length":5,"type":{"kind":"field"}},"visibility":"private"}],"param_witnesses":{"a":[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32],"b":[33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64],"c":[65,66,67],"d":[68,69,70,71,72]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/+2d+7Pe0xXGV3Jyv0nc73K/J973XHLe45qLEKRSqVRK43KS99DQ0NDQ0NDQ0NDQ0NDQ0NDQ0NDQ0NDQ0NDQ0NDQSIUQQgjBH2AtWe/X2meMX/bzzew9s9fMmr1HZp4861k7n2HivO8XRPQR7arWenbXswV3S+4q7lb6622423K3427P3YG7I3cn7s7cXbj34O7K3Y17T+69uPfm3od7X+79uPfnPoD7QO6DuA/mPoT7UO7D1ENr9VDx04O7J3cv7t7cfbj7cvfj7s89gHsg9yDuwdxDuIdyH85d4C5yV3PXcNdy13EP467nLnE3cB/BfST3UdxHcx/DfSz3cPVTyUNqBPdI7lH6a1Umw+O4R3Mfz30C9xhyq6Wew/Us+FVxhNGqKQyrrS3XV5eLNcVzC9UNjaW6Qm1d47BSsVSsK9VNqS7V1JRLtaX6hsaG+kJDsbamXGyqa6hpUrETAVrlpq+qXKU7bF4twPOfiNMqWL8nmXurZrsj8xba5DATNft9mufY5Rv+GfQ3z2NJJ+WgezLhHn9ec5+M31HBSAafaaVCBt9Yig98Yykf8H3H3BP4PDXHaqBo3VMobPDJ3Kfgd5Qr+NCZVgoNvpFAn+MoPvCNo3zA911zT+Dz1ByngaJ1T6WwwSdzn4rfUa7gQ2daqZDBN57iA994ygd83zP3BD5PzfEaKFr3NAobfDL3afgd5Qo+dKaVQoNvFNDnBIoPfBMoH/B939wT+Dw1J2igaN3TKWzwydyn43eUK/jQmVYqZPBNpPjAN5HyAd8PzD2Bz1NzogaK1j2DwgafzH0Gfke5gg+daaWqwD5bAH32AGqdiZuxsLsgivRs/f7Q3BNEPTXP1EDRupMobIjK3JPwO/pWiPrmcBZhQSd1lvqcpOfZ5BYasC2BefQEap1D8QEW6dn6PdfcE2A9Nc/RQNG6jRQ2YGXuRvyOsod6tnpu1HMyuYUGVxUw715ArSkUH7iQnq3fsrkncHlqTtFA0bpNFDa4ZO4m/I6yhzpZPTfpeR65hQZXK2DevYFa51N84EJ6tn5/ZO4JXJ6a52ugaN2pFDa4ZO6p+B1lD/U89TxVzwvILTS4WgPz7gPUupDiAxfSs/X7Y3NP4PLUvFADRetOo7DBJXNPw+8oe6gXqOdpel5EbqHB1QaYd1+g1sUUH7iQnq3fn5h7Apen5sUaKFp3OoUNLpl7On5H2UO9SD1P1/MScgsNrrbAvPsBtS6l+MCF9Gz9/tTcE7g8NS/VQNG6MyhscMncM/A7yh7qJep5hp6XkVtocLUD5t0fqHU5xQcupGfr92fmnsDlqXm5BorWnUlhg0vmnonfUfZQL1PPM/W8gtxCg6s9MO8BQK0rKT5wIT1bvz839wQuT80rNVC07iwKG1wy9yz8jrKHeoV6nqXnVeQWGlwdgHkPBGpdTfGBC+nZ+v2FuSdweWperYGidWdT2OCSuWfjd5Q91KvU82w9ryG30ODqCMx7EFDrWooPXEjP1u8vzT2By1PzWg0UrTuHwgaXzD0Hv6PsoV6jnufoeR25hQZXJ2Deg4Fa11N84EJ6tn5/Ze4JXJ6a12ugaN25FDa4ZO65+B1lD/U69TxXzxvILTS4OgPzHgLUupHiAxfSs/X7a3NP4PLUvFEDRevOo7DBJXPPw+8oe6g3qOd5et5EbqHB1QWY91Cg1s0UH7iQnq3f35h7Apen5s0aKFp3PoUNLpl7Pn5H2UO9ST3P1/MWcgsNrj2AeR8O1LqV4gMX0rP1+1tzT+Dy1LxVA0XrLqCwwSVzL8DvKHuot6jnBXreRm6hwdUVmHcBqHU7xQcupGfr93fmnsDlqXm7BorWXUhhg0vmXojfUfZQb1PPC/W8g9xCg6sbMO8iUOtOig9cSM/W7+/NPYHLU/NODRStu4jCBpfMvQi/o+yh3qGeF+l5F7mFBteewLyrgVp3U3zgQnq2fv9g7glcnpp3a6Bo3cUUNrhk7sX4HWUP9S71vFjPe8gtNLj2AuZdA9S6l+IDF9Kz9ftHc0/g8tS8VwNF6y6hsMElcy/B7yh7qPeo5yV63kduocG1NzDvWqDW/RQfuJCerd8/mXsCl6fm/RooWncphQ0umXspfkfZQ71PPS/V8wFyCw2ufYB51wG1HqT4wIX0bP3+2dwTuDw1H9RA0brLKGxwydzL8DvKHuoD6nmZng+RW2hw7QvMexhQ62GKD1xIz9bvX8w9gctT82ENFK27nMIGl8y9HL+j7KE+pJ6X6/kIuYUG137AvOuBWo9SfOBCerZ+/2ruCVyemo9qoGjdFRQ2uGTuFfgdZQ/1EfW8Qs/HyC00uPYH5l0Caj1O8YEL6dn6/Zu5J3B5aj6ugaJ1V1LY4JK5V+J3lD3Ux9TzSj2fILfQ4DoAmHcDUOtJig9cSM/W79/NPYHLU/NJDRStu4rCBpfMvQq/o+yhPqGeV+n5FLmFBteBwLyPAGo9TfGBC+nZ+v2HuSdweWo+rYGidVdT2OCSuVfjd5Q91KfU82o9nyG30OA6CJj3kUCtZyk+cCE9W7//NPcELk/NZzVQtO4aChtcMvca/I6yh/qMel6j53PkFhpcBwPzPgqo9TzFBy6kZ+v3X+aewOWp+bwGitZdS2GDS+Zei99R9lCfU89r9XyB3EKD6xBg3kcDtV6k+MCF9Gz9/tvcE7g8NV/UQNG66yhscMnc6/A7yh7qC+p5nZ4vkVtocB0KzPsYoNbLFB+4kJ6t3/+YewKXp+bLGihadz2FDS6Zez1+R9lDfUk9r9fzFXILDa7DgHkfC9R6leIDF9Kz9ftfc0/g8tR8VQNF626gsMElc2/A7yh7qK+o5w16vkZuocHVHZj3cKDW6xQfuJCerd//mXsCl6fm6xooWncjhQ0umXsjfkfZQ31NPW/U8w1yq/k8vhm9AZzB+mwJzv044MybAFrlpq9q8u6C4ibKB4r/N/cERU/NTRooWvdNChuKMveb+B05QAk900qhwTca6HMzxQe+zZQP+N4y9wQ+T83NGiha920KG3wy99v4HeUKPnSmlUKD73igzy0UH/i2UD7ge8fcE/g8NbdooGjddyls8Mnc7+J3lCv40JlWCg2+E4A+t1J84NtK+YDvPXNP4PPU3KqBonXfp7DBJ3O/j99RruBDZ1opNPjGAH1uo/jAt43yAd8H5p7A56m5TQNF635IYYNP5v4Qv6NcwYfOtFJo8I0A+txOMPCVdxf4tlM+4PvI3BP4PDW3a6Bo3Y8pbPDJ3B/jd5Qr+NCZVgoNvpFAnzsoPvDtoHzA94m5J/B5au7QQNG6n1LY4JO5P8XvKFfwoTOtFBp8o4A+d1J84NtJ+YDvM3NP4PPU3KmBonU/p7DBJ3N/jt9RruBDZjraeJQ/PPKY5Q9Ta9r1B6ctdzvu9twduDtyd+LuTLseuXyrelfubtzytXnyDVTyZS7yvQjyEePyab3ywZfyGXLycUzyySbyIQHy87byo2vyUyDduXtw9+Tuxd2buw93X+5+3P25B3AP5B7EPZh7CPdQbvkmdglb/lDIV+3Jt1bJF8DIdynIx5LLJ/zKh2XK587JRzjJp6HIBwvIz+jKj7tVfnJE/p9DyUL+Jlr+UmYMfQ0Q+U92+bfXUfR1fQkgnYIFsuAAAA==","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/global_consts/target/witness.tr b/crates/nargo_cli/tests/test_data/global_consts/target/witness.tr
index e4e886f5ae5..33200a80fe2 100644
Binary files a/crates/nargo_cli/tests/test_data/global_consts/target/witness.tr and b/crates/nargo_cli/tests/test_data/global_consts/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/hash_to_field/Nargo.toml b/crates/nargo_cli/tests/test_data/hash_to_field/Nargo.toml
index e0b467ce5da..9e490846dc4 100644
--- a/crates/nargo_cli/tests/test_data/hash_to_field/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/hash_to_field/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
+name = "hash_to_field"
 authors = [""]
 compiler_version = "0.1"
 
-[dependencies]
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/hash_to_field/target/main.json b/crates/nargo_cli/tests/test_data/hash_to_field/target/main.json
index 29aaf0fe831..fecbeb7c3d5 100644
--- a/crates/nargo_cli/tests/test_data/hash_to_field/target/main.json
+++ b/crates/nargo_cli/tests/test_data/hash_to_field/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"input","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"input":[1]},"return_type":{"kind":"field"},"return_witnesses":[2]},"bytecode":"H4sIAAAAAAAA/12J0QoAAAQDDw/+/4eFJOVqre0MEIZufzsqyrGuvwTtyJBSPAAAAA==","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"input","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"input":[1]},"return_type":{"kind":"field"},"return_witnesses":[2]},"bytecode":"H4sIAAAAAAAA/12JSQoAAAgCpzr0/w9HSTcFcZkCgpeybc857cO6+AJoTFxsSAAAAA==","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/higher_order_functions/Nargo.toml b/crates/nargo_cli/tests/test_data/higher_order_functions/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data/higher_order_functions/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/higher_order_functions/src/main.nr b/crates/nargo_cli/tests/test_data/higher_order_functions/src/main.nr
deleted file mode 100644
index e5f4a2f6598..00000000000
--- a/crates/nargo_cli/tests/test_data/higher_order_functions/src/main.nr
+++ /dev/null
@@ -1,65 +0,0 @@
-use dep::std;
-
-fn main() -> pub Field {
-    let f = if 3 * 7 > 200 as u32 { foo } else { bar };
-    assert(f()[1] == 2);
-
-    // Lambdas:
-    assert(twice(|x| x * 2, 5) == 20);
-    assert((|x, y| x + y + 1)(2, 3) == 6);
-
-    // Closures:
-    let a = 42;
-    let g = || a;
-    assert(g() == 42);
-
-    // Mutable variables cannot be captured, but you can
-    // copy them into immutable variables and capture those:
-    let mut x = 2;
-    x = x + 1;
-    let z = x;
-
-    // Add extra mutations to ensure we can mutate x without the
-    // captured z changing.
-    x = x + 1;
-    assert((|y| y + z)(1) == 4);
-    x = x + 1;
-    let ret = twice(add1, 3);
-
-    test_array_functions();
-
-    ret
-}
-
-/// Test the array functions in std::array
-fn test_array_functions() {
-    let myarray: [i32; 3] = [1, 2, 3];
-    assert(myarray.any(|n| n > 2));
-
-    let evens: [i32; 3] = [2, 4, 6];
-    assert(evens.all(|n| n > 1));
-
-    assert(evens.fold(0, |a, b| a + b) == 12);
-    assert(evens.reduce(|a, b| a + b) == 12);
-    
-    let descending = myarray.sort_via(|a, b| a > b);
-    assert(descending == [3, 2, 1]);
-
-    assert(evens.map(|n| n / 2) == myarray);
-}
-
-fn foo() -> [u32; 2] {
-    [1, 3]
-}
-
-fn bar() -> [u32; 2] {
-    [3, 2]
-}
-
-fn add1(x: Field) -> Field {
-    x + 1
-}
-
-fn twice(f: fn(Field) -> Field, x: Field) -> Field {
-    f(f(x))
-}
diff --git a/crates/nargo_cli/tests/test_data/higher_order_functions/target/main.json b/crates/nargo_cli/tests/test_data/higher_order_functions/target/main.json
deleted file mode 100644
index ef21bc465e2..00000000000
--- a/crates/nargo_cli/tests/test_data/higher_order_functions/target/main.json
+++ /dev/null
@@ -1 +0,0 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[],"param_witnesses":{},"return_type":{"kind":"field"},"return_witnesses":[301]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/higher_order_functions/target/witness.tr b/crates/nargo_cli/tests/test_data/higher_order_functions/target/witness.tr
deleted file mode 100644
index 744eb584726..00000000000
Binary files a/crates/nargo_cli/tests/test_data/higher_order_functions/target/witness.tr and /dev/null differ
diff --git a/crates/nargo_cli/tests/test_data/if_else_chain/Nargo.toml b/crates/nargo_cli/tests/test_data/if_else_chain/Nargo.toml
index e0b467ce5da..e9b51315c84 100644
--- a/crates/nargo_cli/tests/test_data/if_else_chain/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/if_else_chain/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
+name = "if_else_chain"
 authors = [""]
 compiler_version = "0.1"
 
-[dependencies]
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/if_else_chain/target/main.json b/crates/nargo_cli/tests/test_data/if_else_chain/target/main.json
index ecb4bb789c2..db42e7d5b0d 100644
--- a/crates/nargo_cli/tests/test_data/if_else_chain/target/main.json
+++ b/crates/nargo_cli/tests/test_data/if_else_chain/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"a","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"},{"name":"c","type":{"kind":"array","length":4,"type":{"kind":"integer","sign":"unsigned","width":32}},"visibility":"private"}],"param_witnesses":{"a":[1],"c":[2,3,4,5]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"a","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"},{"name":"c","type":{"kind":"array","length":4,"type":{"kind":"integer","sign":"unsigned","width":32}},"visibility":"private"}],"param_witnesses":{"a":[1],"c":[2,3,4,5]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/if_else_chain/target/witness.tr b/crates/nargo_cli/tests/test_data/if_else_chain/target/witness.tr
index 17d2191d302..62d88832f6d 100644
Binary files a/crates/nargo_cli/tests/test_data/if_else_chain/target/witness.tr and b/crates/nargo_cli/tests/test_data/if_else_chain/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/integer_array_indexing/Nargo.toml b/crates/nargo_cli/tests/test_data/integer_array_indexing/Nargo.toml
new file mode 100644
index 00000000000..23dd9997c90
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/integer_array_indexing/Nargo.toml
@@ -0,0 +1,6 @@
+[package]
+name = "integer_array_indexing"
+authors = [""]
+compiler_version = "0.1"
+
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/integer_array_indexing/Prover.toml b/crates/nargo_cli/tests/test_data/integer_array_indexing/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/integer_array_indexing/Prover.toml
rename to crates/nargo_cli/tests/test_data/integer_array_indexing/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/integer_array_indexing/src/main.nr b/crates/nargo_cli/tests/test_data/integer_array_indexing/src/main.nr
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/integer_array_indexing/src/main.nr
rename to crates/nargo_cli/tests/test_data/integer_array_indexing/src/main.nr
diff --git a/crates/nargo_cli/tests/test_data/integer_array_indexing/target/main.json b/crates/nargo_cli/tests/test_data/integer_array_indexing/target/main.json
new file mode 100644
index 00000000000..37fed138972
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/integer_array_indexing/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"arr","type":{"kind":"array","length":3,"type":{"kind":"field"}},"visibility":"private"},{"name":"x","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"}],"param_witnesses":{"arr":[1,2,3],"x":[4]},"return_type":{"kind":"field"},"return_witnesses":[5]},"bytecode":"H4sIAAAAAAAA/72TYQrDIAyFtbVs7BQ7QmK0Jv92lcns/Y+wjkVwv5v1QXgK4RE+kptzbnFfdZ/V/V6T/vs77HV3v+r9D3U4JvSGWdOQRbCm1EpsSPiEKJUzpFxXRsbM+RWZqHHiIlUKCCZquGWhTcMudnPBP/nNhlnBkN/1JH5H51wM+RnuDFryC5oz3ngYmHr1D4s3QqMLTiQEAAA=","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/integer_array_indexing/target/witness.tr b/crates/nargo_cli/tests/test_data/integer_array_indexing/target/witness.tr
new file mode 100644
index 00000000000..7a6b5abdacd
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/integer_array_indexing/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/keccak256/Nargo.toml b/crates/nargo_cli/tests/test_data/keccak256/Nargo.toml
index e0b467ce5da..6e2db010876 100644
--- a/crates/nargo_cli/tests/test_data/keccak256/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/keccak256/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
+name = "keccak256"
 authors = [""]
 compiler_version = "0.1"
 
-[dependencies]
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/keccak256/target/main.json b/crates/nargo_cli/tests/test_data/keccak256/target/main.json
index 2c1f00b5a91..e10a86357e2 100644
--- a/crates/nargo_cli/tests/test_data/keccak256/target/main.json
+++ b/crates/nargo_cli/tests/test_data/keccak256/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"result","type":{"kind":"array","length":32,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"}],"param_witnesses":{"result":[2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33],"x":[1]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"result","type":{"kind":"array","length":32,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"}],"param_witnesses":{"result":[2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33],"x":[1]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/keccak256/target/witness.tr b/crates/nargo_cli/tests/test_data/keccak256/target/witness.tr
index df24ffd8ce2..de6cb4f848a 100644
Binary files a/crates/nargo_cli/tests/test_data/keccak256/target/witness.tr and b/crates/nargo_cli/tests/test_data/keccak256/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/workspace/crates/a/Nargo.toml b/crates/nargo_cli/tests/test_data/let_stmt/Nargo.toml
similarity index 61%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/workspace/crates/a/Nargo.toml
rename to crates/nargo_cli/tests/test_data/let_stmt/Nargo.toml
index dc0c2f8917c..448e473f2ed 100644
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/workspace/crates/a/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/let_stmt/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
+name = "let_stmt"
 authors = [""]
 compiler_version = "0.8.0"
 
-[dependencies]
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/numeric_generics/Prover.toml b/crates/nargo_cli/tests/test_data/let_stmt/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/numeric_generics/Prover.toml
rename to crates/nargo_cli/tests/test_data/let_stmt/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data/let_stmt/src/main.nr b/crates/nargo_cli/tests/test_data/let_stmt/src/main.nr
new file mode 100644
index 00000000000..d24a77851e4
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/let_stmt/src/main.nr
@@ -0,0 +1,10 @@
+struct Foo {
+    a: u64,
+}
+
+fn main() {
+    let _ = 42;
+    let _ = 42;
+
+    let Foo { a: _ } = Foo { a: 42 };
+}
diff --git a/crates/nargo_cli/tests/test_data/let_stmt/target/main.json b/crates/nargo_cli/tests/test_data/let_stmt/target/main.json
new file mode 100644
index 00000000000..4c3bb072cb3
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/let_stmt/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[],"param_witnesses":{},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/2NkIAwAQGbG/yQAAAA=","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/let_stmt/target/witness.tr b/crates/nargo_cli/tests/test_data/let_stmt/target/witness.tr
new file mode 100644
index 00000000000..4e90289d5e1
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/let_stmt/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/main_bool_arg/Nargo.toml b/crates/nargo_cli/tests/test_data/main_bool_arg/Nargo.toml
index fb93b9aa2a7..b80dc750c15 100644
--- a/crates/nargo_cli/tests/test_data/main_bool_arg/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/main_bool_arg/Nargo.toml
@@ -1,6 +1,6 @@
 [package]
+name = "main_bool_arg"
 authors = [""]
 compiler_version = "0.1"
 
 [dependencies]
-    
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/main_bool_arg/target/main.json b/crates/nargo_cli/tests/test_data/main_bool_arg/target/main.json
index bd1ede197e7..8a0195d4154 100644
--- a/crates/nargo_cli/tests/test_data/main_bool_arg/target/main.json
+++ b/crates/nargo_cli/tests/test_data/main_bool_arg/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"boolean"},"visibility":"private"},{"name":"y","type":{"kind":"array","length":2,"type":{"kind":"boolean"}},"visibility":"private"}],"param_witnesses":{"x":[1],"y":[2,3]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/82TQQ6DMAwEHWjhO3acEPvWrzRq+P8TKiRXpT1wwZHYi2+jXe16BoAZvgp2H3bxnCgY85/LuKTUSmzE9MSoVTKmXBchoSz5FYW5SZKiVQsqJW60ZuXVwMHPI8JB/gv5pL3P0bmnwTHz6Mi6OfY8GGdj3jvt/cP23tEEvnvvkXvqkNuzf9jpwv38/PmmNwMB1x6kBQAA","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"boolean"},"visibility":"private"},{"name":"y","type":{"kind":"array","length":2,"type":{"kind":"boolean"}},"visibility":"private"}],"param_witnesses":{"x":[1],"y":[2,3]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/7VVUQ7DIAhFbV2yj51Fqlb821VmZu9/hG2ZS5jxr0hiEEzgwVO8AMAVvqLeSzetmK0727T9ynzAzriopu9Nu3OCisXybg+hpq2ix4fbcqHoQiw7IWGk+NzI+0qBUi45uYzBVzxi9kcLxnEaYZxaEKcRjLXI1egM43cm55KYOd6V7Zem9eBO2Ak1QZen7+Nt4BNNPoOkdUJcC7IPfkbdVp6jv+HUYz7bBwuyQ+CHcfQBfOQFqMaxRWUGAAA=","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/main_bool_arg/target/witness.tr b/crates/nargo_cli/tests/test_data/main_bool_arg/target/witness.tr
index 836c869d0a6..1d56c4bc173 100644
Binary files a/crates/nargo_cli/tests/test_data/main_bool_arg/target/witness.tr and b/crates/nargo_cli/tests/test_data/main_bool_arg/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/main_return/Nargo.toml b/crates/nargo_cli/tests/test_data/main_return/Nargo.toml
index fb93b9aa2a7..c5df18dc4ad 100644
--- a/crates/nargo_cli/tests/test_data/main_return/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/main_return/Nargo.toml
@@ -1,6 +1,6 @@
 [package]
+name = "main_return"
 authors = [""]
 compiler_version = "0.1"
 
 [dependencies]
-    
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/main_return/target/main.json b/crates/nargo_cli/tests/test_data/main_return/target/main.json
index 384bca56c0f..fcd25a23f8f 100644
--- a/crates/nargo_cli/tests/test_data/main_return/target/main.json
+++ b/crates/nargo_cli/tests/test_data/main_return/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"public"}],"param_witnesses":{"x":[1]},"return_type":{"kind":"field"},"return_witnesses":[1]},"bytecode":"H4sIAAAAAAAA/2NiQABGJBqZDQACwnKXJAAAAA==","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"public"}],"param_witnesses":{"x":[1]},"return_type":{"kind":"field"},"return_witnesses":[1]},"bytecode":"H4sIAAAAAAAA/2NiwASMSDQyGwBkySDbLAAAAA==","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/merkle_insert/Nargo.toml b/crates/nargo_cli/tests/test_data/merkle_insert/Nargo.toml
index d9434868157..b1a7456b26e 100644
--- a/crates/nargo_cli/tests/test_data/merkle_insert/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/merkle_insert/Nargo.toml
@@ -1,7 +1,6 @@
+[package]
+name = "merkle_insert"
+authors = [""]
+compiler_version = "0.1"
 
-        [package]
-        authors = [""]
-        compiler_version = "0.1"
-    
-        [dependencies]
-    
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/merkle_insert/target/main.json b/crates/nargo_cli/tests/test_data/merkle_insert/target/main.json
index 3d9185d8a20..ba55f8ff17d 100644
--- a/crates/nargo_cli/tests/test_data/merkle_insert/target/main.json
+++ b/crates/nargo_cli/tests/test_data/merkle_insert/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"old_root","type":{"kind":"field"},"visibility":"private"},{"name":"old_leaf","type":{"kind":"field"},"visibility":"private"},{"name":"old_hash_path","type":{"kind":"array","length":3,"type":{"kind":"field"}},"visibility":"private"},{"name":"new_root","type":{"kind":"field"},"visibility":"public"},{"name":"leaf","type":{"kind":"field"},"visibility":"private"},{"name":"index","type":{"kind":"field"},"visibility":"private"},{"name":"mimc_input","type":{"kind":"array","length":4,"type":{"kind":"field"}},"visibility":"private"}],"param_witnesses":{"index":[8],"leaf":[7],"mimc_input":[9,10,11,12],"new_root":[6],"old_hash_path":[3,4,5],"old_leaf":[2],"old_root":[1]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"old_root","type":{"kind":"field"},"visibility":"private"},{"name":"old_leaf","type":{"kind":"field"},"visibility":"private"},{"name":"old_hash_path","type":{"kind":"array","length":3,"type":{"kind":"field"}},"visibility":"private"},{"name":"new_root","type":{"kind":"field"},"visibility":"public"},{"name":"leaf","type":{"kind":"field"},"visibility":"private"},{"name":"index","type":{"kind":"field"},"visibility":"private"},{"name":"mimc_input","type":{"kind":"array","length":4,"type":{"kind":"field"}},"visibility":"private"}],"param_witnesses":{"index":[8],"leaf":[7],"mimc_input":[9,10,11,12],"new_root":[6],"old_hash_path":[3,4,5],"old_leaf":[2],"old_root":[1]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/+29C9h11fQ+/Eg6n5AkIUlCMs+H5JQkSZIkSZpHSZIkSZIkSZIk5BSSJEkSQpIkISRJCCEJSQgh3xx9XP/9/D7X9/tfyxquMa+1Ht56n9797mfc477HPe+55tp7H7r20tJRay7d8XWX9muF9uvO/++3d/x7xX/+d/i10j+/h69V26/V2q/V2681/vn3Vlj6P193+ue/H/PPf7P/7IuvMt5zsX/hA9hrtV9r/7P2O/3z32v+8/f/+n6t//H92gv4lhZ6hYVXMqNUsaJwyQMTPjrNlI7Gcce101k4KYtTzvroLfNcycKr9rL+88nWHPG53rX6eDz8//VvaJ2l/r9fa433XHntEXnF6t8KI/UPQzPrjNi/XjDfdWTMY/sp9G6df/O8/ynu94ys77Fxg8+siYD7FOK++K867zZiL0fkmp9CXDcrIOnm/R3My10RcJ/aybzcfcRejsg1H7N/wC1k+3+tp+ARt7dfd//nv+Fr3fbrHkvLv8Zef9ca8bnWW+ojc4yJ+Z5LtDMH7B3XWhrfSz5I3ENhdtZDwH16Jx66/oi9HJFrfjpx3cC83BNBNx8mjhs8Yl0E3Gd2Mi/3GrGXI3LNz0TMHOARkDXutfR/MscG7de9l5Z/jb3+rj3ic2241EfmGBPzfZZoZw64br320vhe8lHiHgqzsyEC7rM78dD7jtjLEbnmZxPXDczLfRB083HiuMEjNkDAfW4n83K/EXs5Itf8XMTMAR4BWeN+S/8nc2zUft1/afnX2Gd7dxqRt41GfK6Nx8N4xxnr/zwjXVoaf27HrHmx3gcs/P5fZ94r/BtNrISAael//Jz/2ce1/s1/Ix3CNv5nQ8d+3k2WxhM/Fu5Nxudo2UJAuacwMCsg1opxU8gD269N268HLS2/KeSBS8tvAtn0f3z/oKW+bgp54IjP9clObgrZdLznyg8akddPdnJTyJia2Wxp3DWrB8wPXqK9TsO8PXBp/E3Qp4lv/lZuz7EZAu7zO9n8PWTEXo7INT+/g5sjHoygm891MC8YPnFBJ/Py0BF7OSLX/ALEiyXgEXCR5KFL/+diyebt18OWln+Nvf5uOuJzbbHUR+YYE/PDl2hnDri4sunS+F7yBeIeCrOzBQLuizrxUDZiL0fkml/UwU0hD0fQzZeI4waP2BwB9yWdzAsfsZcjcs0vQcwc0FDIGnzp/2QOAb1cWv419vr7oBGfSy31kTnGxKyXaGcOOOR+0NL4XvIV4h4Ks6MQcF/WiYeaEXs5Itf8sg5uCtEIuvk6cdzgEQIB9+WdzIsdsZcjcs0vR8wc4BGQNezS/8kcrv3yS8u/xj7bW2lE3tyIz7XleBj/azeFjFnzYr2PWPj9fFPIf/icW/6zoWM/71ZL44kfC/dW43OEelMI9Z7Cu5GsujT+Qv3IJdoBBTA/EgH3oyaK+9HEcQMvj0bA/ZgO+H4MAu7HLjyXKKLEGLl1wptoZHauJO5dZd6akL2LiWdVIste8Jxze7QzKdpiWfCu6J5wb00cN/CyNQLuxy1NU+fbEOcbeNkGAffjifONhXtb4riBl20RcD+BOG6s+d5uifZ8Ay/bIeB+4iJuHmviWkUdmeVZiMwMZ9oYqbV0jFenXeJVSM4EiyoJz4MVPhvheJbK94R7e+K4gZftEXA/aYn2fGPxvQNxvoGXHRBwP5k431i4dySOG3jZEQH3U4jjxprvnZZozzfwshMC7qcuPBcXJtUgtYisCMu4UiJKU1gSNTknnE01y1hLSu0ZRaiJFVmsy67kqEJ2PeHemThu4GVnBNxPW6I931h870Kcb+BlFwTcTyfONxbuXYnjBl52RcD9DOK4seZ7tyXa8w287IaA+5mLNUrms2XGhmh0Ljx4X4uQVWmXWUyycpe0j8YoUapyDbixvlRuUzReuNQT7t2J4wZedkfA/awl2vONxfcexPkGXvZAwP1s4nxj4d6TOG7gZU8E3M8hjhtrvvdaoj3fwMteCLjDwnNxr5IyXirmvTHesFic01ymWqTwLbZwoavl0rvQjhaKUt7KGht+ZduZAk5uwcIdieMGXiIC7rREe76x+M7E+QZeMgLuQpxvLNyVOG7gpSLgfi5x3FjzvfcS7fkGXvZGwP28xRp1cMobp2JqBwSJZVN8ldxHlUMRJkduuZXtyoNh7T9nb11RPDMfrA6mPa4n3PsQxw287IOA+/lLtOcbi+99ifMNvOyLgPsFxPnGwr0fcdzAy34IuF9IHDfWfO+/RHu+gZf9EXC/aOG5eAsfALFFFdUO+mMW1bOsONzLV6RkUYR2emBiUKGBTaGFlphT9VJoqSLOfXtYuA8gjht4OQAB94uXaM83Ft8HEucbeDkQAfdLiPONhfsg4riBl4MQcL+UOG6s+T54ifZ8Ay8HI+B+2WKNVppkWMrS18yN8lm59lyq+mBK8rFBdb5GkQsLMttSQixKtp8XtWG2hp5wH0IcN/ByCALuly/Rnm8svg8lzjfwcigC7lcQ5xsL92HEcQMvhyHgfiVx3FjzffgS7fkGXg5HwP2qhecS7fKBt+24P4vEM1xzsErCfXnVcOVF5DHLdrCgnUrMmmBNUjLJlHmwyuo73lutG9xHEMcNvByBgPvVS7TnG4vvI4nzDbwciYD7NcT5xsJ9FHHcwMtRCLhfSxw31nwfvUR7voGXoxFwv26xxiCllZnrGkxORQhenRTCJCba1YfqQgk61WRyUMlX5R0PObRmtNzCqjalJ9zHEMcNvByDgPv1S7TnG4vvY4nzDbwci4D7DcT5xsJ9HHHcwMtxCLjfSBw31nwfv0R7voGX4xFwv2nhuUS0jAlXRKyqMNZ+I0rOsSUXxdsBgpVJOJ9T+4E6ympUaR1qpwustMYkY0VPuE8gjht4OQEB95uXaM83Ft8nEucbeDkRAfdbiPONhfsk4riBl5MQcL+VOG6s+X7bEu35Bl7ehoD77Ys1RqFKVaZdR+ClZC9zlsZI1Y7/U1ClxGiVTy60yxNM2+QYz1q6ZBMzBu4G6An3ycRxAy8nI+B+xxLt+cbi+53E+QZe3omA+13E+cbC/W7iuIGXdyPgfg9x3FjzfcoS7fkGXk5BwP3exRp15u1IP2lr2m+S4yoawTU3UvpQeBCeJ5urNFHXbFJlURWZfMpCF8lwcgsW7vcRxw28vA8B9/uXaM83Ft+nEucbeDkVAfcHiPONhfs04riBl9MQcH+QOG6s+T59ifZ8Ay+nI+D+0MJzCctTjdW54q1S7Zm8KbaIbJzVLaW0trBiBOOK8dYdqYvXwbbzBelZTPqOt0zoBvcZxHEDL2cg4P7wEu35xuL7TOJ8Ay9nIuD+CHG+sXCfRRw38HIWAu6PEseNNd9nL9Geb+DlbATcH1t4Lu6NZL7yzG07JVA8RJ6KZ0l6axtcW6NNuSTrkrTOiehdaBHGeG0Sl7l0hfsc4riBl3MQcH98ifZ8Y/F9LnG+gZdzEXB/gjjfWLjPI44beDkPAfcniePGmu9PLdGeb+DlUwi4P72IW9jEOTftwoNOTCZbTXZScZtd4lE65qoXpXDjhQpaMa9ibf+wghdfVNU94T6fOG7g5XwE3J9Zoj3fWHx/ljjfwMtnEXB/jjjfWLgvII4beLkAAffniePGmu8Ll2jPN/ByIQLuLyzijrVax5Qtxdgs2wG/qjk1gNUHEQNrfZDK+ZCyNEroykMRd1yBEN4J0xfui4jjBl4uQsD9xSXa843F98XE+QZeLkbA/SXifGPhvoQ4buDlEgTcXyaOG2u+L12iPd/Ay6UIuL+yWKNpx/rJxhiK4bqmyp03VUSXo81epHZwkHgJPDkuVfE5mpq1c8aKpGXxoSfclxHHDbxchoD7q0u05xuL768R5xt4+RoC7q8T5xsL9+XEcQMvlyPg/gZx3Fjz/c0l2vMNvHwTAfe3lhavO+SWW1IM3OpSrcmxpuTbOYH2wsQovfLB2XZwoNtzCq1bmrHBqOjb8UJrlu4J9xXEcQMvVyDg/vYS7fnG4vtK4nwDL1ci4P4Ocb6xcF9FHDfwchUC7u8Sx40131cv0Z5v4OVqBNzfW3guEbNKOXkjiszBiBRl+6bapIQLPrKsuYv1jlv1THU1lYY6tP74UKNplyd6wn0NcdzAyzUIuL+/RHu+sfj+AXG+gZcfIOD+IXG+sXBfSxw38HItAu4fEceNNd8/XqI938DLjxFw/2QRtyq5HRcoW1sMKUollZL0TChTpGxP0P4gs/ZTJMssZRZVuzRha8w8hViLRvncVCzc1xHHDbxch4D7p0u05xuL758R5xt4+RkC7p8T5xsL9/XEcQMv1yPg/gVx3FjzfcMS7fkGXm5AwP3Lhedqlw+YaX8lCW14jNrKolJtJ/w+y8giK76EFJWyVvNkRLQ2wwvmCrz63Waue8J9I3HcwMuNCLh/tUR7vrH4/jVxvoGXXyPg/g1xvrFw30QcN/ByEwLu3xLHjTXfNy/Rnm/g5WYE3L9bxO0YnN9XlpWuvpQWSQKXOtYsvRS+SOWkLUZKbXSSXNXoW4aJPkcrXWtUT7hvIY4beLkFAffvl2jPNxbffyDON/DyBwTcfyTONxbuW4njBl5uRcD9J+K4seb7z0u05xt4+TMC7r8s4jai1nayrwSXrl150Nxw004KnIEXu0ceMi8uaqlDUhresqbGKETisvqkgy894b6NOG7g5TYE3H9doj3fWHz/jTjfwMvfEHD/nTjfWLhvJ44beLkdAfc/iOPGmm94wn89F8X5/sc/n3Rs3HdawM1sCytBtecyAT6dRaTghBGyJlZc9qHFF2+CssExLkvwCfKKdqn9lWi59j3hXoE4buBlBQTcd74T7fnG4ntF4nwDLysi4L4Lcb6xcK9EHDfwshIC7pUnOt+rEJ9v4GUVBNyrLuIOyocqWmLhPDIdMxPB+AY08hiyjoJbppgNOQjOlajMtCMDznwuzgUeTU+4VyOOG3hZDQH36sTnG4vvNYjzDbysgYB7TeJ8Y+Feizhu4GUtBNxrT3S+1yE+38DLOgi477p43UEkecfHq4UGN7UvaXw7LnBVhYaQWcsL17JWa72SOWidVE3OtMMG2xKMDD3hvhtx3MDL3RBw3534fGPxvS5xvoGXdRFw34M431i41yOOG3hZDwH3PSc63+sTn2/gZX0E3PdaxrfLpR0KGPg8tfaYduRvaira5XbhQRclaxah1OxMhI9tCe1koT1tu+7QHpNjcj3h3oA4buBlAwTc9yY+31h8b0icb+BlQwTc9yHONxbu+xLHDbzcFwH3/SY63xsRn2/gZSME3PdfxA35xLt2tM+y59pKFasUHt78nWlbazEtq7DqvLNFaW9jKTZLKVMWKjije8K9MXHcwMvGCLgfQHy+sfjehDjfwMsmCLgfSJxvLNybEscNvGyKgPtBE53vzYjPN/CyGQLuBy/gFopzAR9yLkyqyTDhahC1Zl+ZZ5EXDe9fw4Kz2XLupG4XI1qPsmqnCcq3Q4WecD+EOG7g5SEIuB9KfL6x+N6cON/Ay+YIuB9GnG8s3FsQxw28bIGA++ETnW9GfL6BF4aAmy/ynbVpOcU7UWWu0gVZua/RcZUk47Iq7mNgJTrFZBQ2sXY5wupkauGpKuN6wi2I4wZeBAJuSXy+sfhWxPkGXhQCbk2cbyzchjhu4MUg4LYTnW9HfL6BF4eA2y/g5pXxUh2zRiavq5ZJScXb83uZvbEylFJFSzCVh8C9t9lYG7W20Rsvigs94d6SOG7gZUsE3I8gPt9YfG9FnG/gZSsE3I8kzjcW7kcRxw28PAoB96MnOt+PIT7fd/CCgPuxi7iZTlq0EwLX8qGwxbDIpOGpPczqqIP1WeRknODZBS60y56ZklVrkC3tFKEn3FsTxw28bI2A+3HE5xuL722I8w28bIOA+/HE+cbCvS1x3MDLtgi4nzDR+d6O+HwDL9sh4H7iIt8ytyN/HViSIsUGODDvpfNJcMfatQUnnbA1Kt5OEkp2KjtnjclVqWQks74n3NsTxw28bI+A+0nE5xuL7x2I8w287ICA+8nE+cbCvSNx3MDLjgi4nzLR+d6J+HwDLzsh4H7qYm4RRhQrXTsyyNEkiCkqeyus8EoJnrLXoQahajvpZ4lLIUN0MsnATEhFip5w70wcN/CyMwLupxGfbyy+dyHON/CyCwLupxPnGwv3rsRxAy+7IuB+xkTnezfi8w287IaA+5mLfJdiXJJFusR9O9uX3qvEsso25gLv/95Qt38JEdqpgue6OpF0kJEpIWL2oSfcuxPHDbzsjoD7WcTnG4vvPYjzDbzsgYD72cT5xsK9J3HcwMueCLifM9H53ov4fAMveyHgDgu4RYFb6xtIwZJqpwdZVBaCL0ZxX60XJsSUtTeaOSW8CO3ROVvXThXaGYNnoifckThu4CUi4E7E5xuL70ycb+AlI+AuxPnGwl2J4wZeKgLu5050vvcmPt/Ay94IuJ+3eN0BYGfJswjS8Qa0sOCF4kkZIXwQouZ2jCBUew7Vrjmw0vqRWS1RO6NNqD3h3oc4buBlHwTczyc+31h870ucb+BlXwTcLyDONxbu/YjjBl72Q8D9wonO9/7E5xt42R8B94sW+Y5B+sp4gxmigc9VM4J7LawWNeWinLE22ypFO+q3pV2ZKCFV5bVKulSDc26AhfsA4riBlwMQcL+Y+Hxj8X0gcb6BlwMRcL+EON9YuA8ijht4OQgB90snOt8HE59v4OVgBNwvW7zu4FO7sMx0OzaAqwkNf8yJmciLlbXqFlGqlrl6U50yLdm4xLQVmfOaQnUu9oT7EOK4gZdDEHC/nPh8Y/F9KHG+gZdDEXC/gjjfWLgPI44beDkMAfcrJzrfhxOfb+DlcATcr1qWW4xgzPn211kwyVivaqo8icgjb7BlsFwmz3RwMfDafqKuVjNeCw+aRdcT7iOI4wZejkDA/Wri843F95HE+QZejkTA/RrifGPhPoo4buDlKATcr53ofB9NfL6Bl6MRcL9uMbfEZKRvINvfs5K3qw5ZJFOl51kp74r0IkWrS04x66QSq60BwuR2IcLAC+F7wn0McdzAyzEIuF9PfL6x+D6WON/Ay7EIuN9AnG8s3McRxw28HIeA+40Tne/jic838HI8Au43LeIOzlfpSntGluBuPS4saxcfjM3tP7aQwpVmMrdLDdbEKpNtSYbx3K5PyOCU0j3hPoE4buDlBATcbyY+31h8n0icb+DlRATcbyHONxbuk4jjBl5OQsD91onO99uIzzfw8jYE3G9fwM3bRYSSiy2lRFXglnrpGugakslCs6AV07r9YcicFeOjDKY9GbMmBWcdzvu+Y+E+mThu4OVkBNzvID7fWHy/kzjfwMs7EXC/izjfWLjfTRw38PJuBNzvmeh8n0J8voGXUxBwv3eR79QuIMCL4mKDJoJVknMdi5bCZ620y8I7JphrVySqzyEpbtrlB2E0rz4WEXvC/T7iuIGX9yHgfj/x+cbi+1TifAMvpyLg/gBxvrFwn0YcN/ByGgLuD050vk8nPt/Ay+kIuD+0eN3BSSaLyE6qwiGSFNmO+UO0wgRZrM6Z5ZB9rCXwoKQwlnvfHiaU9O0Zu8J9BnHcwMsZCLg/THy+sfg+kzjfwMuZCLg/QpxvLNxnEccNvJyFgPujE53vs4nPN/ByNgLujy3ijtoKx3kKDXjQnLN2gcG251apZGlEiaVmmzIv3LVwY40vXkndnrTUpIvuCfc5xHEDL+cg4P448fnG4vtc4nwDL+ci4P4Ecb6xcJ9HHDfwch4C7k9OdL4/RXy+gZdPIeD+9PJzA9FAa+t9LaIEJ5KxiQWXmTMytiODxEq7xNDO+wv3LcYoJto3zEUtq4mqJ9znE8cNvJyPgPszxOcbi+/PEucbePksAu7PEecbC/cFxHEDLxcg4P78ROf7QuLzDbxciID7C4t8K2aLVtGb0J5BJsN8DdJ6G4WQycosDAvS6JC1i0I7z4M2hgkrmDcx655wX0QcN/ByEQLuLxKfbyy+LybON/ByMQLuLxHnGwv3JcRxAy+XIOD+8kTn+1Li8w28XIqA+yuLuSXIdlFB68gaytzODJITQiTvrRIqJq5Yu9IgSo5VRRcaZpV80U6KmEMqnveE+zLiuIGXyxBwf5X4fGPx/TXifAMvX0PA/XXifGPhvpw4buDlcgTc35jofH+T+HwDL99EwP2txXMDb0RDrYvxLb9wm3S7rhCUj7yhDNl5zVX7lrWfUyzcah911to7xSMc++eecF9BHDfwcgUC7m8Tn28svq8kzjfwciUC7u8Q5xsL91XEcQMvVyHg/u5E5/tq4vMNvFyNgPt7i7nFKie1YxzeVE4LHVUS3GnZLkTo1gPlQlVGF/gMtlx85qY9Ht6dTsscrA+2J9zXEMcNvFyDgPv7xOcbi+8fEOcbePkBAu4fEucbC/e1xHEDL9ci4P7RROf7x8TnG3j5MQLunyzmlqxCLdkGy1zRvj2pU9kaI7yoIrV4knR2uj2L4cyqrH3IsmpevDQ+tMf3hPs64riBl+sQcP+U+Hxj8f0z4nwDLz9DwP1z4nxj4b6eOG7g5XoE3L+Y6HzfQHy+gZcbEHD/cjG3JFYia2mknQc4Y4qwPGXRAknlttp2VULVEOFsgTkXvS5W5tTOC7IXqT19MD3hvpE4buDlRgTcvyI+31h8/5o438DLrxFw/4Y431i4byKOG3i5CQH3byc63zcTn2/g5WYE3L9bzC3GsoamqCpksNk6EzJv/4xSyyCqi04I45ON2oVoWbZwXKC4aT9GqozzvrFYuG8hjht4uQUB9++JzzcW338gzjfw8gcE3H8kzjcW7luJ4wZebkXA/aeJzvefic838PJnBNx/WeRblRZaMoQSFjl37RBBcmZCEToxpWxIcHteTiYbkWqxtSSRrfcy13axQoiecN9GHDfwchsC7r8Sn28svv9GnG/g5W8IuP9OnG8s3LcTxw283I6A+x8Tne+lFWjPN/ACNY6N+06LuHOVUuocuKzthL8azbyu3urMtXXOCMVDSalW6Wr2MQYv2g+vzhufbWG+J9wrEMcNvKyAgPvOK9Cebyy+VyTON/CyIgLuuxDnGwv3SsRxAy8rIeBeeaLzvQrx+QZeVkHAveoKi+f+tVYjohdOlMR05DWolld8MC2ulFh8SEa2J5ZZRM6KUtEXVgv3pV12KKUn3KsRxw28rIaAe3Xi843F9xrE+QZe1kDAvSZxvrFwr0UcN/CyFgLutSc63+sQn2/gZR0E3Hdd5NuVVIRyDUlq/8/tFMF4H3U76LfJe9YuM1greAxR+2i0jZFLV9pzl2KMV7kn3Hcjjht4uRsC7rsTn28svtclzjfwsi4C7nsQ5xsL93rEcQMv6yHgvudE53t94vMNvKyPgPtei7kl8RAdz9EwG4M1OVbLa/u7WiSnTazcyXZ+4B1PMprMa5Y88hZrmHVVW94T7g2I4wZeNkDAfW/i843F94bE+QZeNkTAfR/ifGPhvi9x3MDLfRFw32+i870R8fkGXjZCwH3/Rb55Lqa6dkLQ/lek5rGqFEIWXsbsTGm/KdVI1y45cJ2ia6cKShTWHhZj+9b1hHtj4riBl40RcD+A+Hxj8b0Jcb6Bl00QcD+QON9YuDcljht42RQB94MmOt+bEZ9v4GUzBNwPXswtMmcXtTU1CGdkOyEwKhuZrK3ZiRoMz8Fyq6V0At5qzgnDbYlZqxBLVKYn3A8hjht4eQgC7ocSn28svjcnzjfwsjkC7ocR5xsL9xbEcQMvWyDgfvhE55sRn2/ghSHg5gu4ufHw/jRFcx1FKsXldqHB+3aVwXJhpWmPDrZ6UaNUSRZZtRS5tD+VIaSI87nnWLgFcdzAi0DALYnPNxbfijjfwItCwK2J842F2xDHDbwYBNx2ovPtiM838OIQcPtFvkuqrj2DdwXwBO9D6wFzWbTjA16DF0Uz7trpQnLeZ61VTjzXIHUqkQXWE+4tieMGXrZEwP0I4vONxfdWxPkGXrZCwP1I4nxj4X4UcdzAy6MQcD96ovP9GOLzfQcvCLgfu4g7J5ZNsSbUGKS1ORsvS1ZJ2aCqrwU+raWFmVx1rkbUzEwV1Vm4V6Dw5HrCvTVx3MDL1gi4H0d8vrH43oY438DLNgi4H0+cbyzc2xLHDbxsi4D7CROd7+2Izzfwsh0C7icuw+0yc9pyLX0yrkHP7dA/mHbULzzPUkiv2lUJG1p48cHGIkriKjsvmYvR5J5wb08cN/CyPQLuJxGfbyy+dyDON/CyAwLuJxPnGwv3jsRxAy87IuB+ykTneyfi8w287ISA+6kLuLnN3LJiJRztFw8feS5Vhbd0zzIJV50ulasoeLJSq/aXhXdwvGCNty3ZqJ5w70wcN/CyMwLupxGfbyy+dyHON/CyCwLupxPnGwv3rsRxAy+7IuB+xkTnezfi8w287IaA+5mLfPuSjWRZsXZ1Ad4lNkjVnl5znXiK0rh2DYLppHLJwuQqndEiC8+iMLVdq6g94d6dOG7gZXcE3M8iPt9YfO9BnG/gZQ8E3M8mzjcW7j2J4wZe9kTA/ZyJzvdexOcbeNkLAXdYwC2ilo57JTOcFciYmfZBWWWjFTVxbirzPinDWDvwd5znHJViFd62pj03Lz3hjsRxAy8RAXciPt9YfGfifAMvGQF3Ic43Fu5KHDfwUhFwP3ei87038fkGXvZGwP28Rb55bkmleGeLNzpBUElMaFG8zdHFGq0zxuWWYHxqB//JAmbWuhWzFlHGnnDvQxw38LIPAu7nE59vLL73Jc438LIvAu4XEOcbC/d+xHEDL/sh4H7hROd7f+LzDbzsj4D7RQu4eeAuOW8qFypl5QSvsTAXknGsYZZGJK6lUob7VCqzwllVlbQe7tWvQvaE+wDiuIGXAxBwv5j4fGPxfSBxvoGXAxFwv4Q431i4DyKOG3g5CAH3Syc63wcTn2/g5WAE3C9bxA2hJFRWQoHPRW0NMLGdHMSaFdwEwJNqP8RG+HAXb7iE2+29FaK0x+iGm/WE+xDiuIGXQxBwv5z4fGPxfShxvoGXQxFwv4I431i4DyOOG3g5DAH3Kyc634cTn2/g5XAE3K9axJ1r1s5aYUpSSmijS1S2tmsPsp0eMCNVNNqIzKNh3AuvLG9dccayEBTjqifcRxDHDbwcgYD71cTnG4vvI4nzDbwciYD7NcT5xsJ9FHHcwMtRCLhfO9H5Ppr4fAMvRyPgft0ibmWDZyqmzG2Q1ZgSs4W3oOPCes0s3HZhmHBKBKZsA14z5z5LXnKVXnSF+xjiuIGXYxBwv574fGPxfSxxvoGXYxFwv4E431i4jyOOG3g5DgH3Gyc638cTn2/g5XgE3G9axrcRnBtVXGzAlTW8PW8RIcTsAw/GlpSYrl6YWJKOMaQSrRbtHMGU9vdMT7hPII4beDkBAfebic83Ft8nEucbeDkRAfdbiPONhfsk4riBl5MQcL91ovP9NuLzDby8DQH32xdwC8dqSsXzBo1Fo+ADzWUxwUkXYky82nYdQhXltIxCZGZs0Kbq4plT7ezf94T7ZOK4gZeTEXC/g/h8Y/H9TuJ8Ay/vRMD9LuJ8Y+F+N3HcwMu7EXC/Z6LzfQrx+QZeTkHA/d5F3O18PzMZoolWceV1UdmmWBr+YFJllZlQgmtQhctcZm2rCaw9KjnjMos94X4fcdzAy/sQcL+f+Hxj8X0qcb6Bl1MRcH+AON9YuE8jjht4OQ0B9wcnOt+nE59v4OV0BNwfWsQdtI+mKM6cFtkbY9pJgue25RIeqnRVWRetYbJEWVQVsgUcb6TMTpiUi+8J9xnEcQMvZyDg/jDx+cbi+0zifAMvZyLg/ghxvrFwn0UcN/ByFgLuj050vs8mPt/Ay9kIuD+2gJsHa52swddqozS5XW6Ag4FidKrJNXAsWpbhfWui5iFqq3TRtfCcpM4+8p5wn0McN/ByDgLujxOfbyy+zyXON/ByLgLuTxDnGwv3ecRxAy/nIeD+5ETn+1PE5xt4+RQC7k8v5hZnMi+2MOlruOObmF0txhfe0KeQ2wG/l6kdIOj2Q5RTlnseQxG1SqWi6An3+cRxAy/nI+D+DPH5xuL7s8T5Bl4+i4D7c8T5xsJ9AXHcwMsFCLg/P9H5vpD4fAMvFyLg/sIi3zXAp5y3g4LCVXFJS9Ye6EOo7QKD87kd/sucmDC1lhRZO2SQ2cQGOLUfy6ztCfdFxHEDLxch4P4i8fnG4vti4nwDLxcj4P4Scb6xcF9CHDfwcgkC7i9PdL4vJT7fwMulCLi/soi7NAzaSF2Dbn+bOeFT+8tSJCUNjzXYkmuuikWmuUqM5SyDldK1n125lz3hvow4buDlMgTcXyU+31h8f40438DL1xBwf50431i4LyeOG3i5HAH3NyY6398kPt/AyzcRcH9r8bqDjKwEy6OLMcsUjYD794oWuurkotQp1tIO+RkkGSEV3OOnjNYpV8vbxYqecF9BHDfwcgUC7m8Tn28svq8kzjfwciUC7u8Q5xsL91XEcQMvVyHg/u5E5/tq4vMNvFyNgPt7i7hDKllbkWPNwhiljWeS1VSl54y3vy6q9Q17LLJdZuDKeVVjTbb9mNB6UHvCfQ1x3MDLNQi4v098vrH4/gFxvoGXHyDg/iFxvrFwX0scN/ByLQLuH010vn9MfL6Blx8j4P7JIt8yyTve6T1zkUMVSohaYuY6KC14le1ig/ZM2yRCrbn9CJOMrUG2SJNSizE94b6OOG7g5ToE3D8lPt9YfP+MON/Ay88QcP+cON9YuK8njht4uR4B9y8mOt83EJ9v4OUGBNy/XMDNbTbtOKBFFeHhs1GZb/B0OzywWoroWhsc3MRXTc4+w20AhskYnEnRC92K6An3jcRxAy83IuD+FfH5xuL718T5Bl5+jYD7N8T5xsJ9E3HcwMtNCLh/O9H5vpn4fAMvNyPg/t0i314zzWT7C4pLU1SyMqp2xSFExlysRuh2yp80D60bxdrqfTLMpGDb9Qojc1e4byGOG3i5BQH374nPNxbffyDON/DyBwTcfyTONxbuW4njBl5uRcD9p4nO95+Jzzfw8mcE3H9ZzC0sBdaODILXMXHvbAMjbTv0N4Y7oYwsLHlRAhciV6OcrjypooO3xkcpUk+4byOOG3i5DQH3X4nPNxbffyPON/DyNwTcfyfONxbu24njBl5uR8D9j4nO99Kdac838AI1jo37Tgu4ha9GJi91qUUIVYTUWUfVntNp6xq8KHTLMj5IJbIKLPsWZ7wr1Wqbo+E94V6BOG7gZQUE3He+M+35xuJ7ReJ8Ay8rIuC+C3G+sXCvRBw38LISAu6VJzrfqxCfb+BlFQTcqy7mlsKFa89Qam24JI/cuph8O+hPLCkeeLZC2nbwD+cEpmbmWWlH/kYaE9txgu4J92rEcQMvqyHgXp34fGPxvQZxvoGXNRBwr0mcbyzcaxHHDbyshYB77YnO9zrE5xt4WQcB97dWH5fvf33deWT8q474XKuN2L8r/kv9+0/rvOt4c81H1AzvpX93m0j/xvYt0N3dEHzr7nfuQzfrzroZVB/wuy6Cbu5BPN9g4V6POG7gZT0E3PfsxCfWn31iUH3A7/oIuvnOBHPxom7+4/df6STX3WvEuRtRM3yxf6KIEiPsQoU3sR0GO1fgXLiyduIbsm+bU55Vie1CsuA55/ZouBnbFstCu6ysMfu3wUT6N7Zvge42QPCte3ey3m0462ZQfcDvhgi6uQ/xfIiF+77EcQMv90XAfb9OfGKj2ScG1Qf8boSgm+91kuvuf2ccrtl/9sUX+yd4rIlrFXVklmchMjOcaWOk1tIxXp12icPnqzLBokrC82CFz0Y4nqXymP3beCL9G3vuQHcbI8zdAzrx601m3QyqD/jdBEE3DySeb7Bwb0ocN/CyKQLuB3XiE5vNPjGoPuB3MwTdfL+TXPdgorpZ7B8XJtUgtYisCMu4UiJKU1gSd3z8rrOpZhlrSakhFaEmVmSxLruSowrZYfbvIRPp39hzB7p7CMLcPbQTv9581s2g+oDfzRF08zDi+QYL9xbEcQMvWyDgfngnPsFmnxhUH/DLEHTzw05yHSeqm2X9k8xny4wN0ehcePC+FiGr0i6zmGTlLmkfjVGiVOWacIz1pXKbovHCJcz+iYn0b+y5A90JhLmTnfi1mnUzqD7gVyHoRhPPN1i4DXHcwItBwG078Qk3+8Sg+oBfh6CbH3WS6zxR3Sz2j3uVlPFSMe+N8YbF4pzmMtUihW/bAS50tVx6F9oRf1HKW1lj04+y7Wwf93rdlhPp39hzB7rbEmHuHtGJX28162ZQfcDvVgi6eSTxfIOF+1HEcQMvj0LA/ehOfOIxs08Mqu8OfhF085NOct1jiepmWf90cMobp2JqB/WJZVN8ldxHlUMRJkduuZXtSq9h7T9nb11RPDMfrA6mPQ6zf1tPpH9jzx3obmuEuXtcJ369zaybQfUBv9sg6ObxxPMNFu5tieMGXrZFwP2ETnxiu9knBtUH/G6HoJufdpLrnkhUN4v94y3Ug0TaFkBp2b4R1bOsOLwGp0jJogjtFN/EoEITSwptMxBzql4KLVXEfT3s9hPp39hzB7rbHmHuntSJX+8w62ZQfcDvDgi6eTLxfIOFe0fiuIGXHRFwP6UTn9hp9olB9QG/OyHo5ued5LqnEtXNsv5ZaZJhKUtfMzfKZ+UaRlV9MCX52KTifI0iFxZktqWEWJRsfYjaMFsDZv92nkj/xp470N3OCHP3tE78epdZN4PqA353QdDN04nnGyzcuxLHDbzsioD7GZ34xG6zTwyqD/jdDUE3v+gk1z2TqG4W+yfa5VpvefBZJJ7hGq9VEl5PUw1XXkQes2wH/NqpxKwJ1iQlk0yZB6us5gKzf7tPpH9jzx3obneEuXtWJ369x6ybQfUBv3sg6ObZxPMNFu49ieMGXvZEwP2cTnxir9knBtUH/O6FoJtfdpLrAlHdLOtfkNLKzHUNJqciBK9OCmESE+1qb3WhBJ1qMjmo5KvyjoccmpjafoBVbQpm/+JE+jf23IHuIsLcpU78Os+6GVQf8JsRdFOI5xss3JU4buClIuB+bic+sffsE4PqA373RtDNrzrJdc8jqpvF/oloGROuiFhVYaz9RpScY9sRKN4O8q1MwvmcWiN0lNWo0hTWTvlZacJKxqJer9tnIv0be+5Ad/sgzN3zO/HrfWfdDKoP+N0XQTcvIJ5vsHDvRxw38LIfAu4XduIT+88+Mag+4Hd/BN38ppNc9yKiulnWvyhUqcq067a8lOxlztIYqUT1KahSYrTKJxfa5WCmbXKMZy1dsokZA3drYvbvgIn0b+y5A90dgDB3L+7Erw+cdTOoPuD3QATdvIR4vsHCfRBx3MDLQQi4X9qJTxw8+8Sg+oDfgxF089tOct3LiOpmWf905oWFpK1pv0mOq2gE19xI6UPhQXiebK7SRF2zSZVFVWTyKQtdJMO9XnfIRPo39tyB7g5BmLuXd+LXh866GVQf8Hsogm5eQTzfYOE+jDhu4OUwBNyv7MQnDp99YlB9wO/hCLr5XSe57lVEdbPYP2F5qrE6V7xVqiH0ptgisnFWt/TfZMWKEYwrxpu6pC5eB9vO+aVnMbUjfMz+HTGR/o09d6C7IxDm7tWd+PWRs24G1Qf8Homgm9cQzzdYuI8ijht4OQoB92s78YmjZ58YVB/wezSCbn7fSa57HVHd/H7Z+1kbyXzlmdt2Wq94iDwVz5L01ja52BptyiVZl6R1TkTvQtsaGK9N4jIX1Fx3zET6N/bcge6OQZi713fi18fOuhlUH/B7LIJu3kA832DhPo44buDlOATcb+zEJ46ffWJQfcDv8Qi6+WMnue5NRHXzx2WfK2wT59y0C706MZlsNdlJxW12iUfpmKtelMKNFypoxbyKtf3DCl58URX1fYlPmEj/xp470N0JCHP35k78+sRZN4PqA35PRNDNW4jnGyzcJxHHDbychID7rZ34xNtmnxhUH/D7NgTd/KmTXPd2orpZ7B+PtVrHlC3F2Cxd00bNqQmk+iBiYE1HUjkfUpZGCV15KOKOK77CO2Fwc93JE+nf2HMHujsZYe7e0Ylfv3PWzaD6gN93IujmXcTzDRbudxPHDby8GwH3ezrxiVNmnxhUH/B7CoJu/tJJrnsvUd0s659JNicbYyiG65oqd95UEV2ONnuR2gF+4iXw5LhUxedoatbOGSuSlsUHzP69byL9G3vuQHfvQ5i793fi16fOuhlUH/B7KoJuPkA832DhPo04buDlNATcH+zEJ06ffWJQfcDv6Qi6+Wsnue5DRHXz12XXeXPbD6QYuNWlWpNjTcm383rthYlReuWDs+0AXzesQuu2S7DBqOjbMX8TG+r1ujMm0r+x5w50dwbC3H24E78+c9bNoPqA3zMRdPMR4vkGC/dZxHEDL2ch4P5oJz5x9uwTg+oDfs9G0M3fO8l1HyOqm78ve9/DrFJO3ogiczAiRdm+qTYp4YKPLGvuYr3jJTamuppKU01o+vKhRtMuB2P275yJ9G/suQPdnYMwdx/vxK/PnXUzqD7g91wE3XyCeL7Bwn0ecdzAy3kIuD/ZiU98avaJQfUBv59C0M0/Osl1nyaqm8X+CVVyO7ZXtrZ4X5RKKiXpmVCmSNmAtT/IrKGXLLOUWVTtUrCtMfMUYi3aYfbv/In0b+y5A92djzB3n+nErz8762ZQfcDvZxF08zni+QYL9wXEcQMvFyDg/nwnPnHh7BOD6gN+L0TQzZ3W6EM3XyCqm8X+tcu1zDQoSWjDY9RWFpWqEtpnGVlkxZeQolLWap6MiNZmeGOcAu9+aDNHPYe9aCL9G3vuQHcXIczdFzvx64tn3QyqD/i9GEE3XyKeb7BwX0IcN/ByCQLuL3fiE5fOPjGoPuD3UgTd3LmTXPcVorpZ7B93DO6vrCwrXX0pLeoHLnWsWXopfJHKSVuMlNroJLmq0be9QfQ5Wuma0DD7d9lE+jf23IHuLkOYu6924tdfm3UzqD7g92sIuvk68XyDhfty4riBl8sRcH+jE5/45uwTg+oDfr+JoJu7dJLrvkVUN4v940bUGpxVgkvXrvRqbrhpJ/bOwJsdRh4yLy5qqUNSGt7KusYoROKy+qSDL5j9u2Ii/Rt77kB3VyDM3bc78esrZ90Mqg/4vRJBN98hnm+wcF9FHDfwchUC7u924hNXzz4xqD7g92oE3azcSa77HlHdLOufbZuAoBpGE1KDK1JwwghZEysu+9C2Bd4EZYNjXJbgE+wDtEvtr0TLtcfs3zUT6d/Ycwe6uwZh7r7fiV//YNbNoPqA3x8g6OaHxPMNFu5rieMGXq5FwP2jTnzix7NPDKoP+P0xgm5W7STX/YSobpb1Lygfqmg7Ac4j0zEzEYxvQok8hqyj4JYpZkMOgnMlKjPt6J4zn4tzgUeD2b/rJtK/secOdHcdwtz9tBO//tmsm0H1Ab8/Q9DNz4nnGyzc1xPHDbxcj4D7F534xA2zTwyqD/i9AUE3q3eS635JVDeL/eMiSVXgrW6aXFL7ksa3Y3tXVWgKYdbywrWs1VqvZA5aJ1WTM+3Q37adgQyY/btxIv0be+5AdzcizN2vOvHrX8+6GVQf8PtrBN38hni+wcJ9E3HcwMtNCLh/24lP3Dz7xKD6gN+bEXSzZie57ndEdbO8fy6Xdjhvoiqy1S4bvpqKdrld6NVFyZpFKDU7E0Nqp/jthL/Bbdd522NyTKjvc3LLRPo39tyB7m5BmLvfd+LXf5h1M6g+4PcPCLr5I/F8g4X7VuK4gZdbEXD/qROf+PPsE4PqA37/jKCbtTvJdX8hqptl/YPc752LmmXPtZUqVik8fLgw07bWYtoegFXnnS1KextLsVlKmbJQwRnU9zm5bSL9G3vuQHe3IczdXzvx67/NuhlUH/D7NwTd/J14vsHCfTtx3MDL7Qi4/9GJTyytOPvEkPqAX+jd2Lq5aye57k5EdbPYP6E4F0ZKL0yqyTDhahC1Zl+ZZ5EXDe9rzYKz2XLupG4Xf5vGsmqn+sq3w33M/q0wkf6NPXeguxUQ5u7OK/YxdyvOuhlUH/C7IoJu7rIi7XyDhXsl4riBl5UQcK/ciU+sMvvEoPqA31UQdHP3TnLdqkR1s6x/WZuW/70TVeYqXZCV+xodV0kyLqviPgZWolNMRmETa5d/rU6mFp6qMqjnsKtNpH9jzx3objWEuVu9E79eY9bNoPqA3zUQdLMm8XyDhXst4riBl7UQcK/diU+sM/vEoPqA33UQdHOPTnLdXYnqZrF/vDJeqmPWyOR11TIpqXjD7WX2xspQShVtZ1B5CNx7m421UWsbvfGiuIDZv7tNpH9jzx3o7m4Y+6lO/HrdWTeD6gN+18Xwa+L5Bgv3esRxAy/rIeC+Zyc+sf7sE4PqA37Xx9BNJ7nuXkR1s9g/znTSop3UO8a1sMWwyKThqT3O6qiD9VnkZJzg2QUutMuemZJVE5gt7TQfs38bTKR/Y88d6G4DhLm7dyd+veGsm0H1Ab8bIujmPsTzDRbu+xLHDbzcFwH3/TrxiY1mnxhUH/C7EYJu7tVJrrs/Ud0s65/MUTMdWJIixSaYwLyXzifBHWvXcp10wtaoeDvRL9mp7Jw1JlelkpHMor4v8cYT6d/Ycwe62xhh7h7QiV9vMutmUH3A7yYIunkg8XyDhXtT4riBl00RcD+oE5/YbPaJQfUBv5thXDfoJNc9mKhu7r3s/XGMKFa6dnSfo0kQ/1X2VljhlRI8Za9DDUJVZRlLXAoZopNJBmZCKlJg9u8hE+nf2HMHunsIwtw9tBO/3nzWzaD6gN/NEXTzMOL5Bgv3FsRxAy9bIOB+eCc+wWafGFQf8Mswrut3kus4Ud0s618pxiVZpEvcKyal9yqxrLKNucDnCzfVtH8JEdrpvue6OpF0kJEpIWL2qPfXiYn0b+y5A90JhLmTnfi1mnUzqD7gVyHoRhPPN1i4DXHcwItBwG078Qk3+8Sg+oBfh3F+30mu80R1s9g/UeCl0k0kgiXVTvGzqCwEX4zivlovTIgpa280c0p4Edqjc7auDW876/cM9XrdlhPp39hzB7rbEmHuHtGJX28162ZQfcDvVgi6eSTxfIOF+1HEcQMvj0LA/ehOfOIxs08Mqu8OfhF0c/9Oct1jiepmsX93vANOljyLIB1vQikseKF4UkYIH4SouR3nC9WwqXaNl5Wmp8xqidoZbULF7N/WE+nf2HMHutsaYe4e14lfbzPrZlB9wO82CLp5PPF8g4V7W+K4gZdtEXA/oROf2G72iUH1Ab/bYdy/3UmueyJR3SzrXwzSV8abTEI0waZqBPdaWC1qykU5Y222VYrcTvBLuxJcQqrKa5V0qQb3/rrtJ9K/secOdLc9wtw9qRO/3mHWzaD6gN8dEHTzZOL5Bgv3jsRxAy87IuB+Sic+sdPsE4PqA353wnh9VSe57qlEdbPYP+ETY5HpdnwPV2+bfmJOzERerKxVt+hftczVm+qUaTsGl5i2InNeU6jORcz+7TyR/o09d6C7nRHm7mmd+PUus24G1Qf87oKgm6cTzzdYuHcljht42RUB9zM68YndZp8YVB/wuxvG66g7yXXPJKqbZf2LRjDmfIPFgknGelVT5UlEHnmTjQyWy+SZDi4GXlsndLWa8Vp40Cyift7E7hPp39hzB7rbHWHuntWJX+8x62ZQfcDvHgi6eTbxfIOFe0/iuIGXPRFwP6cTn9hr9olB9QG/eyHo5sGd5LpAVDeL/RMxGembSBoeK3m7yptFMlV6npXyrkgvUrS65BSzTiqx2gQkTG4Xfg28ESJm/+JE+jf23IHuIsLcpU78Os+6GVQf8JsRdFOI5xss3JU4buClIuB+bic+sffsE4PqA373RtDNQzvJdc8jqpvF/ongfJWuNKQswatsuLCsXew1Nrf/2MI/V5rJ3C7tWhOrTLbtEBjP7XqwDE4pjdm/fSbSv7HnDnS3D8LcPb8Tv9531s2g+oDffRF08wLi+QYL937EcQMv+yHgfmEnPrH/7BOD6gN+90fQzcM6yXUvIqqbxf7xdtG25GJLKVEVeIm0dE00NSSThWZBK6Z1+8OQOSvGRxlMA8msScFZZ1DPYQ+YSP/GnjvQ3QEIc/fiTvz6wFk3g+oDfg9E0M1LiOcbLNwHEccNvByEgPulnfjEwbNPDKoP+D0YQTcP7yTXvYyobpb1L7ULtvDmN7FJQwSrJOc6Fi2Fz1ppl4V3TDDXrgBXn0NS3LTLvcJoXn0sImL275CJ9G/suQPdHYIwdy/vxK8PnXUzqD7g91AE3byCeL7Bwn0YcdzAy2EIuF/ZiU8cPvvEoPqA38MRdMM7yXWvIqqbxf41DEwWkZ1UhUPUL1ImH6IVJshidc4sh+xjLYEHJYWx3Pv2MKGkb0hRc90RE+nf2HMHujsCYe5e3YlfHznrZlB9wO+RCLp5DfF8g4X7KOK4gZejEHC/thOfOHr2iUH1Ab9HI+hGdpLrXkdUN3LZfZnaCsd5Ck04QXPO2gVd2zCrVLI0osRSs02ZF+7apsEaX7ySuoEtNemCen/dMRPp39hzB7o7BmHuXt+JXx8762ZQfcDvsQi6eQPxfIOF+zjiuIGX4xBwv7ETnzh+9olB9QG/xyPoRneS695EVDd6+fm9aKLR1vtaRAlOJGMTCy4zZ2RsR/eJlXZJ17ZdA/dte6CYaN8wF7WsJirM/p0wkf6NPXeguxMQ5u7Nnfj1ibNuBtUH/J6IoJu3EM83WLhPIo4beDkJAfdbO/GJt80+Mag+4PdtCLqxneS6txPVzbL+KWaLVtGb0JDJZJivQVpvoxAyWZmFYUEaHbJ2UWjnedDGMGEF8yZm1Ot1J0+kf2PPHejuZIS5e0cnfv3OWTeD6gN+34mgm3cRzzdYuN9NHDfw8m4E3O/pxCdOmX1iUH3A7ykIuvGd5Lr3EtXNYv94kO0irtaRNZXkdnafnBAieW+VUDFxxdqVXVFyrCq60DSjki/aSRFzSMVzzP69byL9G3vuQHfvQ5i793fi16fOuhlUH/B7KoJuPkA832DhPo04buDlNATcH+zEJ06ffWJQfcDv6Qi6eUQnue5DRHXziGWfU2JEU40uxrd9AbdJt+u4QfnIm0pCdl5z1b5lDX+x8NLpqLPW3ike4bbMjNm/MybSv7HnDnR3BsLcfbgTvz5z1s2g+oDfMxF08xHi+QYL91nEcQMvZyHg/mgnPnH27BOD6gN+z0bQzSM7yXUfI6qbRy47v1dOasc4fAiJFjqqJLjTsl341U1DyoWqjC6+Wp+Lz9y0x8OnmWiZg/XBYvbvnIn0b+y5A92dgzB3H+/Er8+ddTOoPuD3XATdfIJ4vsHCfR5x3MDLeQi4P9mJT3xq9olB9QG/n0LQzaM7yXWfJqqbxf6JrEIt2QbLXNG+gXUqW2OEF1WkFvuTzk43dIYzq7L2IcuqefHS+NAej9m/8yfSv7HnDnR3PsLcfaYTv/7srJtB9QG/n0XQzeeI5xss3BcQxw28XICA+/Od+MSFs08Mqg/4vRBBN4/tJNd9gahuFvvHEyuRtZTfzuWdMUVYnrJoQb9yW227CqxqiHDGz5yLXhcrc2rn9tmL1GAHg9m/iybSv7HnDnR3EcLcfbETv7541s2g+oDfixF08yXi+QYL9yXEcQMvlyDg/nInPnHp7BOD6gN+L0XQzeM6yXVfIaqbxf4JY1lTQ1FVyGCzdSZk3v4ZpZZBVBedEMYnG7UL0bJs4dhecdPgS5VxPx/2son0b+y5A91dhjB3X+3Er78262ZQfcDv1xB083Xi+QYL9+XEcQMvlyPg/kYnPvHN2ScG1Qf8fhNBN4/vJNd9i6hulvVPlbYZyBD2WeTctcN8yZkJRejElLIhwctqcjLZiFSLrSWJbL2XubaLw0Jg9u+KifRv7LkD3V2BMHff7sSvr5x1M6g+4PdKBN18h3i+wcJ9FXHcwMtVCLi/24lPXD37xKD6gN+rEXTzhE5y3feI6mZZ/3KVUuocuKxVmWo087p6qzPX1jkjFA8lpVqlq9nHGLxoTanOG59tYR6zf9dMpH9jzx3o7hqEuft+J379g1k3g+oDfn+AoJsfEs83WLivJY4beLkWAfePOvGJH88+Mag+4PfHCLp5Yie57idEdfPEZfdl1lqNiF44URLTkdeg2j7AB9O2ASUWH5KRDbDMInJWlIq+sFq4L+0ybymY/btuIv0be+5Ad9chzN1PO/Hrn826GVQf8PszBN38nHi+wcJ9PXHcwMv1CLh/0YlP3DD7xKD6gN8bEHTzpE5y3S+J6mZZ/1xJRSjXlJDa/3M7zTfeR50ys8l71i7rWit4DFH7aLSNkUtXGuZSjPEqY/bvxon0b+y5A93diDB3v+rEr38962ZQfcDvrxF08xvi+QYL903EcQMvNyHg/m0nPnHz7BOD6gN+b0bQzZM7yXW/I6qbxf6JxEN0PEfDbAzW5Fgtrw2TFslpEyt3sp3je8eTjCbzmiWPvG0XmHVVW9TPm7hlIv0be+5Ad7cgzN3vO/HrP8y6GVQf8PsHBN38kXi+wcJ9K3HcwMutCLj/1IlP/Hn2iUH1Ab9/RtDNUzrJdX8hqptl/eO5mOraSX37X5Gax6pSCFl4GbMzpf2mVCNdu8TLdYqune4rUVh7WIztW4fZv9sm0r+x5w50dxvC3P21E7/+26ybQfUBv39D0M3fiecbLNy3E8cNvNyOgPsfnfjE0l1mnxhSH/ALvRtbN0/tJNfdiahuFvsnZM4uamtqEM7IdlJvVDYyWVuzEzUYnoPlVkvpBHw0iROG2xKzViGWqFDfv26FifRv7LkD3a2AMHd3vksfc7firJtB9QG/KyLo5i53oZ1vsHCvRBw38LISAu6VO/GJVWafGFQf8LsKgm6e1kmuW5Wobhb7x42H960umusoUikutwu73rerupYLK017eLDVixqlSrLIqqXIpf2pDCG1TQFm/1abSP/GnjvQ3WoIc7d6J369xqybQfUBv2sg6GZN4vkGC/daxHEDL2sh4F67E59YZ/aJQfUBv+sg6ObpneS6uxLVzbL+lVRdQ+ZdAT0E70PTEHNZtGN8XoMXRTPu2il/ct5nrVVOPNcgdSqRBdT+3W0i/Rt77kB3d0OYu7t34tfrzroZVB/wuy6Cbu5BPN9g4V6POG7gZT0E3PfsxCfWn31iUH3A7/oIunlGJ7nuXkR1s6x/ObFsijWhxiCtzdl4WbJKygZVfS3FBtc2CbnqXI2omZkqqrNwL2fhCfX+ug0m0r+x5w50twHC3N27E7/ecNbNoPqA3w0RdHMf4vkGC/d9ieMGXu6LgPt+nfjERrNPDKoP+N0IQTfP7CTX3Z+obpb1L7vMnLZcS5+Ma9LJIYtgTDup9zxLIb1qV4FtaJsCH2wsoiSusvOSuRhNxuzfxhPp39hzB7rbGGHuHtCJX28y62ZQfcDvJgi6eSDxfIOFe1PiuIGXTRFwP6gTn9hs9olB9QG/myHo5lmd5LoHE9XNYv+4zdyyYiXcelm8EMlLVeEjg7NMwlWnS+UqCp6s1Kr9beEdHPNb423bMSjM/j1kIv0be+5Adw9BmLuHduLXm8+6GVQf8Ls5gm4eRjzfYOHegjhu4GULBNwP78Qn2OwTg+oDfhmCbp7dSa7jRHWzrH++ZCNZVqxdzYVPmwtSNdia68RTlMa1a75MJ5VLFiZX6YwWWXgWhant2nDF7J+YSP/GnjvQnUCYO9mJX6tZN4PqA34Vgm408XyDhdsQxw28GATcthOfcLNPDKoP+HUIunlOJ7nOE9XNYv9E1NJxr2SGM3sZM9M+KKtstKImzk1l3idl2mqZk+M856gUq/B21g0zL5j923Ii/Rt77kB3WyLM3SM68eutZt0Mqg/43QpBN48knm+wcD+KOG7g5VEIuB/diU88ZvaJQfXdwS+CbkInue6xRHUTlr/vYdsBFO9s8UYn2AAkJrQo3uboYo3WGeNy2xn4lKtJFjTDmtpi1iLKiNm/rSfSv7HnDnS3NcLcPa4Tv95m1s2g+oDfbRB083ji+QYL97bEcQMv2yLgfkInPrHd7BOD6gN+t0PQTeok1z2RqG4W+8cDd8l5U7lQKSsneI2FuZCMY00z0ojEtVTKcJ9KZVY4q6qS1sNrr6uQmP3bfiL9G3vuQHfbI8zdkzrx6x1m3QyqD/jdAUE3Tyaeb7Bw70gcN/CyIwLup3TiEzvNPjGoPuB3JwTdlE5y3VOJ6qYse9/DFvZDZSUUkWrbE1QT2wl+rFnBTZo8qQbexlqr8YZLePm0t0KU9hjddIPav50n0r+x5w50tzPC3D2tE7/eZdbNoPqA310QdPN04vkGC/euxHEDL7si4H5GJz6x2+wTg+oDfndD0M1zO8l1zySqm8X+8VyzdtYKU5JSQhtdorK1XeuV7RSfGami0UZkHg3jXnhleVOVM5aFoBhHfT3s7hPp39hzB7rbHeN16J349R6zbgbVB/zugfE6N+L5Bgv3nsRxAy97Ytz/3olP7DX7xKD6gN+9EHTzvE5yXSCqm8X+cWWDZyqmzG2Q1ZgSs4WPLOHCes0sbB8ME06JwJRtwqmZc58lL7lKL1BzXZxI/8aeO9BdxLj/oRO/zrNuBtUH/GaM8xXi+QYLdyWOG3ipGNddOvGJvWefGFQf8Ls3gm6e30muex5R3SzvnxGcG1VcbMJR1vCGt4gQYvaBB2NLSkxXL0wsSccYUolWi3aeb0r7ewazf/tMpH9jzx3obh+MuevEr/eddTOsvta3fRF08wLi+QYL937EcQMv+yHgfmEnPrH/7BOD6gN+98fwiU5y3YuI6maxf8KxmlLxvEmDRdPAlCKLCU66EGPi1bbrvqoop2UUIjNjgzZVF8+c8g03Zv8OmEj/xp470N0BCHP34k78+sBZN4PqA34PRNDNS4jnGyzcBxHHDbwchID7pZ34xMGzTwyqD/g9GGM/0EmuexlR3Sz2T2TlM5MhmmgVV14XlW2KpeknmFRZZSaU4JpUhMtcZm2rCaw9KjnjMouY/TtkIv0be+5Ad4cgzN3LO/HrQ2fdDKoP+D0UQTevIJ5vsHAfRhw38HIYAu5XduITh88+Mag+4PdwBN28qJNc9yqiulnsnwjaR1MUZ06L7I0x7UTfc9vyPg9Vuqqsi9YwWaIsqgrZNg7eSJmdMCkX1Ot1R0ykf2PPHejuCIS5e3Unfn3krJtB9QG/RyLo5jXE8w0W7qOI4wZejkLA/dpOfOLo2ScG1Qf8Ho1xHtRJrnsdUd28eNn741jrZA2+Vhulye3yLhzQF6NTTa6Jg0XLMryfddQ8RG2VLroWnpPU2UeO2b9jJtK/secOdHcMwty9vhO/PnbWzaD6gN9jEXTzBuL5Bgv3ccRxAy/HIeB+Yyc+cfzsE4PqA36Px7hfo5Nc9yaiunnJsvN7k3mxhUlfwx3fxOxqMb7wpp4UsuHGy9QO8nUDr5yy3PMYiqhVKhUFZv9OmEj/xp470N0JCHP35k78+sRZN4PqA35PRNDNW4jnGyzcJxHHDbychID7rZ34xNtmnxhUH/D7Noz7MjvJdW8nqptl/auhXeLN7cC+cFVc0pI1AD6E2i7oOp9DjDInJkytJUXWDvtlNrEJJrV2MGsx+3fyRPo39tyB7k5GmLt3dOLX75x1M6g+4PedCLp5F/F8g4X73cRxAy/vRsD9nk584pTZJwbVB/yegqCbl3WS695LVDfL+leaBrSRugbdUDEnfGqgpEhKGh5rsCXXXBWLTHOVGMtZBiulaz2p3KN+jtj7JtK/secOdPc+hLl7fyd+feqsm0H1Ab+nIujmA8TzDRbu04jjBl5OQ8D9wU584vTZJwbVB/yejvG6vE5y3YeI6maxf0JGVoLl0cWYZYpGwOtuiha66uSi1CnWkp1gsEMQUsFrc5TROuVqebs4jNm/MybSv7HnDnR3BsLcfbgTvz5z1s2g+oDfMxF08xHi+QYL91nEcQMvZyHg/mgnPnH27BOD6gN+z8Z43Xwnue5jRHXzimWvt0klaytyrFkYo7TxTLKaqvSc8QZLVOubdmKR7bIuV86rGmuyDX5oGqqY/TtnIv0be+5Ad+cgzN3HO/Hrc2fdDKoP+D0XQTefIJ5vsHCfRxw38HIeAu5PduITn5p9YlB9wO+nEHTzyk5y3aeJ6mZZ/2SSd3yScOYihyqUELXEzHVQWvAq28Vd7Zm2SYRac4NukrE1yLZVSKltDzD7d/5E+jf23IHuzkeYu8904tefnXUzqD7g97MIuvkc8XyDhfsC4riBlwsQcH++E5+4cPaJQfUBvxci6OZVneS6LxDVzWL/uM2mHcu3LYDw0vjEfJOHbof4VksRXZORgxffVJOzz3CbpmEyBmdS9EK35mD276KJ9G/suQPdXYQwd1/sxK8vnnUzqD7g92IE3XyJeL7Bwn0JcdzAyyUIuL/ciU9cOvvEoPqA30sRdPPqTnLdV4jqZln/vGaayQZEcWmKSlZG1a7whsiYi9UIHaxMmoempmJt9T4ZZlKw7fqwkRk11102kf6NPXegu8sQ5u6rnfj112bdDKoP+P0agm6+TjzfYOG+nDhu4OVyBNzf6MQnvjn7xKD6gN9vIujmNZ3kum8R1c1i/zhLgbWj++B1TNw728Qgra7aGO6EMrKw5EUJXIhcjXK68qSKDt4aH6VImP27YiL9G3vuQHdXIMzdtzvx6ytn3QyqD/i9EkE33yGeb7BwX0UcN/ByFQLu73biE1fPPjGoPuD3agTdvLaTXPc9orpZ7J/w1cjkpS61CKGKkDrrqBpWp61r8ohCtz2CD1KJrALLvm0TvCvVapujQf28iWsm0r+x5w50dw3C3H2/E7/+waybQfUBvz9A0M0PiecbLNzXEscNvFyLgPtHnfjEj2efGFQf8PtjBN28rpNc9xOiulnsHy9cuIas1Np0IXnk1sXktU2JJcUDz1ZIy7SF83pTM/OsRJmMNCa2Y32N2b/rJtK/secOdHcdwtz9tBO//tmsm0H1Ab8/Q9DNz4nnGyzc1xPHDbxcj4D7F534xA2zTwyqD/i9AUE3r/8v5Tr2n32JVUfs5Woj9u/YPvrHVx+Ri2+tPl7/3tBJ/0acE76omf/4czM72Zf9ckTfH1EzvJf+3TiR/o29boLubkRYN3/VSd769aybQfUBv79G0M1viO9PsHDfRBw38HITAu7fduITN88+Mag+4PdmBN28uZN92bdG3IO/fsRcfGIn+4oR94/8zSP27y2d5OLfjehbI2qGL/ZPFFFihKtIwptoZHauwH1glXlrQvbt4hLPqsR2QCh4zrk9Gl6saYtloR0Xop733DKR/o3t+6C7WxB8//ed5IU/zLoZVB/w+wcE3fyReL7Gwn0rcdzAy60IuP/UiU/8efaJQfUBv39G0M3bJ5iL3z5iLj65k1z8F6Jzt9g/wWNNXKuoI7M8C5GZ4UwbI7WWjvHqtEu8CsmZYFEl4XmwwmcjHM9SoX7e020T6d/YvgW6uw3Bt/7ayXr3t1k3g+oDfv+GoJu/E8+HWLhvJ44beLkdAfc/OvGJpZVmnxhSH/ALvRtbN++aYC5+14i5+N2d5OI7EZ27xf5xYVINUovIirCMKyWiNIUlUZNzwtlUs4y1pNSQilATK7JYl13JUYXsMPu3wkT6N7Zvge5WQPCtO6/Ux9ytOOtmUH3A74oIurnLyLrpBfdKxHEDLysh4F65E59YZfaJQfUBv6sg6Oa9E8zF7x0xF7+vk1y8KtG5W9Y/yXy2zNgQjc6FB+9rEbIq7TKLSVbukvbRGCVKVa4NnrG+VG5TNF441Pe5W20i/Rvbt0B3qyH41uqdrHdrzLoZVB/wuwaCbtYkng+xcK9FHDfwshYC7rU78Yl1Zp8YVB/wuw6Cbj4wwVz8gRFz8Wmd5OK7Ep27xf5xr5IyXirmvTHesFic01ymWqTwbTvKha6WS++CdaIo5a2ssc2fst5F3OvFd5tI/8b2LdDd3RB86+6drHfrzroZVB/wuy6Cbu5BPB9i4V6POG7gZT0E3PfsxCfWn31iUH3A7/oIuvnQBHPxh0bMxWd0kovvRXTulvVPB6e8cSom7VJi2RRfJfdR5VCEyZFbbmU7qTGs/efsrSuKZ+aD1cG0x2H2b4OJ9G9s3wLdbYDgW/fuZL3bcNbNoPqA3w0RdHMf4vkQC/d9ieMGXu6LgPt+nfjERrNPDKoP+N0IQTcfmWAu/siIufisTnLx/YnO3WL/eNtUwoi1LajSsn0jqmdZcXgNbJGSRRGccCYGFdqwpdA2ozGn6qXQUkXc96PYeCL9G9u3QHcbI/jWAzpZ7zaZdTOoPuB3EwTdPJB4PsTCvSlx3MDLpgi4H9SJT2w2+8Sg+oDfzRB087EJ5uKPjZiLz+kkFz+Y6Nwt65+VJhmWsvQ1c6N8Vq5hVNUHU5KPbdScr1HkwoLMtpQQi5KtD1EbZmvA7N9DJtK/sX0LdPcQBN96aCfr3eazbgbVB/xujqCbhxHPh1i4tyCOG3jZAgH3wzvxCTb7xKD6gF+GoJtPTDAXf2LEXHxeJ7mYE527xf6JdtziLQ8+i8QznNFYJeH1rNVw5UXkMcukjHYqMWuCNUnJJFPmwSqrucDsn5hI/8b2LdCdQPAt2cl6p2bdDKoP+FUIutHE8yEWbkMcN/BiEHDbTnzCzT4xqD7g1yHo5tMTzMWfHjEXn99JLvZE525Z/4KUVmauazA5FSF4dVIIk5hopzXVhRJ0qsnkoJKvyjsecmjD2PajrGpTMPu35UT6N7Zvge62RPCtR3Sy3m0162ZQfcDvVgi6eSTxfIiF+1HEcQMvj0LA/ehOfOIxs08Mqu8OfhF087kJ5uLPjZiLL+gkFz+W6Nwt9k9E2y7MuiJiVaVtodvklZxj25Eq7lm2Mgnnc2qN0FFWo0qbUBczK20wk7Go14u3nkj/xvYt0N3WCL71uE7Wu21m3QyqD/jdBkE3jyeeD7Fwb0scN/CyLQLuJ3TiE9vNPjGoPuB3OwTdfGGCufgLI+biizrJxU8kOnfL+heFKlWZdu7CS8le5iyNkUpUn4IqJUarfHKhHecwbZNjPGvpkk3MGLjbH7N/20+kf2P7FuhuewTfelIn690Os24G1Qf87oCgmycTz4dYuHckjht42REB91M68YmdZp8YVB/wuxOCbr40wVz8pRFz8SWd5OKnEp27Zf3TmRcWkram/SY5rqIRXHMjpQ+FB+F5srlKE3XNJlUWVZHJpyx0kQz3evHOE+nf2L4FutsZwbee1sl6t8usm0H1Ab+7IOjm6cTzIRbuXYnjBl52RcD9jE58YrfZJwbVB/zuhqCbr0wwF39lxFx8WSe5+JlE526xf8LyVGN1rnirVEPoTbFFZOOsbrvPNpasGMG4YrxNp9TF62BTEdKzmDSrmP3bfSL9G9u3QHe7I/jWszpZ7/aYdTOoPuB3DwTdPJt4PsTCvSdx3MDLngi4n9OJT+w1+8Sg+oDfvRB08/UJ5uKvj5iLL+8kFweic3f5ss/TMZL5yjO3LFvFQ+SpeJakt7aNm63RplySdUla50T0LrStqfHaJC5zQc3FcSL9G9u3QHcRwbdSJ+tdnnUzqD7gNyPophDPh1i4K3HcwEtFwP3cTnxi79knBtUH/O6NoJtvTTAXf2vEXHxFJ7n4eUTnbrF/XNjEOTftoEYnJpOtJjupuM0u8Sgdc9WLUrjxQgWtmFextn9YwYsvqqJ+rsc+E+nf2L4FutsHwbee38l6t++sm0H1Ab/7IujmBcTzIRbu/YjjBl72Q8D9wk58Yv/ZJwbVB/zuj6Cb70wwF39nxFx8VSe5+EVE526xfzzWah1TthRjs3RttmpObcCqDyIG1uZQKudDytIooSsPRdxxYiO8EwY3Fx8wkf6N7VuguwMQfOvFnax3B866GVQf8Hsggm5eQjwfYuE+iDhu4OUgBNwv7cQnDp59YlB9wO/BCLr53gRz8fdGzMXXdJKLX0Z07pb1zySbk40xFMN1TZU7b6qILkebvUhM58RL4MlxqYrP0dSsnTNWJC2LD5j9O2Qi/Rvbt0B3hyD41ss7We8OnXUzqD7g91AE3byCeD7Ewn0YcdzAy2EIuF/ZiU8cPvvEoPqA38MRdPPDCebiH46Yi6/tJBe/iujcXbvsnCa3/WiKgVtdqjU51pR8sk57YWKUXvngbElWN6xC67ZLtcGo6HkqbVhRrxcfMZH+je1boLsjEHzr1Z2sd0fOuhlUH/B7JIJuXkM8H2LhPoo4buDlKATcr+3EJ46efWJQfcDv0Qi6+ckEc/FPRszF13WSi19HdO6uW/a+4VmlnLwRReZgRIqyfVNtUsIFH1nW3MV6x0tcTXU1lTZ1oc2nDzWadpyD2b9jJtK/sX0LdHcMgm+9vpP17thZN4PqA36PRdDNG4jnQyzcxxHHDbwch4D7jZ34xPGzTwyqD/g9HkE3P59gLv75iLn4+k5y8ZuIzt1i/4QqOUunbG3by6JUUilJz4QyRcoGrP1BZg29ZJmlzKJqRzm2xsxTiLVoh9m/EybSv7F9C3R3AoJvvbmT9e7EWTeD6gN+T0TQzVuI50Ms3CcRxw28nISA+62d+MTbZp8YVB/w+zYE3fxygrn4lyPm4hs7ycVvJzp3i/1rxy3MNChJaMNj1FYWlaoS2mcZWWTFl5CiUtZqnoyI1mZ4Y8QC7x5uM0e9j+LkifRvbN8C3Z2M4Fvv6GS9e+esm0H1Ab/vRNDNu4jnQyzc7yaOG3h5NwLu93TiE6fMPjGoPuD3FATd/GaCufg3I+bimzrJxe8lOneL/eOOwf35lWWlqy+lbTUDlzrWLL0UvkjlpC1GSm10klzV6NveNPocrXRtUDH7976J9G9s3wLdvQ/Bt97fyXp36qybQfUBv6ci6OYDxPMhFu7TiOMGXk5DwP3BTnzi9NknBtUH/J6OoJvfTTAX/27EXHxLJ7n4Q0TnbrF/3Ihag7NKcOnaSY3mhhsXqzPwZuGRh8yLi1rqkJSGj9KpMQqRuKw+6eALZv/OmEj/xvYt0N0ZCL714U7WuzNn3QyqD/g9E0E3HyGeD7Fwn0UcN/ByFgLuj3biE2fPPjGoPuD3bATd/HGCufiPI+biWzvJxR8jOnfL+mfbJjSohtGE1OCKFJwwQtbEiss+tG2pN0HZ4BiXJfgE+1DtUvsr0XLtMft3zkT6N7Zvge7OQfCtj3ey3p0762ZQfcDvuQi6+QTxfIiF+zziuIGX8xBwf7ITn/jU7BOD6gN+P4Wgm79MMBf/ZcRcfFsnufjTROduWf+C8qGKthPlPDIdMxPB+DZokceQdRTcMsVsyEFwrkRlpqjCmc/FucCjwezf+RPp39i+Bbo7H8G3PtPJevfZWTeD6gN+P4ugm88Rz4dYuC8gjht4uQAB9+c78YkLZ58YVB/weyGCbv4+wVz89xFz8e2d5OIvEJ2725e9P2KSqsBbHbZxS+1LGi98cVWFNmHMWl64lrVa65XMQeukanKGaWnbzlQGzP5dNJH+je1boLuLEHzri52sdxfPuhlUH/B7MYJuvkQ8H2LhvoQ4buDlEgTcX+7EJy6dfWJQfcDvpQi6udOa08vFi5j/0/6tsGYfc/cVonO3vH8uF92OaKIqstUuG76aina5HdToomTNIpSanYkhSR1i0Q1uO6dpj8kxob5P22UT6d/YvgW6uwzBt77ayXr3tVk3g+oDfr+GoJuvE8+HWLgvJ44beLkcAfc3OvGJb84+Mag+4PebCLq5ywRz8V1GzMUrdZKLv0V07pb1D/ad3rmoWfZcW6lilcKb7CTTttZi2h6UVeedLUp7G0uxWUqZslDBGdT3abtiIv0b27dAd1cg+Na3O1nvrpx1M6g+4PdKBN18h3g+xMJ9FXHcwMtVCLi/24lPXD37xKD6gN+rEXSz6gRz8aoj5uLVOsnF3yM6d4v9E4pzYaT0wqSaDBOuBlFr9pV5FnnR8Lk6LDibLedO6nZ402Y0K8uU8oJbzP5dM5H+je1boLtrEHzr+52sdz+YdTOoPuD3Bwi6+SHxfIiF+1riuIGXaxFw/6gTn/jx7BOD6gN+f4ygmzUnmIvXHDEXr9VJLv4J0blb1r+sTdt/eieqzFW6ICv3NTqukmRcVsV9DKxEp5iMwibWjm+sTqYWnqoyqPdRXDeR/o3tW6C76xB866edrHc/m3UzqD7g92cIuvk58XyIhft64riBl+sRcP+iE5+4YfaJQfUBvzcg6OauE8zFdx0xF9+tk1z8S6Jzt9g/Xhkv1TFrZPK6apmUVLzh9jJ7Y2UopYq2M608BO69zcbaqLWN3nhRXMDs340T6d/YvgW6uxHBt37VyXr361k3g+oDfn+NoJvfEM+HWLhvIo4beLkJAfdvO/GJm2efGFQf8Hszgm7uMcFcfI8Rc/F6neTi3xGdu8X+caaTFtq20eNa2GJYZNLw1B5nddTB+ixyMk7w7AIX2mXPTMmqDagtNqJ+rsctE+nf2L4FursFwbd+38l694dZN4PqA37/gKCbPxLPh1i4byWOG3i5FQH3nzrxiT/PPjGoPuD3zwi6udcEc/G9RszFG3SSi/9CdO6W9U/mqJkOLEmRYhu4wLyXzifBHWtnMU46YWtUPPtaslPZOWtMrkolI5lF/VyP2ybSv7F9C3R3G4Jv/bWT9e5vs24G1Qf8/g1BN38nng+xcN9OHDfwcjsC7n904hNLK88+MaQ+4Bd6N7Zu7jPBXHyfEXPxfTvJxXciOneL/ePCiGKlq9LlaBJsP1X2VljhlRI8Za9DDUJVZRlLXAoZopNJBmZCKlJg9m+FifRvbN8C3a2A4Ft3XrmPuVtx1s2g+oDfFRF0c5eRddML7pWI4wZeVkLAvXInPrHK7BOD6gN+V0HQzf0nmIvvP2Iu3riTXLwq0blb1r9SjEuySJe4V0xK71ViWWUbc5E61jZ17V9CBK+r57o6kXSQkSkhYvao9xevNpH+je1boLvVEHxr9U7WuzVm3QyqD/hdA0E3axLPh1i41yKOG3hZCwH32p34xDqzTwyqD/hdB0E3D5xgLn7giLl4005y8V2Jzt1i/0SBt3ppQyZYUra6LCoLwRejuK/WCxNiytobzZwSXoT26JytY8zaYjxDvV58t4n0b2zfAt3dDcG37t7JerfurJtB9QG/6yLo5h7E8yEW7vWI4wZe1kPAfc9OfGL92ScG1Qf8ro+gmwdPMBc/eMRc/JBOcvG9iM7dYv/ueAfELHkWQTreBq2w4IXiSRkhfBCiZi+dUA2bamc0rLR5zKyWqJ3RJlTM/m0wkf6N7Vuguw0QfOvenax3G866GVQf8Lshxn2DxPMhFu77EscNvNwXAff9OvGJjWafGFQf8LsRgm4eNsFc/LARc/EWneTi+xOdu2X9i0H6yngbsxBNsKkawb0WVouaclHOWJttlSJXZUs7ySkhVeW1SrpUg3t/8cYT6d/YvgW62xjBtx7QyXq3yaybQfUBv5tgnI8Sz4dYuDcljht42RQB94M68YnNZp8YVB/wuxmCbvgEczEfMReLTnLxg4nO3WL/hE+MRaZd4nD60uYv5sRM5MXKWnXbelYtc/WmOmXajtUlpq3InNcUqnMRs38PmUj/xvYt0N1DEHzroZ2sd5vPuhlUH/C7OcZ1IOL5EAv3FsRxAy9bIOB+eCc+wWafGFQf8MsQdKMnmIv1iLnYdJKLOdG5W9a/aARjzjdYLJhkrFc1VZ5E5JG3sZPBcpk808HFwGvrhK5WM14LD5pF1M+7ExPp39i+BboTCL4lO1nv1KybQfUBvwpjvSOeD7FwG+K4gReDgNt24hNu9olB9QG/DkE3foK52I+Yi7fsJBd7onO32D8Rk5G+DVnDYyVvpzRZJFOl51kp74r0IkWrS04x66QSq20Ahcnt4MbAG4lj9m/LifRvbN8C3W2J4FuP6GS922rWzaD6gN+tEHTzSOL5EAv3o4jjBl4ehYD70Z34xGNmnxhU3x38YvjEBHPxI0fMxY/qJBc/lujcLfZPBOerdKUhZQle5cqFZe2wxtjc/mPbfHKlmcztaMaaWGWybYfKeG7nOTI4pTRm/7aeSP/G9i3Q3dYIvvW4Tta7bWbdDKoP+N0GQTePJ54PsXBvSxw38LItAu4ndOIT280+Mag+4Hc7BN08doK5+LEj5uKtO8nFTyQ6d4v94+3QpeRiSylRFXiLF+na0NWQTBaaBa2Y1u0PQ+asGB9lMA0ksyYFZ51BvY9i+4n0b2zfAt1tj+BbT+pkvdth1s2g+oDfHRB082Ti+RAL947EcQMvOyLgfkonPrHT7BOD6gN+d8LYP08wFz9+xFy8bSe5+KlE525Z/1I7cIE3P4xttESwSnKuY9FS+KyVdll4xwRz7QSn+hyS4qYd1wijefWxiIjZv50n0r+xfQt0tzOCbz2tk/Vul1k3g+oDfndB0M3TiedDLNy7EscNvOyKgPsZnfjEbrNPDKoP+N0NQTdPnGAufuKIuXj7TnLxM4nO3WL/GgYmi8hOqsJhq1mkTD5EK0yQxeqcWQ7Zx1oCD0oKY7n37WFCSd+Qoubi3SfSv7F9C3S3O4JvPauT9W6PWTeD6gN+90DQzbOJ50Ms3HsSxw287ImA+zmd+MRes08Mqg/43QvjXGmCufjJI+biHTvJxYHo3O247L5+bYXjPIU2eEFzztqBjG2YVSpZGlFiqdmmzAt3bdNqjS9eSd3Alpp0Qb2/OE6kf2P7FuguIvhW6mS9y7NuBtUH/GYE3RTi+RALdyWOG3ipCLif24lP7D37xKD6gN+9EXTz1Anm4qeOmIt37iQXP4/o3O28/P4l0YZOW+9rESU4kYxNLLjMnJFRl5JYaUcytu1auW/bU8VE+4a5qGU1UWH2b5+J9G9s3wLd7YPgW8/vZL3bd9bNoPqA330RdPMC4vkQC/d+xHEDL/sh4H5hJz6x/+wTg+oDfvfHuN9qgrn46SPm4l07ycUvIjp3y/qnmC1aRW9CQyaTYb4Gab2NQshkZRaGBWl0yNpFoZ3nQRvDhBXMm5hRrxcfMJH+je1boLsDEHzrxZ2sdwfOuhlUH/B7IIJuXkI8H2LhPog4buDlIATcL+3EJw6efWJQfcDvwQi6eeYEc/EzR8zFu3eSi19GdO4W+8eDbIcwWkfWpixLmZITQiTvrRIqJq5YO5kRJceqogtt5lTyRTspYg6peI7Zv0Mm0r+xfQt0dwiCb728k/Xu0Fk3g+oDfg9F0M0riOdDLNyHEccNvByGgPuVnfjE4bNPDKoP+D0c43UIE8zFzx4xF+/ZSS5+FdG523PZ50wa0aZOF+PbvpTbpNs5TFA+8jZlITuvuWrfsoa/WHjrl6iz1t4pHuG2/ozZvyMm0r+xfQt0dwSCb726k/XuyFk3g+oDfo9E0M1riOdDLNxHEccNvByFgPu1nfjE0bNPDKoP+D0aQTdhgrk4jJiLYye5+HVE5y4uu39JOaldI4hXroWOKgnutGwHN7rNoHKhKqOLr9bn4jM37fHwaZRa5mB9sJj9O2Yi/Rvbt0B3xyD41us7We+OnXUzqD7g91gE3byBeD7Ewn0ccdzAy3EIuN/YiU8cP/vEoPqA3+MxXp87wVxcRszFtZNc/Caic7fYP5FVqCXbYJkr2jewTmVrjPCiitS2nUlnpxs6w5lVWfuQZdW8eGl8aI/H7N8JE+nf2L4FujsBwbfe3Ml6d+Ksm0H1Ab8nIujmLcTzIRbuk4jjBl5OQsD91k584m2zTwyqD/h9G4JunjfBXPy8EXPxPp3k4rcTnbvF/vHESmRtl6mSd8YUYXnKom00K7fVtlMcVUOEe5yYc9HrYmVOqW1MvUgNdjCY/Tt5Iv0b27dAdycj+NY7Olnv3jnrZlB9wO87EXTzLuL5EAv3u4njBl7ejYD7PZ34xCmzTwyqD/g9BeN9ayaYi18wYi7er5Nc/F6ic7fYP2Esa9NUVBUy2GydCZm3f0apZRDVRSeE8clG7UK0LFu4bUlx0+BLlRXq+1G8byL9G9u3QHfvQ/Ct93ey3p0662ZQfcDvqQi6+QDxfIiF+zTiuIGX0xBwf7ATnzh99olB9QG/pyPo5kUTzMUvGjEXH9BJLv4Q0blb1j9V2mY0w2aTRc6da/PGmQlF6MSUsiHBy1pzMtmIVIutJYlsvZe5tsMdITD7d8ZE+je2b4HuzkDwrQ93st6dOetmUH3A75kIuvkI8XyIhfss4riBl7MQcH+0E584e/aJQfUBv2cj6OYlE8zFLxkxFx/USS7+GNG5W9a/XKWUOgcua1WmGs28rt7qzLV1zgjFQ0mpVulq9jEGL1pTqvPGZ1uYx+zfORPp39i+Bbo7B8G3Pt7JenfurJtB9QG/5yLo5hPE8yEW7vOI4wZezkPA/clOfOJTs08Mqg/4/RSCbl42wVz8shFz8SGd5OJPE527Q5bd119rNSJ64URJTEdeg2r7UB9M24aWWHxIRjbAMovIWVEq+sJq4b60Y5pSMPt3/kT6N7Zvge7OR/Ctz3Sy3n121s2g+oDfzyLo5nPE8yEW7guI4wZeLkDA/flOfOLC2ScG1Qf8Xoigm1dMMBe/YsRcfFgnufgLROduWf9cSUUo1yYptf9ny7TxPuqUmU3es3YsY63gMUTto9E2Ri5daZhLMcYr1Pcvvmgi/Rvbt0B3FyH41hc7We8unnUzqD7g92IE3XyJeD7Ewn0JcdzAyyUIuL/ciU9cOvvEoPqA30sRdPOqCebiV42Yi4/oJBd/hejcLfZPJB6i4zkaZmOwJsdqeW2YtEhOm1i5k0wp73iS0WRes+SRt+0qs65qi/p5d5dNpH9j+xbo7jIE3/pqJ+vd12bdDKoP+P0agm6+TjwfYuG+nDhu4OVyBNzf6MQnvjn7xKD6gN9vIujmNRPMxa8ZMRcf1Uku/hbRuVvWP56Lqc450/5XpOaxqhRCFl7G7ExpvynVSNeOaLhO0TGvlSisPSzG9q3D7N8VE+nf2L4FursCwbe+3cl6d+Wsm0H1Ab9XIujmO8TzIRbuq4jjBl6uQsD93U584urZJwbVB/xejaCb100wF79uxFx8TCe5+HtE526xf0Lm7KK2pgbhjJTcGZWNTNbW7EQNhudgudVSOgEfLemE4bbErFWIJSrU9y++ZiL9G9u3QHfXIPjW9ztZ734w62ZQfcDvDxB080Pi+RAL97XEcQMv1yLg/lEnPvHj2ScG1Qf8/hhBN2+YYC5+w4i5+LhOcvFPiM7dYv+48fC5OUVzHUUqxeV2MON9O5WxXFhp2sODrV7UKFWSRVYtRS7tT2UIqW1KMft33UT6N7Zvge6uQ/Ctn3ay3v1s1s2g+oDfnyHo5ufE8yEW7uuJ4wZerkfA/YtOfOKG2ScG1Qf83oCgmzdNMBe/acRcfEInufiXROduWf9Kqq4h867APAXvQ5tB5rKwvPIavCiacZd4SM77rLXKiecapE4lsoDavxsn0r+xfQt0dyOCb/2qk/Xu17NuBtUH/P4aQTe/IZ4PsXDfRBw38HITAu7fduITN88+Mag+4PdmBN28ZYK5+C0j5uKTOsnFvyM6d8v6lxPLplgTagzS2pyNlyWrpGxQ1ddSbHBtk5qrztWImpmpojoLrwUoPKHeX3zLRPo3tm+B7m5B8K3fd7Le/WHWzaD6gN8/IOjmj8TzIRbuW4njBl5uRcD9p0584s+zTwyqD/j9M4Ju3j7BXPz2EXPxyZ3k4r8Qnbtl/csuM6ct19In49ro5ZBFMEY64XmWQnrVTnFsaJtSH2wsoiSusvOSuRgN6vu03TaR/o3tW6C72xB866+drHd/m3UzqD7g928Iuvk78XyIhft24riBl9sRcP+jE59YWmX2iSH1Ab/Qu7F1864J5uJ3jZiL391JLr4T0blb7B+3mVtWrIRb94sXInmpakMUskzCVadL5SoKnqzUqv1t4R3c5mSNt23HqjD7t8JE+je2b4HuVkDwrTuv0sfcrTjrZlB9wO+KCLq5y8i66QX3SsRxAy8rIeBeuROfWGX2iUH1Ab+rIOjmvRPMxe8dMRe/r5NcvCrRuVvWP1+ykSwr1k5j4NPWg1QNtuY68RSlce3MhumkcsnC5Cqd0SILz6IwtZ3tVMz+rTaR/o3tW6C71RB8a/VO1rs1Zt0Mqg/4XQNBN2sSz4dYuNcijht4WQsB99qd+MQ6s08Mqg/4XQdBNx+YYC7+wIi5+LROcvFdic7dYv9E1NJxr2SGe5ZkzEz7oKyy0YqaODeVeZ+UYUzl5DjPOSrFKnycTsPMUT8H+m4T6d/YvgW6uxuCb929k/Vu3Vk3g+oDftdF0M09iOdDLNzrEccNvKyHgPuenfjE+rNPDKoP+F0fQTcfmmAu/tCIufiMTnLxvYjO3RnL3ze87UCLd7Z4oxNsQBMTWhRvc3SxRuuMcbntTH3K1SQLM8fatMasRZQRs38bTKR/Y/sW6G4DBN+6dyfr3YazbgbVB/xuiKCb+xDPh1i470scN/ByXwTc9+vEJzaafWJQfcDvRgi6+cgEc/FHRszFZ3WSi+9PdO4W+8cDd8l5U7lQKSsneI2FuZCMY23mpBGJa6mU4T6VyqxwVlUlrYf3jqlCYvZv44n0b2zfAt1tjOBbD+hkvdtk1s2g+oDfTRB080Di+RAL96bEcQMvmyLgflAnPrHZ7BOD6gN+N0PQzccmmIs/NmIuPqeTXPxgonN3zrL3DW+bzVBZCUWk2vak1USpWKxZwU3+PKkG3sZaq/GGS3j7F2+FKO0xus0dav8eMpH+je1boLuHIPjWQztZ7zafdTOoPuB3cwTdPIx4PsTCvQVx3MDLFgi4H96JT7DZJwbVB/wyBN18YoK5+BMj5uLzOsnFnOjcLfaP55q1s1aYkpQS2ugSla3trEYqq5iRKhptRObRMO6FV5a3qXTGshAU46jvRyEm0r+xfQt0JxB8S3ay3qlZN4PqA34Vgm408XyIhdsQxw28GATcthOfcLNPDKoP+HUIuvn0BHPxp0fMxed3kos90blb7B9XNnimYsrcBlmNKTFb+MhJLqzXzLaHF8OEUyIwZdvg1cy5z5KXXKUXqLl4y4n0b2zfAt1tieBbj+hkvdtq1s2g+oDfrRB080ji+RAL96OI4wZeHoWA+9Gd+MRjZp8YVN8d/CLo5nMTzMWfGzEXX9BJLn4s0blb3j8jODequNgGT1nDG94iQojZBx6MLSkxXb0wsSQdY0glWi2U4aa0v2cw+7f1RPo3tm+B7rZG8K3HdbLebTPrZlB9wO82CLp5PPF8iIV7W+K4gZdtEXA/oROf2G72iUH1Ab/bIejmCxPMxV8YMRdf1EkufiLRuVvsn3CsplQ8b6PFomlgSpHFBCddiDHxatu5jSrKaRmFyMzYoE3VxTOnfMON2b/tJ9K/sX0LdLc9gm89qZP1bodZN4PqA353QNDNk4nnQyzcOxLHDbzsiID7KZ34xE6zTwyqD/jdCUE3X5pgLv7SiLn4kk5y8VOJzt1i/0RWPjMZoolWceV1UdmmWNr8BZMqq8yEElwbNeEyl1nbagJrj0rOuMwiZv92nkj/xvYt0N3OCL71tE7Wu11m3QyqD/jdBUE3TyeeD7Fw70ocN/CyKwLuZ3TiE7vNPjGoPuB3NwTdfGWCufgrI+biyzrJxc8kOneL/RNB+2iK4sxpkb0xhivruW37TR6qdFVZF61hskRZVBWybVy9kTI7YVIuqNeLd59I/8b2LdDd7gi+9axO1rs9Zt0Mqg/43QNBN88mng+xcO9JHDfwsicC7ud04hN7zT4xqD7gdy8E3Xx9grn46yPm4ss7ycWB6Nxdvuz9Ea11sgZfq43S5HY8AzcoFaNTTa4NF4uWZfg8nah5iNoqXXQtPCeps48cs39xIv0b27dAdxHBt1In612edTOoPuA3I+imEM+HWLgrcdzAS0XA/dxOfGLv2ScG1Qf87o2gm29NMBd/a8RcfEUnufh5ROfuimX3L5nMiy1M+hru+CZmV4vxhbfpSyEbbrxMqQFr4JVTlnseQxG1SqWiwOzfPhPp39i+BbrbB8G3nt/JerfvrJtB9QG/+yLo5gXE8yEW7v2I4wZe9kPA/cJOfGL/2ScG1Qf87o+gm+9MMBd/Z8RcfFUnufhFROduWf9qaEc0ORZXuCouackaAB9CbQcyzucQo8yJCVNrSZEpn2U2sQ1cau1g1mL274CJ9G9s3wLdHYDgWy/uZL07cNbNoPqA3wMRdPMS4vkQC/dBxHEDLwch4H5pJz5x8OwTg+oDfg9G0M33JpiLvzdiLr6mk1z8MqJzt6x/pc2QNlLXoBsq5oRPDZQUSUnDYw225JqrYpFprlI7pM4yWCld60nlHvVzoA+ZSP/G9i3Q3SEIvvXyTta7Q2fdDKoP+D0UQTevIJ4PsXAfRhw38HIYAu5XduITh88+Mag+4PdwBN38cIK5+Icj5uJrO8nFryI6d4v9EzKyEiyPLsYsUzQCXvdatNBVJxelTrGW7ASDHaqQCl4bq4zWKVfL2+EOZv+OmEj/xvYt0N0RCL716k7WuyNn3QyqD/g9EkE3ryGeD7FwH0UcN/ByFALu13biE0fPPjGoPuD3aATd/GSCufgnI+bi6zrJxa8jOnfXLXu9aypZW5FjzcIYpY1nktVUpeeMN1iiWt9mLxbZjmW4cl7VWJNt8EObwYrZv2Mm0r+xfQt0dwyCb72+k/Xu2Fk3g+oDfo9F0M0biOdDLNzHEccNvByHgPuNnfjE8bNPDKoP+D0eQTc/n2Au/vmIufj6TnLxm4jO3bL+ySRNlIplLnKoQglRS8xcB6UFr7IdzmjPtE0i1JobdJOMrUG2rWpKbXuK2b8TJtK/sX0LdHcCgm+9uZP17sRZN4PqA35PRNDNW4jnQyzcJxHHDbychID7rZ34xNtmnxhUH/D7NgTd/HKCufiXI+biGzvJxW8nOneL/eM2G5VgCyq8ND4x38ZLC5+sliK6NoYOXvxaTc4+w23+hskYnEnRC92ag9m/kyfSv7F9C3R3MoJvvaOT9e6ds24G1Qf8vhNBN+8ing+xcL+bOG7g5d0IuN/TiU+cMvvEoPqA31MQdPObCebi34yYi2/qJBe/l+jcLeuf10wz2YAoLk1Rycqo2glNiIy5WI3QwcqkeWjTWKyt3ifDTAq2ne8YmVFz8fsm0r+xfQt09z4E33p/J+vdqbNuBtUH/J6KoJsPEM+HWLhPI44beDkNAfcHO/GJ02efGFQf8Hs6gm5+N8Fc/LsRc/EtneTiDxGdu8X+cZYCq1kEr2Pi3tk2TNLqqo3hTigjC0telMCFyNUopytPqujgrfFRioTZvzMm0r+xfQt0dwaCb324k/XuzFk3g+oDfs9E0M1HiOdDLNxnEccNvJyFgPujnfjE2bNPDKoP+D0bQTd/nGAu/uOIufjWTnLxx4jO3WL/hK9GJi91qUUIVYTUWUfVsDptXRuvKHTbo/oglcgqsOzbNtW7Uq22ORrUz7s7ZyL9G9u3QHfnIPjWxztZ786ddTOoPuD3XATdfIJ4PsTCfR5x3MDLeQi4P9mJT3xq9olB9QG/n0LQzV8mmIv/MmIuvq2TXPxponO32D9euHANWam1zZXkkVsXk9c2JZYUDzxbIS3TFu5XMjUzz0qUyUhjoi9VY/bv/In0b2zfAt2dj+Bbn+lkvfvsrJtB9QG/n0XQzeeI50Ms3BcQxw28XICA+/Od+MSFs08Mqg/4vRBBN3/vJBevPuJzrTFi/27vo39izH3F30fcV/yjk/6N6TW3j9i/pbX68P0vjOj7I2qG99K/iybSv7HXTdDdRQjr5hc7yVsXz7oZVB/wezGCbr5EfH+ChfsS4riBl0sQcH+5E5+4dPaJQfUBv5ci6OYu/6Vcwv6zrzH3Zepbq4/Xv5X66J94PdF92cqd9G/Mfe3izP2n/Vulk/kdcU74yiP2b9VO9mVfGXHdHFEzfLF/oogSI1zFFN5EI7NzBe6DrcxbE7JvFzd5ViW2A37Bc87t0fBmCbZYFtpxP+p542UT6d/YuQN0dxlC7vhqJ3n1a7NuBtUH/H4NQTdfJ76/w8J9OXHcwMvlCLi/0YlPfHP2iUH1Ab/fRNDN2hPcV6w9Yi5ep5Nc/K1VcGaF/WdffLF/gseauFZRR2Z5FiIzw5k2RmotHePVaZd4FZIzwaJKwvNghc9GOJ6lQv281Csm0r+xfQt0dwWCb327k/Xuylk3g+oDfq9E0M13iOdDLNxXEccNvFyFgPu7nfjE1bNPDKoP+L0aQTd3n2AuvvuIuXjdTnLx94jO3WL/uDCpBqlFZEVYxpUSUZrCkqjJOeFsqlnGWlJqSEWoiRVZrMuu5KhCdpj9u2Yi/Rvbt0B31yD41vc7We9+MOtmUH3A7w8QdPND4vkQC/e1xHEDL9ci4P5RJz7x49knBtUH/P4YQTf3nGAuvueIuXj9TnLxT4jO3bL+SeazZcaGaHQuPHhfi5BVaZdZTLJyl7SPxihRqnJt8Iz1pXKbovHCob7P53UT6d/YvgW6uw7Bt37ayXr3s1k3g+oDfn+GoJufE8+HWLivJ44beLkeAfcvOvGJG2afGFQf8HsDgm7uPcFcfO8Rc/GGneTiXxKdu8X+ca+SMl4q5r0x3rBYnNNcplqk8G07yoWulkvvgnWiKOWtrLHNn7LeRdzrxTdOpH9j+xbo7kYE3/pVJ+vdr2fdDKoP+P01gm5+QzwfYuG+iThu4OUmBNy/7cQnbp59YlB9wO/NCLq53wRz8f1GzMUbdZKLf0d07pb1TwenvHEqJu1SYtkUXyX3UeVQhMmRW25lO6kxrP3n7K0rimfmg9XBtMdh9u+WifRvbN8C3d2C4Fu/72S9+8Osm0H1Ab9/QNDNH4nnQyzctxLHDbzcioD7T534xJ9nnxhUH/D7ZwTdPGCCufgBI+biTTrJxX8hOneL/eNtUwkj1ragSsv2jaieZcXhNbBFShZFcMKZGFRow5ZC24zGnKqXQksVcd+P4raJ9G9s3wLd3YbgW3/tZL3726ybQfUBv39D0M3fiedDLNy3E8cNvNyOgPsfnfjE0qqzTwypD/iF3o2tmwdNMBc/aMRcvFknufhOROduWf+sNMmwlKWvmRvls3INo6o+mJJ8bKPmfI0iFxZktqWEWJRsfYjaMFsDZv9WmEj/xvYt0N0KCL5151X7mLsVZ90Mqg/4XRFBN3cZWTe94F6JOG7gZSUE3Ct34hOrzD4xqD7gdxUE3Tx0grn4oSPm4s07ycWrEp27xf6JdtziLQ8+i8QznNFYJeH1rNVw5UXkMcukjHYqMWuCNUnJJFPmwSqrucDs32oT6d/YvgW6Ww3Bt1bvZL1bY9bNoPqA3zUQdLMm8XyIhXst4riBl7UQcK/diU+sM/vEoPqA33UQdPPwCebih4+Yi1knufiuROduWf+ClFZmrmswORUheHVSCJOYaKc11YUSdKrJ5KCSr8o7HnJow9j2o6xqUzD7d7eJ9G9s3wLd3Q3Bt+7eyXq37qybQfUBv+si6OYexPMhFu71iOMGXtZDwH3PTnxi/dknBtUH/K6PoBs5wVwsR8zFqpNcfC+ic7fYPxFtY9oVEasqjLXfiJJzbDtSxT3LVibhfE6tETrKalRpE+piZqUNZjIW9XrxBhPp39i+BbrbAMG37t3JerfhrJtB9QG/GyLo5j7E8yEW7vsSxw283BcB9/068YmNZp8YVB/wuxGCbuwEc7EdMRe7TnLx/YnO3bL+RaFKVaadu/BSspc5S2OkEtWnoEqJ0SqfXGjHOUzb5BjPWrpkEzMG7vbH7N/GE+nf2L4FutsYwbce0Ml6t8msm0H1Ab+bIOjmgcTzIRbuTYnjBl42xXj9VCc+sdnsE4PqA343Q9DNIyaYix8xYi7eqpNc/GCic7esfzrzwkLS1rTfJMdVNIJrbqT0ofAgPE82V2mirtmkyqIqMvmUhS6S4V4vfshE+je2b4HuHoLxuohO1rvNZ90Mqg/43RxBNw8jng+xcG9BHDfwsgXGfaKd+ASbfWJQfcAvQ9DNoyeYix89Yi5+TCe5mBOdu8X+CctTjdW54q1SDaE3xRaRjbO67T7bWLJiRDvbYbxNp9TF62BTEdKzmDSrmP0TE+nf2L4FuhMY9391st6pWTeD6gN+FYJuNPF8iIXbEMcNvBiM8/BOfMLNPjGoPuDXIejmcRPMxY8bMRdv00ku9kTnbptln6djJPOVZ25ZtoqHyFPxLElvbRs3W6NNuSTrkrTOiehdaFtT47VJXOaCmou3nEj/xvYt0N2WGOdcnax3W826GVQf8LsVgm4eSTwfYuF+FHHcwMujMK77deITj5l9YlB9d/CLoJsnTDAXP2HEXLxdJ7n4sUTnbrF/XNjEOTftoEYnJpOtJjupuM0u8Sgdc9WLUrjxQgWtmFextn9YwYsvqqJ+rsfWE+nf2L4FutsaYz/fyXq3zaybQfUBv9sg6ObxxPMhFu5tieMGXrbFyDed+MR2s08Mqg/43Q5BN0+aYC5+0oi5eIdOcvETic7dYv94rNU6pmwpxmbp2mzVnNqAVR9EDKzNoVTOh5SlUUJXHoq448RGeCcMbi7efiL9G9u3QHfbY/hWJ+vdDrNuBtUH/O6AoJsnE8+HWLh3JI4beNkRAfdTOvGJnWafGFQf8LsThm4mmIufMmIu3qmTXPxUonO3rH8m2ZxsjKEYrmuq3HlTRXQ52uxFYjonXgJPjktVfI6mZu2csSJpWXzA7N/OE+nf2L4FutsZwbee1sl6t8usm0H1Ab+7IOjm6cTzIRbuXYnjBl52RcD9jE58YrfZJwbVB/zuhrG+TDAXP23EXLxLJ7n4mUTnbpdl5zS57UdTDNzqUq3Jsabkk3XaCxOj9MoHZ0uyumEVWrddqg1GRc9TacOKer1494n0b2zfAt3tjuBbz+pkvdtj1s2g+oDfPRB082zi+RAL957EcQMveyLgfk4nPrHX7BOD6gN+98LYT00wFz9jxFy8Wye5OBCdu92WvW94Viknb0SRORiRomzfVJuUcMFHljV3sd7xEldTXU2lTV1o8+lDjaYd52D2L06kf2P7FuguIvhW6mS9y7NuBtUH/GYE3RTi+RALdyWOG3ipCLif24lP7D37xKD6gN+9Ma67TDAXP2vEXLxHJ7n4eUTnbrF/QpWcpVO2tu1lUSqplKRnQpkiZQPW/iC3pMUkyyxlFlU7yrE1Zp5CrEU7zP7tM5H+je1boLt9EHzr+Z2sd/vOuhlUH/C7L4JuXkA8H2Lh3o84buBlPwTcL+zEJ/affWJQfcDv/hjnDBPMxc8ZMRfv1UkufhHRuVvsXztuYaZBSUIbHqO2sqhUldA+y8giK76EFJWyVvNkRLQ2wxsjFnj3cJs56n0UB0ykf2P7FujuAATfenEn692Bs24G1Qf8Hoigm5cQz4dYuA8ijht4OQgB90s78YmDZ58YVB/wezDGeeQEc3EaMRfnTnLxy4jO3WL/uGNwf35lWenqS2lbzcCljjVLL4UvUjlpi5FSG50kVzX6tjeNPkcrXRtUzP4dMpH+je1boLtDEHzr5Z2sd4fOuhlUH/B7KIJuXkE8H2LhPow4buDlMATcr+zEJw6ffWJQfcDv4Rj330wwFz93xFy8dye5+FVE526xf9yIWoOzSnDp2kmN5oYbF6sz8GbhkYfMi4ta6pCUho/SqTEKkbisPungC2b/jphI/8b2LdDdEQi+9epO1rsjZ90Mqg/4PRJBN68hng+xcB9FHDfwchQC7td24hNHzz4xqD7g92iM+/QmmIufP2Iu3reTXPw6onO3rH+2bUKDahhNSA2uSMEJI2RNrLjsQ9uWehOUDY5xWYJPsA/VLrW/Ei3XHrN/x0ykf2P7FujuGATfen0n692xs24G1Qf8HougmzcQz4dYuI8jjht4OQ4B9xs78YnjZ58YVB/wezzGfekTzMUvHDEX799JLn4T0blb1r+gfKii7UQ5j0zHzEQwvg1a5DFkHQW3TDEbchCcK1GZKapw5nNxLvBoMPt3wkT6N7Zvge5OQPCtN3ey3p0462ZQfcDviQi6eQvxfIiF+yTiuIGXkxBwv7UTn3jb7BOD6gN+34bx+pUJ5uIXj5iLD+wkF7+d6NwduOz9EZNUBd7qsI1bal/SeOGLqyq0CWPW8sK1rNVar2QOWidVkzNMS9t2pjJg9u/kifRvbN8C3Z2M4Fvv6GS9e+esm0H1Ab/vRNDNu4jnQyzc7yaOG3h5NwLu93TiE6fMPjGoPuD3FIzXa04wF790xFx8cCe5+L1E5255/1wuuh3RRFVkq102fDUV7XI7qNFFyZpFKDU7E0OSOsSiG9x2TtMek2NCfZ+2902kf2P7FujufQi+9f5O1rtTZ90Mqg/4PRVBNx8gng+xcJ9GHDfwchoC7g924hOnzz4xqD7g93SM13VPMBe/fMRcfGgnufhDROduWf9g3+mdi5plz7WVKlYpvMlOMm1rLabtQVl13tmitLexFJullCkLFZxBfZ+2MybSv7F9C3R3BoJvfbiT9e7MWTeD6gN+z0TQzUeI50Ms3GcRxw28nIWA+6Od+MTZs08Mqg/4PRvjfUwmmItfOWIuPryTXPwxonN3+LL3DedcGCm9MKkmw4SrQdSafWWeRV40fK4OC85my7mTuh3etBnNyjKlvOAWs3/nTKR/Y/sW6O4cBN/6eCfr3bmzbgbVB/yei6CbTxDPh1i4zyOOG3g5DwH3JzvxiU/NPjGoPuD3UxjvdzTBXPzqEXPxkZ3k4k8Tnbtl/cvatP2nd6LKXKULsnJfo+MqScZlVdzHwEp0iskobGLt+MbqZGrhqSqDeh/F+RPp39i+Bbo7H8G3PtPJevfZWTeD6gN+P4ugm88Rz4dYuC8gjht4uQAB9+c78YkLZ58YVB/weyGCbl47wVz82hFz8dGd5OIvEJ27xf7xynipjlkjk9dVy6Sk4g23l9kbK0MpVbSdaeUhcO9tNtZGrW30xoviAmb/LppI/8b2LdDdRQi+9cVO1ruLZ90Mqg/4vRhBN18ing+xcF9CHDfwcgkC7i934hOXzj4xqD7g91IE3bx+grn49SPm4mM7ycVfITp3i/3jTCcttG2jx7WwxbDIpOGpPc7qqIP1WeRknODZBS60y56ZklUbUFtsRP1cj8sm0r+xfQt0dxmCb321k/Xua7NuBtUH/H4NQTdfJ54PsXBfThw38HI5Au5vdOIT35x9YlB9wO83EXTzxgnm4jeOmIuP7yQXf4vo3C3rn8xRMx1YkiLFNnCBeS+dT4I71s5inHTC1qh49rVkp7Jz1phclUpGMov6uR5XTKR/Y/sW6O4KBN/6difr3ZWzbgbVB/xeiaCb7xDPh1i4ryKOG3i5CgH3dzvxiatnnxhUH/B7NYJu3jzBXPzmEXPxiZ3k4u8RnbsTl70/ohHFSlely9Ek2H6q7K2wwisleMpehxqEqsoylrgUMkQnkwzMhFSkwOzfNRPp39i+Bbq7BsG3vt/JeveDWTeD6gN+f4Cgmx8Sz4dYuK8ljht4uRYB94868Ykfzz4xqD7g98cIunnrBHPxW0fMxW/rJBf/hOjcLetfKcYlWaRL3CsmpfcqsayyjblIHWubuvYvIYLX1XNdnUg6yMiUEDF71PuLr5tI/8b2LdDddQi+9dNO1rufzboZVB/w+zME3fyceD7Ewn09cdzAy/UIuH/RiU/cMPvEoPqA3xsQdPOOCebid4yYi9/ZSS7+JdG5W+yfKPBWL23IBEvKVpdFZSH4YhT31XphQkxZe6OZU8KL0B6ds3WMWVuMZ6jXi2+cSP/G9i3Q3Y0IvvWrTta7X8+6GVQf8PtrBN38hng+xMJ9E3HcwMtNCLh/24lP3Dz7xKD6gN+bEXTzngnm4veMmItP6SQX/47o3C327453QMySZxGk423QCgteKJ6UEcIHIWr20gnVsKl2RsNKm8fMaonaGW1CxezfLRPp39i+Bbq7BcG3ft/JeveHWTeD6gN+/4Cgmz8Sz4dYuG8ljht4uRUB95868Yk/zz4xqD7g988Iunn/BHPx+0fMxad2kov/QnTulvUvBukr423MQjTBpmoE91pYLWrKRTljbbZVilyVLe0kp4RUldcq6VIN7v3Ft02kf2P7FujuNgTf+msn693fZt0Mqg/4/RuCbv5OPB9i4b6dOG7g5XYE3P/oxCeWVpt9Ykh9wC/0bvTPD59gLv7giLn49E5y8Z2Izt1i/4RPjEWmXeJw+tLmL+bETOTFylp123pWLXP1pjpl2o7VJaatyJzXFKpzEbN/K0ykf2P7FuhuBQTfuvNqfczdirNuBtUH/K6IoJu7jKybXnCvRBw38LISAu6VO/GJVWafGFQf8LsKgm4+PMFc/OERc/GZneTiVYnO3bL+RSMYc77BYsEkY72qqfIkIo+8jZ0MlsvkmQ4uBl5bJ3S1mvFaeNAson7e3WoT6d/YvgW6Ww3Bt1bvZL1bY9bNoPqA3zUQdLMm8XyIhXst4riBl7UQcK/diU+sM/vEoPqA33UQdPPRCebij46Yi8/uJBfflejcLfZPxGSkb0PW8FjJ2ylNFslU6XlWyrsivUjR6pJTzDqpxGobQGFyO7gx8EbimP2720T6N7Zvge7uhuBbd+9kvVt31s2g+oDfdRF0cw/i+RAL93rEcQMv6yHgvmcnPrH+7BOD6gN+10fQzccnmIs/PmIuPreTXHwvonO32D8RnK/SlYaUJXiVKxeWtcMaY3P7j23zyZVmMrejGWtilcm2HSrjuZ3nyOCU0pj922Ai/Rvbt0B3GyD41r07We82nHUzqD7gd0ME3dyHeD7Ewn1f4riBl/si4L5fJz6x0ewTg+oDfjdC0M0nJ5iLPzliLv5UJ7n4/kTnbrF/vB26lFxsKSWqAm/xIl0buhqSyUKzoBXTuv1hyJwV46MMpoFk1qTgrDOo91FsPJH+je1boLuNEXzrAZ2sd5vMuhlUH/C7CYJuHkg8H2Lh3pQ4buBlUwTcD+rEJzabfWJQfcDvZgi6+cwEc/FnRszFn+0kFz+Y6Nwt619qBy7w5oexjZYIVknOdSxaCp+10i4L75hgrp3gVJ9DUty04xphNK8+FhEx+/eQifRvbN8C3T0Ewbce2sl6t/msm0H1Ab+bI+jmYcTzIRbuLYjjBl62QMD98E58gs0+Mag+4Jch6ObzE8zFnx8xF1/YSS7mROdusX8NA5NFZCdV4bDVLFImH6IVJshidc4sh+xjLYEHJYWx3Pv2MKGkb0hRc7GYSP/G9i3QnUDwLdnJeqdm3QyqD/hVCLrRxPMhFm5DHDfwYhBw2058ws0+Mag+4Nch6OaLE8zFXxwxF1/cSS72ROfu4mX39WsrHOcptMELmnPWDmRsw6xSydKIEkvNNmVeuGubVmt88UrqBrbUpAvq/cVbTqR/Y/sW6G5LBN96RCfr3VazbgbVB/xuhaCbRxLPh1i4H0UcN/DyKATcj+7EJx4z+8Sg+u7gF0E3X55gLv7yiLn40k5y8WOJzt2ly+9fEm3otPW+FlGCE8nYxILLzBkZdSmJlXYkY9uulfu2PVVMtG+Yi1pWExVm/7aeSP/G9i3Q3dYIvvW4Tta7bWbdDKoP+N0GQTePJ54PsXBvSxw38LItAu4ndOIT280+Mag+4Hc7BN18dYK5+Ksj5uKvdZKLn0h07pb1TzFbtIrehIZMJsN8DdJ6G4WQycosDAvS6JC1i0I7z4M2hgkrmDcxo14v3n4i/Rvbt0B32yP41pM6We92mHUzqD7gdwcE3TyZeD7Ewr0jcdzAy44IuJ/SiU/sNPvEoPqA350QdPONCebib4yYi7/ZSS5+KtG5W+wfD7IdwmgdWZuyLGVKTgiRvLdKqJi4Yu1kRpQcq4outJlTyRftpIg5pOI5Zv92nkj/xvYt0N3OCL71tE7Wu11m3QyqD/jdBUE3TyeeD7Fw70ocN/CyKwLuZ3TiE7vNPjGoPuB3NwTdfHuCufjbI+biKzvJxc8kOndXLvucSSPa1OlifNuXcpt0O4cJykfepixk5zVX7VvW8BcLb/0SddbaO8Uj3NafMfu3+0T6N7Zvge52R/CtZ3Wy3u0x62ZQfcDvHgi6eTbxfIiFe0/iuIGXPRFwP6cTn9hr9olB9QG/eyHo5rsTzMXfHTEXX91JLg5E5+7qZfcvKSe1Yxw+RFILHVUS3GnZDm50m0HlQlVGF1+tz8Vnbtrj4dMotczB+mAx+xcn0r+xfQt0FxF8K3Wy3uVZN4PqA34zgm4K8XyIhbsSxw28VATcz+3EJ/aefWJQfcDv3gi6+f4Ec/H3R8zFP+gkFz+P6Nwt9k9kFWrJNljmivYNrFPZGiO8qCK1bWfS2emGznBmVdY+ZFk1L14aH9rjMfu3z0T6N7Zvge72QfCt53ey3u0762ZQfcDvvgi6eQHxfIiFez/iuIGX/RBwv7ATn9h/9olB9QG/+yPo5kcTzMU/GjEX/7iTXPwionO32D+eWIms7TJV8s6YIixPWbSNZuW22naKo2qIcI8Tcy56XazMKbWNqRepwQ4Gs38HTKR/Y/sW6O4ABN96cSfr3YGzbgbVB/weiKCblxDPh1i4DyKOG3g5CAH3SzvxiYNnnxhUH/B7MIJufjrBXPzTEXPxzzrJxS8jOneL/RPGsjZNRVUhg83WmZB5+2eUWgZRXXRCGJ9s1C5Ey7KF25YUNw2+VFmhvh/FIRPp39i+Bbo7BMG3Xt7JenforJtB9QG/hyLo5hXE8yEW7sOI4wZeDkPA/cpOfOLw2ScG1Qf8Ho6gm19MMBf/YsRcfEMnufhVROduWf9UaZvRDJtNFjl3rs0bZyYUoRNTyoYEL2vNyWQjUi22liSy9V7m2g53hMDs3xET6d/YvgW6OwLBt17dyXp35KybQfUBv0ci6OY1xPMhFu6jiOMGXo5CwP3aTnzi6NknBtUH/B6NoJtfTTAX/2rEXPzrTnLx64jO3bL+5Sql1DlwWasy1WjmdfVWZ66tc0YoHkpKtUpXs48xeNGaUp03PtvCPGb/jplI/8b2LdDdMQi+9fpO1rtjZ90Mqg/4PRZBN28gng+xcB9HHDfwchwC7jd24hPHzz4xqD7g93gE3fx2grn4tyPm4ps7ycVvIjp3Ny+7r7/WakT0womSmI68BtX2oT6Ytg0tsfiQjGyAZRaRs6JU9IXVwn1pxzSlYPbvhIn0b2zfAt2dgOBbb+5kvTtx1s2g+oDfExF08xbi+RAL90nEcQMvJyHgfmsnPvG22ScG1Qf8vg1BN7+fYC7+/Yi5+A+d5OK3E527Zf1zJRWhXJuk1P6fLdPG+6hTZjZ5z9qxjLWCxxC1j0bbGLl0pWEuxRivUN+/+OSJ9G9s3wLdnYzgW+/oZL1756ybQfUBv+9E0M27iOdDLNzvJo4beHk3Au73dOITp8w+Mag+4PcUBN38aYK5+E8j5uI/d5KL30t07hb7JxIP0fEcDbMxWJNjtbw2TFokp02s3EmmlHc8yWgyr1nyyNt2lVlXtUX9vLv3TaR/Y/sW6O59CL71/k7Wu1Nn3QyqD/g9FUE3HyCeD7Fwn0YcN/ByGgLuD3biE6fPPjGoPuD3dATd/HWCufivI+biv3WSiz9EdO6W9Y/nYqpzzrT/Fal5rCqFkIWXMTtT2m9KNdK1IxquU3TMayUKaw+LsX3rMPt3xkT6N7Zvge7OQPCtD3ey3p0562ZQfcDvmQi6+QjxfIiF+yziuIGXsxBwf7QTnzh79olB9QG/ZyPo5h8TzMX/GDEXL63dx9x9jOjcLfZPyJxd1NbUIJyRkjujspHJ2pqdqMHwHCy3Wkon4KMlnTDclpi1CrFEhfr+xedMpH9j+xbo7hwE3/p4J+vdubNuBtUH/J6LoJtPEM+HWLjPI44beDkPAfcnO/GJT80+Mag+4PdTCLq5838p17H/7GvUXLyI+T/t34qd5OJPE527xf5x4+Fzc4rmOopUisvtYMb7dipjubDStIcHW72oUaoki6xailzan8oQUtuUYvbv/In0b2zfAt2dj+Bbn+lkvfvsrJtB9QG/n0XQzeeI50Ms3BcQxw28XICA+/Od+MSFs08Mqg/4vRBBNytPMBevPGIuXqWTXPwFonO3rH8lVdeQeVdgnoL3oc0gc1lYXnkNXhTNuEs8JOd91lrlxHMNUqcSWUDt30UT6d/YvgW6uwjBt77YyXp38aybQfUBvxcj6OZLxPMhFu5LiOMGXi5BwP3lTnzi0tknBtUH/F6KoJvVJ5iLVx8xF6/RSS7+CtG5W9a/nFg2xZpQY5DW5my8LFklZYOqvpZig2ub1Fx1rkbUzEwV1Vl4LUDhCfX+4ssm0r+xfQt0dxmCb321k/Xua7NuBtUH/H4NQTdfJ54PsXBfThw38HI5Au5vdOIT35x9YlB9wO83EXSz9gRz8doj5uJ1OsnF3yI6d8v6l11mTluupU/GtdHLIYtgjHTC8yyF9Kqd4tjQNqU+2FhESVxl5yVzMRrU92m7YiL9G9u3QHdXIPjWtztZ766cdTOoPuD3SgTdfId4PsTCfRVx3MDLVQi4v9uJT1w9+8Sg+oDfqxF0c/cJ5uK7j5iL1+0kF3+P6Nwt9o/bzC0rVsKt+8ULkbxUtSEKWSbhqtOlchUFT1Zq1f628A5uc7LG27ZjVZj9u2Yi/Rvbt0B31yD41vc7We9+MOtmUH3A7w8QdPND4vkQC/e1xHEDL9ci4P5RJz7x49knBtUH/P4YQTf3nGAuvueIuXj9TnLxT4jO3bL++ZKNZFmxdhoDn7YepGqwNdeJpyiNa2c2TCeVSxYmV+mMFll4FoWp7WynYvbvuon0b2zfAt1dh+BbP+1kvfvZrJtB9QG/P0PQzc+J50Ms3NcTxw28XI+A+xed+MQNs08Mqg/4vQFBN/eeYC6+94i5eMNOcvEvic7dYv9E1NJxr2SGe5ZkzEz7oKyy0YqaODeVeZ+UYUzl5DjPOSrFKnycTsPMUT8H+saJ9G9s3wLd3YjgW7/qZL379aybQfUBv79G0M1viOdDLNw3EccNvNyEgPu3nfjEzbNPDKoP+L0ZQTf3m2Auvt+IuXijTnLx74jO3bL+8dx2oMU7W7zRCTagiQktirc5ulijdca43HamPuVqkoWZY21aY9YiyojZv1sm0r+xfQt0dwuCb/2+k/XuD7NuBtUH/P4BQTd/JJ4PsXDfShw38HIrAu4/deITf559YlB9wO+fEXTzgAnm4geMmIs36SQX/4Xo3C32jwfukvOmcqFSVk7wGgtzIRnH2sxJIxLXUinDfSqVWeGsqkpaD+8dU4XE7N9tE+nf2L4FursNwbf+2sl697dZN4PqA37/hqCbvxPPh1i4byeOG3i5HQH3PzrxiaXVZ58YUh/wC70bWzcPmmAuftCIuXizTnLxnYjO3WbL3je8bTZDZSUUkWrbk1YTpWKxZgU3+fOkGngba63GGy7h7V+8FaK0x+g2d6j9W2Ei/Rvbt0B3KyD41p1X72PuVpx1M6g+4HdFBN3cZWTd9IJ7JeK4gZeVEHCv3IlPrDL7xKD6gN9VEHTz0Anm4oeOmIs37yQXr0p07hb7x3PN2lkrTElKCW10icrWdlYjlVXMSBWNNiLzaBj3wivL21Q6Y1kIinHU96NYbSL9G9u3QHerIfjW6p2sd2vMuhlUH/C7BoJu1iSeD7Fwr0UcN/CyFgLutTvxiXVmnxhUH/C7DoJuHj7BXPzwEXMx6yQX35Xo3C32jysbPFMxZW6DrMaUmC185CQX1mtm28OLYcIpEZiybfBq5txnyUuu0gvUXHy3ifRvbN8C3d0Nwbfu3sl6t+6sm0H1Ab/rIujmHsTzIRbu9YjjBl7WQ8B9z058Yv3ZJwbVB/yuj6AbOcFcLEfMxaqTXHwvonO3vH9GcG5UcbENnrKGN7xFhBCzDzwYW1JiunphYkk6xpBKtFoow01pf89g9m+DifRvbN8C3W2A4Fv37mS923DWzaD6gN8NEXRzH+L5EAv3fYnjBl7ui4D7fp34xEazTwyqD/jdCEE3doK52I6Yi10nufj+ROdusX/CsZpS8byNFoumgSlFFhOcdCHGxKtt5zaqKKdlFCIzY4M2VRfPnPINN2b/Np5I/8b2LdDdxgi+9YBO1rtNZt0Mqg/43QRBNw8kng+xcG9KHDfwsinG66c68YnNZp8YVB/wuxmCbh4xwVz8iBFz8Vad5OIHE527xf6JrHxmMkQTreLK66KyTbG0+QsmVVaZCSW4NmrCZS6zttUE1h6VnHGZRcz+PWQi/Rvbt0B3D8F4XUQn693ms24G1Qf8bo6gm4cRz4dYuLcgjht42QLjPtFOfILNPjGoPuCXIejm0RPMxY8eMRc/ppNczInO3WL/RNA+mqI4c1pkb4zhynpu236ThypdVdZFa5gsURZVhWwbV2+kzE6YlAvq9WIxkf6N7VugO4Fx/1cn652adTOoPuBXIehGE8+HWLgNcdzAi8E4D+/EJ9zsE4PqA34dgm4eN8Fc/LgRc/E2neRiT3Tutln2/ojWOlmDr9VGaXI7noEblIrRqSbXhotFyzJ8nk7UPERtlS66Fp6T1NlHjtm/LSfSv7F9C3S3JcY5Vyfr3VazbgbVB/xuhaCbRxLPh1i4H0UcN/DyKIzrfp34xGNmnxhU3x38IujmCRPMxU8YMRdv10kufizRudtu2f1LJvNiC5O+hju+idnVYnzhbfpSyIYbL1NqwBp45ZTlnsdQRK1SqSgw+7f1RPo3tm+B7rbG2M93st5tM+tmUH3A7zYIunk88XyIhXtb4riBl20x8k0nPrHd7BOD6gN+t0PQzZMmmIufNGIu3qGTXPxEonO3rH81tCOaHIsrXBWXtGQNgA+htgMZ53OIUebEhKm1pMiUzzKb2AYutXYwazH7t/1E+je2b4HutsfwrU7Wux1m3QyqD/jdAUE3TyaeD7Fw70gcN/CyIwLup3TiEzvNPjGoPuB3JwzdTDAXP2XEXLxTJ7n4qUTnbln/SpshbaSuQTdUzAmfGigpkpKGxxpsyTVXxSLTXCXGcpbBSulaTyr3qJ8DvfNE+je2b4Hudkbwrad1st7tMutmUH3A7y4Iunk68XyIhXtX4riBl10RcD+jE5/YbfaJQfUBv7thrC8TzMVPGzEX79JJLn4m0blb7J+QkZVgeXQxZpmiEfC616KFrjq5KHWKtWQnGOxQhVTw2lhltE65Wt4OdzD7t/tE+je2b4HudkfwrWd1st7tMetmUH3A7x4Iunk28XyIhXtP4riBlz0RcD+nE5/Ya/aJQfUBv3th7KcmmIufMWIu3q2TXByIzt1uy17vmkrWVuRYszBGaeOZZDVV6TnjDZao1rfZi0W2YxmunFc11mQb/NBmsGL2L06kf2P7FuguIvhW6mS9y7NuBtUH/GYE3RTi+RALdyWOG3ipCLif24lP7D37xKD6gN+9Ma67TDAXP2vEXLxHJ7n4eUTnbln/ZJImSsUyFzlUoYSoJWaug9KCV9kOZ7Rn2iYRas0NuknG1iDbVjWltj3F7N8+E+nf2L4FutsHwbee38l6t++sm0H1Ab/7IujmBcTzIRbu/YjjBl72Q8D9wk58Yv/ZJwbVB/zuj3HOMMFc/JwRc/FeneTiFxGdu8X+cZuNSrAFFV4an5hv46WFT1ZLEV0bQwcvfq0mZ5/hNn/DZAzOpOiFbs3B7N8BE+nf2L4FujsAwbde3Ml6d+Csm0H1Ab8HIujmJcTzIRbug4jjBl4OQsD90k584uDZJwbVB/wejHEeOcFcnEbMxbmTXPwyonO3rH9eM81kA6K4NEUlK6NqJzQhMuZiNUIHK5PmoU1jsbZ6nwwzKdh2vmNkRs3Fh0ykf2P7FujuEATfenkn692hs24G1Qf8Hoqgm1cQz4dYuA8jjht4OQwB9ys78YnDZ58YVB/wezjG/TcTzMXPHTEX791JLn4V0blb7B9nKbCaRfA6Ju6dbcMkra7aGO6EMrKw5EUJXIhcjXK68qSKDt4aH6VImP07YiL9G9u3QHdHIPjWqztZ746cdTOoPuD3SATdvIZ4PsTCfRRx3MDLUQi4X9uJTxw9+8Sg+oDfozHu05tgLn7+iLl4305y8euIzt1i/4SvRiYvdalFCFWE1FlH1bA6bV0bryh026P6IJXIKrDs2zbVu1Kttjka1M+7O2Yi/Rvbt0B3xyD41us7We+OnXUzqD7g91gE3byBeD7Ewn0ccdzAy3EIuN/YiU8cP/vEoPqA3+Mx7kufYC5+4Yi5eP9OcvGbiM7dYv944cI1ZKXWNleSR25dTF7blFhSPPBshbRMW7hfydTMPCtRJiONib5Ujdm/EybSv7F9C3R3AoJvvbmT9e7EWTeD6gN+T0TQzVuI50Ms3CcRxw28nISA+62d+MTbJuATd17QDXytOK6G3NrtB6xz59GeT/3iLktLN9xlvAz7+VWWli5cZTxuQNugm7H7uOp4z6VWG++5xOoj+s0aSzi+AF/P+ue/oY8r/I8/W2nh948Z6eevtDS6H7Mm+6W7/PO51vpn3ePqjDPoz53/R3/u9D++f8zC71dc6OFdEHq40qjPaSM8x8oL9f8L679qX33hz1da+PfK42Ljd1r4mf963n99vzLazxV3fL7pKv8L/lX+TR2r/Bfxr4L2c80d/K/6v+Bf9d/Usep/Ef+qaD/X3PG+rKv9L/hX+zd1rPZfxL8a2s815V8Y///wr/5v6lj9v4h/dbSfaxQ8xxr/C/41/k0da/wX8a+x8HMx/O//Fv/KBPCP+3NlgOdY83/Bv+a/qWPN/yL+NRd+Lgb//7f4VyaAf9yfaww8x1r/C/61/k0da/0X8a+18HMx1r//W/yrEsA/7s81d1wXXPt/wb/2v6lj7f8i/rXRfq654/64df4X/Ov8mzrW+S/iX2fh52Ks//+3+FcngB/D//9v8a9MAP+4P9fe8T5bd/1f8N/139Rx1/8i/n/9rFUWONj/gOftd+C++/3r4YuXcP71+zstwFmk8H9evhgNw9LS+Nfc/3X9cPT3/unkngKs64n/8XsSddK/v685Xv9ePOI9GS/po39qzHtaDhyxfwd10r8TR+zfS0bs30s7uSfo7SOeOY6oGb6sfw2MS7Z6Xosy1fD2PyZs5NxlE5R2IcUYrfAymzte1m1UDMF7E0qF7/7nmeO/vsZeS0fsJVus9+SFC4j/Ov9Y4d9oAuEM6P/zOoP/2ce1ljoLPEDSyauP/7zvWH28ocTC/Y7VR+domTlR7unqCzWu8E8xwzDBJgBSO4R/uAADF+H/dVH2X3gWD2z/H6571JTrkQ4A","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/merkle_insert/target/witness.tr b/crates/nargo_cli/tests/test_data/merkle_insert/target/witness.tr
index 1e45192ef23..d19fcd4479e 100644
Binary files a/crates/nargo_cli/tests/test_data/merkle_insert/target/witness.tr and b/crates/nargo_cli/tests/test_data/merkle_insert/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/modules/Nargo.toml b/crates/nargo_cli/tests/test_data/modules/Nargo.toml
index e0b467ce5da..eaa0a3a1b4b 100644
--- a/crates/nargo_cli/tests/test_data/modules/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/modules/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
+name = "modules"
 authors = [""]
 compiler_version = "0.1"
 
-[dependencies]
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/modules/target/main.json b/crates/nargo_cli/tests/test_data/modules/target/main.json
index 1ae1a66ab0d..5b013404f52 100644
--- a/crates/nargo_cli/tests/test_data/modules/target/main.json
+++ b/crates/nargo_cli/tests/test_data/modules/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"y","type":{"kind":"field"},"visibility":"public"}],"param_witnesses":{"x":[1],"y":[2]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/82RSw7DMAhESVL3PGAghl2vUqvO/Y9QqbIlq12GSJ0NrJ7mcweABL/a+n30i+dEy8Ri3EVayY2Ynpi9mqJo3Y2M1PSVjbmZWPHqBZ2EGx3qfHTYGsja4jJ+fI3ubv1fgnsc7G/u2R5SYA9X5U4X5I7cHyb98T40vK2T3zdWhU+xCAQAAA==","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"y","type":{"kind":"field"},"visibility":"public"}],"param_witnesses":{"x":[1],"y":[2]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/7WTMRLEIAhFMYkp9ywgGrHbq6yz5v5H2JkdCyaxC9LgWDw+H9gBwMM91p7fPeOzIKdYjEeMLYdGTB8MpUrCmOohJJQkfYMwN4mSSy0ZC0VudKbCZ4cthqzVrsc/yw28dMZeWmrWerfBexnsxD6hJ7jUufr4GvyZFp8xpG0C14Pd8s/q29vPCBXypvmpDx7sD8opnfqIfsM1RNtxBQAA","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/modules/target/witness.tr b/crates/nargo_cli/tests/test_data/modules/target/witness.tr
index f2e4f40bac6..75b360e7cac 100644
Binary files a/crates/nargo_cli/tests/test_data/modules/target/witness.tr and b/crates/nargo_cli/tests/test_data/modules/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/modules_more/Nargo.toml b/crates/nargo_cli/tests/test_data/modules_more/Nargo.toml
index e0b467ce5da..cc60838dbb0 100644
--- a/crates/nargo_cli/tests/test_data/modules_more/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/modules_more/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
+name = "modules_more"
 authors = [""]
 compiler_version = "0.1"
 
-[dependencies]
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/modules_more/target/main.json b/crates/nargo_cli/tests/test_data/modules_more/target/main.json
index 10cdf62cb0f..5249e410b3a 100644
--- a/crates/nargo_cli/tests/test_data/modules_more/target/main.json
+++ b/crates/nargo_cli/tests/test_data/modules_more/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"y","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"x":[1],"y":[2]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/82RQQ6DMAwETWn6Hju2iX3rVxo1/P8JSChICI4Yib2sTyPv7gcAEpw1dv92x2uiYcdinERayY2Yfpi9mqJonYyM1PSfjbmZWPHqBZ2EG83qPHfYK5A1xmVc/9q6e/d7CO5xYx+5V3tIgT3clTvdkDtyf9jpwfsQHLQAJ4/0cgQEAAA=","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"y","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"x":[1],"y":[2]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/7VTMQ7DIAw0JGTsW2wMwWz9SlHJ/59QqSISSthibjFiON+d7Q0AHNyxtPpuFZ+BTMfFuIdQk6/E9EGfi0QMsexCQlHi1wtzlSApl5wwU+BKR8x8NDKryLXoefxzmUGWRjlLTc293nXwtoOd2CZ4gkufa46vwZ9q8xlDWifwOtBb/lm+nf6MsKO8aX6ag1PUaTuN/fGc+AEp7slRcQUAAA==","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/modules_more/target/witness.tr b/crates/nargo_cli/tests/test_data/modules_more/target/witness.tr
index e5c3a870c45..37e8a80e806 100644
Binary files a/crates/nargo_cli/tests/test_data/modules_more/target/witness.tr and b/crates/nargo_cli/tests/test_data/modules_more/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/modulus/Nargo.toml b/crates/nargo_cli/tests/test_data/modulus/Nargo.toml
index e0b467ce5da..895b2af6ac0 100644
--- a/crates/nargo_cli/tests/test_data/modulus/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/modulus/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
+name = "modulus"
 authors = [""]
 compiler_version = "0.1"
 
-[dependencies]
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/modulus/target/main.json b/crates/nargo_cli/tests/test_data/modulus/target/main.json
index c3e8c8b4d99..ee73406d65e 100644
--- a/crates/nargo_cli/tests/test_data/modulus/target/main.json
+++ b/crates/nargo_cli/tests/test_data/modulus/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"bn254_modulus_be_bytes","type":{"kind":"array","length":32,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"},{"name":"bn254_modulus_be_bits","type":{"kind":"array","length":254,"type":{"kind":"integer","sign":"unsigned","width":1}},"visibility":"private"}],"param_witnesses":{"bn254_modulus_be_bits":[33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200,201,202,203,204,205,206,207,208,209,210,211,212,213,214,215,216,217,218,219,220,221,222,223,224,225,226,227,228,229,230,231,232,233,234,235,236,237,238,239,240,241,242,243,244,245,246,247,248,249,250,251,252,253,254,255,256,257,258,259,260,261,262,263,264,265,266,267,268,269,270,271,272,273,274,275,276,277,278,279,280,281,282,283,284,285,286],"bn254_modulus_be_bytes":[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32]},"return_type":{"kind":"field"},"return_witnesses":[1145]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"bn254_modulus_be_bytes","type":{"kind":"array","length":32,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"},{"name":"bn254_modulus_be_bits","type":{"kind":"array","length":254,"type":{"kind":"integer","sign":"unsigned","width":1}},"visibility":"private"}],"param_witnesses":{"bn254_modulus_be_bits":[33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200,201,202,203,204,205,206,207,208,209,210,211,212,213,214,215,216,217,218,219,220,221,222,223,224,225,226,227,228,229,230,231,232,233,234,235,236,237,238,239,240,241,242,243,244,245,246,247,248,249,250,251,252,253,254,255,256,257,258,259,260,261,262,263,264,265,266,267,268,269,270,271,272,273,274,275,276,277,278,279,280,281,282,283,284,285,286],"bn254_modulus_be_bytes":[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32]},"return_type":{"kind":"field"},"return_witnesses":[2003]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/modulus/target/witness.tr b/crates/nargo_cli/tests/test_data/modulus/target/witness.tr
index ab27312faa7..cc9339c4168 100644
Binary files a/crates/nargo_cli/tests/test_data/modulus/target/witness.tr and b/crates/nargo_cli/tests/test_data/modulus/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/nested_arrays_from_brillig/Nargo.toml b/crates/nargo_cli/tests/test_data/nested_arrays_from_brillig/Nargo.toml
new file mode 100644
index 00000000000..01273040d31
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/nested_arrays_from_brillig/Nargo.toml
@@ -0,0 +1,6 @@
+[package]
+name = "nested_arrays_from_brillig"
+authors = [""]
+compiler_version = "0.6.0"
+
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/nested_arrays_from_brillig/Prover.toml b/crates/nargo_cli/tests/test_data/nested_arrays_from_brillig/Prover.toml
new file mode 100644
index 00000000000..1a59cd124a7
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/nested_arrays_from_brillig/Prover.toml
@@ -0,0 +1 @@
+values = [1,2,3,4,5,6]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/nested_arrays_from_brillig/src/main.nr b/crates/nargo_cli/tests/test_data/nested_arrays_from_brillig/src/main.nr
new file mode 100644
index 00000000000..46c4ebe938e
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/nested_arrays_from_brillig/src/main.nr
@@ -0,0 +1,26 @@
+struct Header {
+    params: [Field; 3],
+}
+
+struct MyNote {
+    plain: Field,
+    array: [Field; 2],
+    header: Header,
+}
+
+fn access_nested(notes: [MyNote; 2]) -> Field {
+    notes[0].array[1] + notes[1].array[0] + notes[0].plain + notes[1].header.params[0]
+}
+
+unconstrained fn create_inside_brillig(values: [Field; 6]) -> [MyNote; 2] {
+    let header = Header { params: [values[0], values[1], values[2]]};
+    let note0 = MyNote { array: [values[0], values[1]], plain : values[2], header };
+    let note1 = MyNote { array: [values[3], values[4]], plain : values[5], header };
+    [note0, note1]
+}
+
+fn main(values: [Field; 6]) {
+    let notes = create_inside_brillig(values);
+    assert(access_nested(notes) == (2 + 4 + 3 + 1));
+}
+
diff --git a/crates/nargo_cli/tests/test_data/nested_arrays_from_brillig/target/main.json b/crates/nargo_cli/tests/test_data/nested_arrays_from_brillig/target/main.json
new file mode 100644
index 00000000000..d4c1a39603f
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/nested_arrays_from_brillig/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"values","type":{"kind":"array","length":6,"type":{"kind":"field"}},"visibility":"private"}],"param_witnesses":{"values":[1,2,3,4,5,6]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/92b7VbiMBCGw2cpxYoo8uk99BPKP25l3cUfe817MdvEzvElGyrKjEvNOTltSc0882ZmGisulVK+em296tivjq2yt8veKXu3Gu9X1y24h+5X8Jlu++oYXdbiFt9ckRRjuwGMnQYwdhvA2GsAY5+REXN9VJ17ZR+o19oxLHtQjd2UPSz7bdnHZb8r+0S9tT/VUf9cWx03rCN7HvZNn1/bSK//b2Du8c7/U2vTtbRpWdd7OMe67TH7quccMM+p1NszRzeKA2IfqrdYwPvwnPQhtgDG+3BkZo8FNI7JZ1uPAejhwzlpMbS0aFnz7OHaA01GMM7Ab2LkhnlOPUcIvpD/I9AhqM7xPjwn34ktgPEA9GBmjwU0jk/pcfMJPUbv6MEc34lAHqaogW6uGoK5Qkc6x5zBefZwPQBNmpgz9nqfEyN2XH2nnLHrwUf0eC9nmNkTAY2TU3pIxAd3vgvUpQ36o5vruXvuPsQDDVz7EGb2TEDjLfls64E19dJ9CNZU7vonUaf1HF/13OWufxJ1+pQeEvsy5vjOBfJwhxro5qohl+5DcO/exJxp0HP3S3KmQfuyRGJvc0oP7vjAd0xd6+cUjIWVdl1eP00e9Bz2uuBnpzrHdzh9Xg4Tf56Dow8cZB9rDXP9TU7pj7WS7OMeSmJdXPscXBd7nyO1LoGDA9eF7As+F826jBwcuC5kfwQczLXG/E4fOjiwLpD9EDhueTkyPcfYwXELHGR/DBx3vBy5nmPi4LgDDrI/AY57Xo6Nb3HoVvc++h5YHnhZTO5OwRZxkZ0AxjFnprwc5m+SD5b/dD0Fu4+8dhNfHfuvW91aPALLjJfFrMUcbBHXDPSncaznc14OsxYzy3+6Rr5zWYdXwIr3uGJ8ZvkhsL61MT6T0yj11bH/utXF+BxYFrwsJsaXYIu4yE4A4x3gWPJymLVYWP7TNfKdy9prEKt3Bax4jysfF5YfArFYm4+LT7CO/zOrwHqa5yP6r1td7VgCy4qXxdSONdgiLrITwDjuq9e8HGYtVpb/dI1857KGV8CK97hifGX5IbC+tTG+krP74ecjsjCvl4nxJ7BFXGQngHF8Pj7xcpi1WFv+0zXyncvaaxCrdwWseI8rH9eWH1K141Q+ki0fPpvAZ22LWWtq5xTrix9qHea5Pca5fJgrjTZZdtgmhziNf0TJ7rnIoyx/3hRxEedF/isp0vRQZMV297zbRrs4Sw/xS75LX6rJZoq36EjpFzLONWbUb/5F+l3Kec+oH2PMxHMGHw8vpm3xC/DYuL/Ey6hlhLxYJOmld9sREwJfnv2n9tk6hkq48Eos0oPAvFPFl5RSfk/51+ioOF2zpu/9l4zd/gJqB4bgajMAAA==","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/nested_arrays_from_brillig/target/witness.tr b/crates/nargo_cli/tests/test_data/nested_arrays_from_brillig/target/witness.tr
new file mode 100644
index 00000000000..878a2665415
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/nested_arrays_from_brillig/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/numeric_generics/Nargo.toml b/crates/nargo_cli/tests/test_data/numeric_generics/Nargo.toml
index d9434868157..199ec161f74 100644
--- a/crates/nargo_cli/tests/test_data/numeric_generics/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/numeric_generics/Nargo.toml
@@ -1,7 +1,6 @@
+[package]
+name = "numeric_generics"
+authors = [""]
+compiler_version = "0.1"
 
-        [package]
-        authors = [""]
-        compiler_version = "0.1"
-    
-        [dependencies]
-    
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/numeric_generics/target/main.json b/crates/nargo_cli/tests/test_data/numeric_generics/target/main.json
index d1dbb3968e9..4c3bb072cb3 100644
--- a/crates/nargo_cli/tests/test_data/numeric_generics/target/main.json
+++ b/crates/nargo_cli/tests/test_data/numeric_generics/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[],"param_witnesses":{},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/2NkwA0A9IrFgRwAAAA=","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[],"param_witnesses":{},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/2NkIAwAQGbG/yQAAAA=","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/pedersen_check/Nargo.toml b/crates/nargo_cli/tests/test_data/pedersen_check/Nargo.toml
index d9434868157..c4fbf2407a7 100644
--- a/crates/nargo_cli/tests/test_data/pedersen_check/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/pedersen_check/Nargo.toml
@@ -1,7 +1,6 @@
+[package]
+name = "pedersen_check"
+authors = [""]
+compiler_version = "0.1"
 
-        [package]
-        authors = [""]
-        compiler_version = "0.1"
-    
-        [dependencies]
-    
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/pedersen_check/target/main.json b/crates/nargo_cli/tests/test_data/pedersen_check/target/main.json
index ee10b717c38..a6e68f73f03 100644
--- a/crates/nargo_cli/tests/test_data/pedersen_check/target/main.json
+++ b/crates/nargo_cli/tests/test_data/pedersen_check/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"y","type":{"kind":"field"},"visibility":"private"},{"name":"salt","type":{"kind":"field"},"visibility":"private"},{"name":"out_x","type":{"kind":"field"},"visibility":"private"},{"name":"out_y","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"out_x":[4],"out_y":[5],"salt":[3],"x":[1],"y":[2]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/9WXaQrCMBCFp9Z939FbJE1ik39exWK9/wnEBjsw+tcXqA9CSQuP+WYh6ZmIDvRW1qxhs3pi/2z3z/Zd/D6iT+Xt89o+jbpYW5dFrY2+qSJU3inrqovXXjvv7oU3pvbWl6EKpQramlo/XDAP9VZfeKnfpIfAuMa4uBTnOHpORL4JyM7eGbg+U2AeUnFPE3Aj609CaH50fVjoOR8AmUfAuGaEn/PoOU9Ub/ZG9/uCuj3nkXuRgBtZfxJC86Prw8qxcfoMyNwDep3+I386B/b2GuiFzB/fPXlGYpx851w2a0WfQs/8DsZSVN8sO8Gyadb2iwV9ri6BvbcBxrUn/LkaPeX/CwHZ2Rvda0fq9rkauY8JuJH1JyE0P7o+Ui8jwZQOcA8AAA==","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"y","type":{"kind":"field"},"visibility":"private"},{"name":"salt","type":{"kind":"field"},"visibility":"private"},{"name":"out_x","type":{"kind":"field"},"visibility":"private"},{"name":"out_y","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"out_x":[4],"out_y":[5],"salt":[3],"x":[1],"y":[2]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/+1X0Y6CMBBcQPDUU09Pzd1ftBSkvN2vHBH//wuMNLbJWn3rNMHESZoWSJaZ2Xaz/SWiPd2QDKMYRsqeL/b5Yt+Z71O6R2bnPzsrcayqvil7qeS/KNtO16Kqu6OWWta6PpVaqV5Xumm7thGtrFQvz3WrzuKGCYslwiALIK8PHC+RWX99JJ6XIgwSyZnznbH1xM7pkz1RRNBE3n98H1dP3kF/HiNJswhx54Tb/LF0z/E5Eizk6D11QBfRHKh5CuS1oNcrokjOnO8nW7+LaGDMhTUUHXdJ4y6iRvcSn6OoRRTtqUOG5akToOYUqPmH4uQZ7J/MgJpXQF5I/9ytyZ0Rw9PdltbD+KJ7+Gcp1JcNTEvZ+Vo2TMt2GN+eFnTTsgbmeAvktaPXa1qQnDnfPVu/m5bAmDtrKDrugcbdtBjdB3yOojYtSE9zxtEcHrOZzWHK6RFXJUaxiKMTAAA=","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/pedersen_check/target/witness.tr b/crates/nargo_cli/tests/test_data/pedersen_check/target/witness.tr
index 13568902eb0..d6e19416a8c 100644
Binary files a/crates/nargo_cli/tests/test_data/pedersen_check/target/witness.tr and b/crates/nargo_cli/tests/test_data/pedersen_check/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/poseidon_bn254_hash/Nargo.toml b/crates/nargo_cli/tests/test_data/poseidon_bn254_hash/Nargo.toml
index 6a061f5a217..49f60c86aee 100644
--- a/crates/nargo_cli/tests/test_data/poseidon_bn254_hash/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/poseidon_bn254_hash/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
-name = "Poseidon 254-bit permutation test on 3 elements with alpha = 5"
+name = "poseidon_bn254_hash"
+description = "Poseidon 254-bit permutation test on 3 elements with alpha = 5"
 authors = [""]
 compiler_version = "0.1"
 
diff --git a/crates/nargo_cli/tests/test_data/poseidon_bn254_hash/target/main.json b/crates/nargo_cli/tests/test_data/poseidon_bn254_hash/target/main.json
index da09534d15c..ead0faac568 100644
--- a/crates/nargo_cli/tests/test_data/poseidon_bn254_hash/target/main.json
+++ b/crates/nargo_cli/tests/test_data/poseidon_bn254_hash/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x1","type":{"kind":"array","length":2,"type":{"kind":"field"}},"visibility":"private"},{"name":"y1","type":{"kind":"field"},"visibility":"public"},{"name":"x2","type":{"kind":"array","length":4,"type":{"kind":"field"}},"visibility":"private"},{"name":"y2","type":{"kind":"field"},"visibility":"public"}],"param_witnesses":{"x1":[1,2],"x2":[4,5,6,7],"y1":[3],"y2":[8]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x1","type":{"kind":"array","length":2,"type":{"kind":"field"}},"visibility":"private"},{"name":"y1","type":{"kind":"field"},"visibility":"public"},{"name":"x2","type":{"kind":"array","length":4,"type":{"kind":"field"}},"visibility":"private"},{"name":"y2","type":{"kind":"field"},"visibility":"public"}],"param_witnesses":{"x1":[1,2],"x2":[4,5,6,7],"y1":[3],"y2":[8]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/poseidon_bn254_hash/target/witness.tr b/crates/nargo_cli/tests/test_data/poseidon_bn254_hash/target/witness.tr
index 98aadc61c77..28f73665f80 100644
Binary files a/crates/nargo_cli/tests/test_data/poseidon_bn254_hash/target/witness.tr and b/crates/nargo_cli/tests/test_data/poseidon_bn254_hash/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/poseidonsponge_x5_254/Nargo.toml b/crates/nargo_cli/tests/test_data/poseidonsponge_x5_254/Nargo.toml
index 902abd85754..4577f31236c 100644
--- a/crates/nargo_cli/tests/test_data/poseidonsponge_x5_254/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/poseidonsponge_x5_254/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
-name = "Variable-length Poseidon-128 sponge test on 7 elements with alpha = 5"
+name = "poseidonsponge_x5_254"
+description = "Variable-length Poseidon-128 sponge test on 7 elements with alpha = 5"
 authors = [""]
 compiler_version = "0.1"
 
diff --git a/crates/nargo_cli/tests/test_data/poseidonsponge_x5_254/target/main.json b/crates/nargo_cli/tests/test_data/poseidonsponge_x5_254/target/main.json
index e44834080df..1514e7de371 100644
--- a/crates/nargo_cli/tests/test_data/poseidonsponge_x5_254/target/main.json
+++ b/crates/nargo_cli/tests/test_data/poseidonsponge_x5_254/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"array","length":7,"type":{"kind":"field"}},"visibility":"private"}],"param_witnesses":{"x":[1,2,3,4,5,6,7]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"array","length":7,"type":{"kind":"field"}},"visibility":"private"}],"param_witnesses":{"x":[1,2,3,4,5,6,7]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/poseidonsponge_x5_254/target/witness.tr b/crates/nargo_cli/tests/test_data/poseidonsponge_x5_254/target/witness.tr
index 44e1f1e18a0..a8558ca73c8 100644
Binary files a/crates/nargo_cli/tests/test_data/poseidonsponge_x5_254/target/witness.tr and b/crates/nargo_cli/tests/test_data/poseidonsponge_x5_254/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/pred_eq/Nargo.toml b/crates/nargo_cli/tests/test_data/pred_eq/Nargo.toml
index d9434868157..ffa0d440f4a 100644
--- a/crates/nargo_cli/tests/test_data/pred_eq/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/pred_eq/Nargo.toml
@@ -1,7 +1,6 @@
+[package]
+name = "pred_eq"
+authors = [""]
+compiler_version = "0.1"
 
-        [package]
-        authors = [""]
-        compiler_version = "0.1"
-    
-        [dependencies]
-    
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/pred_eq/target/main.json b/crates/nargo_cli/tests/test_data/pred_eq/target/main.json
index 1296aef707e..d157823f59d 100644
--- a/crates/nargo_cli/tests/test_data/pred_eq/target/main.json
+++ b/crates/nargo_cli/tests/test_data/pred_eq/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"y","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"x":[1],"y":[2]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/82STQ6DIBCFR62t3oZhQIZdr1JSvP8RGhtIiC6ZSXybYfWF97MCwApXTeW+yzV9wqFhkdmcy8FmJPwYGxN743zaGBk9+69losyOQ0wxmIiOMu4+0l5goyBrkvP4/1fN7lHeg3COlX3m9uYwC+ag5XtW8C3ZPzQaFfvpZT0VNn8wX0qbr2zp7he49+YP34uCb8n+oZG0f+l+Wv0AhcF06fgGAAA=","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"y","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"x":[1],"y":[2]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/+1USxLCIAxNf9huPAvhU8LOq8hI738ERwcdrOwaHBZmkwyLl7yX8BYAWOA7hpQvKctjgV2GpeVqTHQqosarVD6QlcaGlZDQkr0p0jqSIeeDd9Kj0RE36/WWwHpGrIGP4xOrK2jZMWvJOXM+71io+8JNiAqcYNdnr+O58MbavMaSxgq4E/Adfy3eE/+OZAb5PsoWNRXAa06/MBQBdQzllNV/QzmIKZKg3LgztG0oD94z/44+DKVlTftsxvzzvOIOhKdrBcIJAAA=","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/pred_eq/target/witness.tr b/crates/nargo_cli/tests/test_data/pred_eq/target/witness.tr
index 4e27ca68940..dd00292cdab 100644
Binary files a/crates/nargo_cli/tests/test_data/pred_eq/target/witness.tr and b/crates/nargo_cli/tests/test_data/pred_eq/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/range_fail/Nargo.toml b/crates/nargo_cli/tests/test_data/range_fail/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data/range_fail/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/range_fail/Prover.toml b/crates/nargo_cli/tests/test_data/range_fail/Prover.toml
deleted file mode 100644
index 7524e8b58b1..00000000000
--- a/crates/nargo_cli/tests/test_data/range_fail/Prover.toml
+++ /dev/null
@@ -1,2 +0,0 @@
-x = "300"
-y = "20"
diff --git a/crates/nargo_cli/tests/test_data/range_fail/src/main.nr b/crates/nargo_cli/tests/test_data/range_fail/src/main.nr
deleted file mode 100644
index 4535c5d9e5f..00000000000
--- a/crates/nargo_cli/tests/test_data/range_fail/src/main.nr
+++ /dev/null
@@ -1,8 +0,0 @@
-// Multiple integers constraints.
-//
-// There is currently no range optimizer currently in ACIR :(
-//    
-fn main(x: u8, y: Field) {
-    let _z = x + (y as u8);
-}
-    
diff --git a/crates/nargo_cli/tests/test_data/range_fail/target/main.json b/crates/nargo_cli/tests/test_data/range_fail/target/main.json
deleted file mode 100644
index f3f1b1c656e..00000000000
--- a/crates/nargo_cli/tests/test_data/range_fail/target/main.json
+++ /dev/null
@@ -1 +0,0 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"integer","sign":"unsigned","width":8},"visibility":"private"},{"name":"y","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"x":[1],"y":[2]},"return_type":null,"return_witnesses":[]},"bytecode":[205,146,61,10,194,48,24,134,209,216,234,113,146,38,177,201,230,191,155,160,55,104,107,196,96,85,144,40,174,185,65,218,234,224,1,4,117,242,8,30,192,11,120,17,103,29,156,187,164,5,191,245,131,151,151,231,125,14,245,147,190,119,226,32,90,116,214,251,193,118,21,117,131,56,214,231,73,123,52,236,39,105,165,161,175,61,185,17,145,146,59,161,47,227,237,90,73,177,82,199,204,36,233,171,5,237,14,85,173,35,96,102,140,101,8,130,176,6,30,57,12,64,35,231,89,123,190,245,173,189,145,106,190,20,74,70,153,201,190,92,48,108,18,34,124,79,32,140,2,232,241,144,81,72,104,216,100,136,33,202,232,212,99,24,11,70,152,207,67,238,67,142,8,22,104,70,57,158,253,42,85,11,96,11,210,2,184,216,239,83,166,62,224,79,244,113,157,60,125,156,60,125,220,50,244,1,5,176,117,10,208,199,181,223,199,152,15],"proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/references/Nargo.toml b/crates/nargo_cli/tests/test_data/references/Nargo.toml
similarity index 60%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/references/Nargo.toml
rename to crates/nargo_cli/tests/test_data/references/Nargo.toml
index 09a8dd8e8c8..83fc1fd3811 100644
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/references/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/references/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
+name = "references"
 authors = [""]
 compiler_version = "0.5.1"
 
-[dependencies]
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/references/Prover.toml b/crates/nargo_cli/tests/test_data/references/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/references/Prover.toml
rename to crates/nargo_cli/tests/test_data/references/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/references/src/main.nr b/crates/nargo_cli/tests/test_data/references/src/main.nr
similarity index 54%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/references/src/main.nr
rename to crates/nargo_cli/tests/test_data/references/src/main.nr
index 60b3c372fbd..f70293cb5a6 100644
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/references/src/main.nr
+++ b/crates/nargo_cli/tests/test_data/references/src/main.nr
@@ -6,6 +6,11 @@ fn main(mut x: Field) {
     s.add2();
     assert(s.y == 5);
 
+    // Regression for #1946: Method resolution error when calling &mut methods with a variable of type &mut T
+    let s_ref = &mut s;
+    s_ref.add2();
+    assert(s.y == 7);
+
     // Test that normal mutable variables are still copied
     let mut a = 0;
     mutate_copy(a);
@@ -25,6 +30,9 @@ fn main(mut x: Field) {
     };
     *c.bar.array = [3, 4];
     assert(*c.bar.array == [3, 4]);
+
+    regression_1887();
+    regression_2054();
 }
 
 fn add1(x: &mut Field) {
@@ -53,3 +61,29 @@ impl S {
 fn mutate_copy(mut a: Field) {
     a = 7;
 }
+
+// Previously the `foo.bar` in `foo.bar.mutate()` would insert an automatic dereference
+// of `foo` which caused the method to wrongly be mutating a copy of bar rather than the original.
+fn regression_1887() {
+    let foo = &mut Foo { bar: Bar { x: 0 } };
+    foo.bar.mutate();
+    assert(foo.bar.x == 32);
+}
+
+struct Foo { bar: Bar }
+struct Bar { x: Field }
+
+impl Bar {
+    fn mutate(&mut self) {
+        self.x = 32;
+    }
+}
+
+// Ensure that mutating a variable does not also mutate its copy
+fn regression_2054() {
+    let mut x = 2;
+    let z = x;
+
+    x += 1;
+    assert(z == 2);
+}
diff --git a/crates/nargo_cli/tests/test_data/references/target/main.json b/crates/nargo_cli/tests/test_data/references/target/main.json
new file mode 100644
index 00000000000..f3cd7eb1f69
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/references/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"x":[1]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/+2UXQ6DIBCEF3+qtUl7FRBQeOtVaor3P0JrismG+uZugonzAtFkYGbJdwOAB/yriOszrnKflEBeWg7GhLEPSquX7P3krDR2Gpxyyjr77p3WwRk3+smP0iujg5qt13M0Kwi8wvxT+fUQG/kFcf6Czkvi+5ZoXyWzw/8vDJkgOSft8b7xjfRwjiGVDL4V0D1+rtwV/Ywkssy+01U5g6+G44GvBh7wXdD+BN9Oz5qpqAbyBt+Su6GfESv4qDtdlTP4Wjge+FrgAd8V7U/w7fRsY6HUvh3kDb4ld0c/I1bwUXYqkjtifQBGeiGvEw8AAA==","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/references/target/witness.tr b/crates/nargo_cli/tests/test_data/references/target/witness.tr
new file mode 100644
index 00000000000..5870572eae6
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/references/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/regression/Nargo.toml b/crates/nargo_cli/tests/test_data/regression/Nargo.toml
index e0b467ce5da..0f60b2c20ee 100644
--- a/crates/nargo_cli/tests/test_data/regression/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/regression/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
+name = "regression"
 authors = [""]
 compiler_version = "0.1"
 
-[dependencies]
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/regression/src/main.nr b/crates/nargo_cli/tests/test_data/regression/src/main.nr
index 06e35827d1e..e01888dea37 100644
--- a/crates/nargo_cli/tests/test_data/regression/src/main.nr
+++ b/crates/nargo_cli/tests/test_data/regression/src/main.nr
@@ -78,24 +78,13 @@ fn main(x: [u8; 5], z: Field)
 	assert(len == 5);
 	assert([nib[0], nib[1], nib[2], nib[3], nib[4]] == [15, 1, 12, 11, 8]);
 
-
-}
-
-#[test]
-// Issue 1144
-fn test_1144()
-{
-    main([0x3f, 0x1c, 0xb8, 0x99, 0xab], 3);
-}
-
-// Issue 1169
-fn enc_test()
-{
-    let val1 = [0xb8,0x8f,0x61,0xe6,0xfb,0xda,0x83,0xfb,0xff,0xfa,0xbe,0x36,0x41,0x12,0x13,0x74,0x80,0x39,0x80,0x18,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00];
+	// Issue 1169
+	let val1 = [0xb8,0x8f,0x61,0xe6,0xfb,0xda,0x83,0xfb,0xff,0xfa,0xbe,0x36,0x41,0x12,0x13,0x74,0x80,0x39,0x80,0x18,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00];
     let val1_length = 20;
 
     let enc_val1 = enc(val1,val1_length);
 
     assert(enc_val1.0 == [0x94,0xb8,0x8f,0x61,0xe6,0xfb,0xda,0x83,0xfb,0xff,0xfa,0xbe,0x36,0x41,0x12,0x13,0x74,0x80,0x39,0x80,0x18,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00]);
     assert(enc_val1.1 == 21);
+
 }
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/regression/target/main.json b/crates/nargo_cli/tests/test_data/regression/target/main.json
index 6b81ed9f0d7..02e3d0eb75b 100644
--- a/crates/nargo_cli/tests/test_data/regression/target/main.json
+++ b/crates/nargo_cli/tests/test_data/regression/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"array","length":5,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"},{"name":"z","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"x":[1,2,3,4,5],"z":[6]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"array","length":5,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"},{"name":"z","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"x":[1,2,3,4,5],"z":[6]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/regression/target/witness.tr b/crates/nargo_cli/tests/test_data/regression/target/witness.tr
index 63ba113d074..ff04a722861 100644
Binary files a/crates/nargo_cli/tests/test_data/regression/target/witness.tr and b/crates/nargo_cli/tests/test_data/regression/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/regression_method_cannot_be_found/Nargo.toml b/crates/nargo_cli/tests/test_data/regression_method_cannot_be_found/Nargo.toml
new file mode 100644
index 00000000000..fc1dc4d4ce2
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/regression_method_cannot_be_found/Nargo.toml
@@ -0,0 +1,6 @@
+[package]
+name = "regression_method_cannot_be_found"
+authors = [""]
+compiler_version = "0.1"
+
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/higher_order_functions/Prover.toml b/crates/nargo_cli/tests/test_data/regression_method_cannot_be_found/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data/higher_order_functions/Prover.toml
rename to crates/nargo_cli/tests/test_data/regression_method_cannot_be_found/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/regression_method_cannot_be_found/src/main.nr b/crates/nargo_cli/tests/test_data/regression_method_cannot_be_found/src/main.nr
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/regression_method_cannot_be_found/src/main.nr
rename to crates/nargo_cli/tests/test_data/regression_method_cannot_be_found/src/main.nr
diff --git a/crates/nargo_cli/tests/test_data/regression_method_cannot_be_found/target/main.json b/crates/nargo_cli/tests/test_data/regression_method_cannot_be_found/target/main.json
new file mode 100644
index 00000000000..bcd3cb00647
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/regression_method_cannot_be_found/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[],"param_witnesses":{},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/82Y7WqDMBSG47YaYzTqnWi3pexf72O/9vVjMMoYu3/WrAkc2tMm0HNCAiUW5X3exwMKVkKIShzWLTjG1tbv83VrOc599rva/26OztX0/LkGnlSZq33GymcZ3/uOlLHMys8IrurMjATg16AbTZfDPaxJMzevLkOC/sE1dNfgfA12Seu2VIAZcsN/ycZdr11GE/FvkB5NRv+GjWv/568i/grpoTL6KzaufXIZbcS/RXq0Gf1bNq79CI6X/DXSQ2f012xc++Ayuoh/h/ToMvp3gMvx/Ev1lwX403LvX1xGH/HvkR59Rv8ecDnmn+ovC/Cn5VrrMkzE3yA9TEZ/A7gc779Uf1WAPy3XPrqMIeI/ID2GjP4DG9e+uYwx4j8iPcaM/iPgcrz/U/11Af4cz/9Uf1mAPy138+4ypoj/hPSYMvoHVgNm8P3zufv92oXL4SeccFwBHTjCk89NWyIHcWb9AWoqKyjwEgAA","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/regression_method_cannot_be_found/target/witness.tr b/crates/nargo_cli/tests/test_data/regression_method_cannot_be_found/target/witness.tr
new file mode 100644
index 00000000000..4e90289d5e1
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/regression_method_cannot_be_found/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/scalar_mul/Nargo.toml b/crates/nargo_cli/tests/test_data/scalar_mul/Nargo.toml
index e0b467ce5da..eb1abb258ed 100644
--- a/crates/nargo_cli/tests/test_data/scalar_mul/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/scalar_mul/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
+name = "scalar_mul"
 authors = [""]
 compiler_version = "0.1"
 
-[dependencies]
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/scalar_mul/target/main.json b/crates/nargo_cli/tests/test_data/scalar_mul/target/main.json
index dfc535a4355..f7d6bbe0645 100644
--- a/crates/nargo_cli/tests/test_data/scalar_mul/target/main.json
+++ b/crates/nargo_cli/tests/test_data/scalar_mul/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"a","type":{"kind":"field"},"visibility":"private"},{"name":"a_pub_x","type":{"kind":"field"},"visibility":"public"},{"name":"a_pub_y","type":{"kind":"field"},"visibility":"public"},{"name":"b","type":{"kind":"field"},"visibility":"private"},{"name":"b_pub_x","type":{"kind":"field"},"visibility":"public"},{"name":"b_pub_y","type":{"kind":"field"},"visibility":"public"}],"param_witnesses":{"a":[1],"a_pub_x":[2],"a_pub_y":[3],"b":[4],"b_pub_x":[5],"b_pub_y":[6]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/9WXwU4CMRCGZwFBQASJeHDxInjw1m5btr35Km5c3v8JjE7SJkSP+w9pm2y2pz/z/dOZTt+JqKb/axT/H/Gvhi1dXWgZdbK2b5teG/2pmtB5p6zrTl577bz7arwxvbe+DV1oVdDW9PrsgjlHsRlQK3Gy5m3cV2D2pP1Xd2jsc1yMSop7LsA9E+YeGl8lxP2Yeb4nQtw7MHdaYzA/ssfdAeN6KsQ/4PnWO2AukP7xGVn8fpzf77hfRm10PY6E6vGZ8u6/N0LcNZVRR8D86Bro3/5K/iFmQpR/C6DWSyH+rYDMe2BcSP/Su4FZ7+Me3b+TNrqPrSnvOZK51wLcK5KpHzR/7vnhfiFxv75S3nPFVIj7QGXMFcD86APQvyOVcS+Ogf4tgVpvhfi3ATIfgXEh/UtzBbM+xD26fydtdB/bUt73FnNvBbg3VMZcgczPJOrweeU65zf39CL2HxWOe+VYGAAA","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"a","type":{"kind":"field"},"visibility":"private"},{"name":"a_pub_x","type":{"kind":"field"},"visibility":"public"},{"name":"a_pub_y","type":{"kind":"field"},"visibility":"public"},{"name":"b","type":{"kind":"field"},"visibility":"private"},{"name":"b_pub_x","type":{"kind":"field"},"visibility":"public"},{"name":"b_pub_y","type":{"kind":"field"},"visibility":"public"}],"param_witnesses":{"a":[1],"a_pub_x":[2],"a_pub_y":[3],"b":[4],"b_pub_x":[5],"b_pub_y":[6]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/scalar_mul/target/witness.tr b/crates/nargo_cli/tests/test_data/scalar_mul/target/witness.tr
index 0efa6a5fc24..44c998c2e5b 100644
Binary files a/crates/nargo_cli/tests/test_data/scalar_mul/target/witness.tr and b/crates/nargo_cli/tests/test_data/scalar_mul/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/schnorr/Nargo.toml b/crates/nargo_cli/tests/test_data/schnorr/Nargo.toml
index e0b467ce5da..f6f45f983f5 100644
--- a/crates/nargo_cli/tests/test_data/schnorr/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/schnorr/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
+name = "schnorr"
 authors = [""]
 compiler_version = "0.1"
 
-[dependencies]
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/schnorr/target/main.json b/crates/nargo_cli/tests/test_data/schnorr/target/main.json
index f8532b5eabb..5c80b2f055b 100644
--- a/crates/nargo_cli/tests/test_data/schnorr/target/main.json
+++ b/crates/nargo_cli/tests/test_data/schnorr/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"message","type":{"kind":"array","length":10,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"},{"name":"pub_key_x","type":{"kind":"field"},"visibility":"private"},{"name":"pub_key_y","type":{"kind":"field"},"visibility":"private"},{"name":"signature","type":{"kind":"array","length":64,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"}],"param_witnesses":{"message":[1,2,3,4,5,6,7,8,9,10],"pub_key_x":[11],"pub_key_y":[12],"signature":[13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"message","type":{"kind":"array","length":10,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"},{"name":"pub_key_x","type":{"kind":"field"},"visibility":"private"},{"name":"pub_key_y","type":{"kind":"field"},"visibility":"private"},{"name":"signature","type":{"kind":"array","length":64,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"}],"param_witnesses":{"message":[1,2,3,4,5,6,7,8,9,10],"pub_key_x":[11],"pub_key_y":[12],"signature":[13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/sha256/Nargo.toml b/crates/nargo_cli/tests/test_data/sha256/Nargo.toml
index e0b467ce5da..d29e88bc237 100644
--- a/crates/nargo_cli/tests/test_data/sha256/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/sha256/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
+name = "sha256"
 authors = [""]
 compiler_version = "0.1"
 
-[dependencies]
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/sha256/target/main.json b/crates/nargo_cli/tests/test_data/sha256/target/main.json
index af2ca033909..5fd48602f5b 100644
--- a/crates/nargo_cli/tests/test_data/sha256/target/main.json
+++ b/crates/nargo_cli/tests/test_data/sha256/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"result","type":{"kind":"array","length":32,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"}],"param_witnesses":{"result":[2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33],"x":[1]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"result","type":{"kind":"array","length":32,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"}],"param_witnesses":{"result":[2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33],"x":[1]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/sha256/target/witness.tr b/crates/nargo_cli/tests/test_data/sha256/target/witness.tr
index d733011474b..e0cd7de22c6 100644
Binary files a/crates/nargo_cli/tests/test_data/sha256/target/witness.tr and b/crates/nargo_cli/tests/test_data/sha256/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/sha2_blocks/Nargo.toml b/crates/nargo_cli/tests/test_data/sha2_blocks/Nargo.toml
index e0b467ce5da..5ba3d3dc6db 100644
--- a/crates/nargo_cli/tests/test_data/sha2_blocks/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/sha2_blocks/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
+name = "sha2_blocks"
 authors = [""]
 compiler_version = "0.1"
 
-[dependencies]
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/sha2_blocks/target/main.json b/crates/nargo_cli/tests/test_data/sha2_blocks/target/main.json
new file mode 100644
index 00000000000..d91ddbcca35
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/sha2_blocks/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"array","length":3,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"},{"name":"result256","type":{"kind":"array","length":32,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"},{"name":"result512","type":{"kind":"array","length":64,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"}],"param_witnesses":{"result256":[4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35],"result512":[36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99],"x":[1,2,3]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/sha2_blocks/target/witness.tr b/crates/nargo_cli/tests/test_data/sha2_blocks/target/witness.tr
new file mode 100644
index 00000000000..b2245408b31
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/sha2_blocks/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/sha2_byte/Nargo.toml b/crates/nargo_cli/tests/test_data/sha2_byte/Nargo.toml
index e0b467ce5da..8759ff064f3 100644
--- a/crates/nargo_cli/tests/test_data/sha2_byte/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/sha2_byte/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
+name = "sha2_byte"
 authors = [""]
 compiler_version = "0.1"
 
-[dependencies]
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/sha2_byte/target/main.json b/crates/nargo_cli/tests/test_data/sha2_byte/target/main.json
new file mode 100644
index 00000000000..7bedae5d2d4
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/sha2_byte/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"result256","type":{"kind":"array","length":32,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"},{"name":"result512","type":{"kind":"array","length":64,"type":{"kind":"integer","sign":"unsigned","width":8}},"visibility":"private"}],"param_witnesses":{"result256":[2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33],"result512":[34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97],"x":[1]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/sha2_byte/target/witness.tr b/crates/nargo_cli/tests/test_data/sha2_byte/target/witness.tr
new file mode 100644
index 00000000000..040f1224e20
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/sha2_byte/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/signed_division/Nargo.toml b/crates/nargo_cli/tests/test_data/signed_division/Nargo.toml
new file mode 100644
index 00000000000..b4ec731ad08
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/signed_division/Nargo.toml
@@ -0,0 +1,6 @@
+[package]
+name = "signed_division"
+authors = [""]
+compiler_version = "0.1"
+
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/2_div/Prover.toml b/crates/nargo_cli/tests/test_data/signed_division/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/2_div/Prover.toml
rename to crates/nargo_cli/tests/test_data/signed_division/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/signed_division/src/main.nr b/crates/nargo_cli/tests/test_data/signed_division/src/main.nr
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/signed_division/src/main.nr
rename to crates/nargo_cli/tests/test_data/signed_division/src/main.nr
diff --git a/crates/nargo_cli/tests/test_data/signed_division/target/main.json b/crates/nargo_cli/tests/test_data/signed_division/target/main.json
new file mode 100644
index 00000000000..73fa10811d2
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/signed_division/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"integer","sign":"signed","width":32},"visibility":"private"},{"name":"y","type":{"kind":"integer","sign":"signed","width":32},"visibility":"private"},{"name":"z","type":{"kind":"integer","sign":"signed","width":32},"visibility":"private"}],"param_witnesses":{"x":[1],"y":[2],"z":[3]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/signed_division/target/witness.tr b/crates/nargo_cli/tests/test_data/signed_division/target/witness.tr
new file mode 100644
index 00000000000..dc3e7aee633
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/signed_division/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/simple_add_and_ret_arr/Nargo.toml b/crates/nargo_cli/tests/test_data/simple_add_and_ret_arr/Nargo.toml
new file mode 100644
index 00000000000..67826a05fea
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/simple_add_and_ret_arr/Nargo.toml
@@ -0,0 +1,6 @@
+[package]
+name = "simple_add_and_ret_arr"
+authors = [""]
+compiler_version = "0.6.0"
+
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_add_and_ret_arr/Prover.toml b/crates/nargo_cli/tests/test_data/simple_add_and_ret_arr/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/simple_add_and_ret_arr/Prover.toml
rename to crates/nargo_cli/tests/test_data/simple_add_and_ret_arr/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_add_and_ret_arr/src/main.nr b/crates/nargo_cli/tests/test_data/simple_add_and_ret_arr/src/main.nr
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/simple_add_and_ret_arr/src/main.nr
rename to crates/nargo_cli/tests/test_data/simple_add_and_ret_arr/src/main.nr
diff --git a/crates/nargo_cli/tests/test_data/simple_add_and_ret_arr/target/main.json b/crates/nargo_cli/tests/test_data/simple_add_and_ret_arr/target/main.json
new file mode 100644
index 00000000000..be53f4d8947
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/simple_add_and_ret_arr/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"x":[1]},"return_type":{"kind":"array","length":1,"type":{"kind":"field"}},"return_witnesses":[2]},"bytecode":"H4sIAAAAAAAA/62QMRLAIAgE0XwIBBS6fCVO8P9PSGPhJGW8Zrudmz0AIMF3efKcxH+jtLgYq0i0EsR0YfFuiqK9Ghmp6V2MOUysefeGTsJBQ53HlOXNv+DVIC0NHsnD9V4gAQAA","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/simple_add_and_ret_arr/target/witness.tr b/crates/nargo_cli/tests/test_data/simple_add_and_ret_arr/target/witness.tr
new file mode 100644
index 00000000000..35e05b7622b
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/simple_add_and_ret_arr/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/simple_array_param/Nargo.toml b/crates/nargo_cli/tests/test_data/simple_array_param/Nargo.toml
new file mode 100644
index 00000000000..f92a75d2cb8
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/simple_array_param/Nargo.toml
@@ -0,0 +1,6 @@
+[package]
+name = "simple_array_param"
+authors = [""]
+compiler_version = "0.6.0"
+
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_array_param/Prover.toml b/crates/nargo_cli/tests/test_data/simple_array_param/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/simple_array_param/Prover.toml
rename to crates/nargo_cli/tests/test_data/simple_array_param/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_array_param/src/main.nr b/crates/nargo_cli/tests/test_data/simple_array_param/src/main.nr
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/simple_array_param/src/main.nr
rename to crates/nargo_cli/tests/test_data/simple_array_param/src/main.nr
diff --git a/crates/nargo_cli/tests/test_data/simple_array_param/target/main.json b/crates/nargo_cli/tests/test_data/simple_array_param/target/main.json
new file mode 100644
index 00000000000..3950749e85a
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/simple_array_param/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"xs","type":{"kind":"array","length":2,"type":{"kind":"field"}},"visibility":"private"}],"param_witnesses":{"xs":[1,2]},"return_type":{"kind":"field"},"return_witnesses":[2]},"bytecode":"H4sIAAAAAAAA/12KsQkAAAjDUsX/X3awgtglDSQBMSszTPl/5/j2DZaRF3BIAAAA","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/simple_array_param/target/witness.tr b/crates/nargo_cli/tests/test_data/simple_array_param/target/witness.tr
new file mode 100644
index 00000000000..a8e277ea795
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/simple_array_param/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/simple_bitwise/Nargo.toml b/crates/nargo_cli/tests/test_data/simple_bitwise/Nargo.toml
new file mode 100644
index 00000000000..12f2b6989ec
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/simple_bitwise/Nargo.toml
@@ -0,0 +1,6 @@
+[package]
+name = "simple_bitwise"
+authors = [""]
+compiler_version = "0.6.0"
+
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_bitwise/Prover.toml b/crates/nargo_cli/tests/test_data/simple_bitwise/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/simple_bitwise/Prover.toml
rename to crates/nargo_cli/tests/test_data/simple_bitwise/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_bitwise/src/main.nr b/crates/nargo_cli/tests/test_data/simple_bitwise/src/main.nr
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/simple_bitwise/src/main.nr
rename to crates/nargo_cli/tests/test_data/simple_bitwise/src/main.nr
diff --git a/crates/nargo_cli/tests/test_data/simple_bitwise/target/main.json b/crates/nargo_cli/tests/test_data/simple_bitwise/target/main.json
new file mode 100644
index 00000000000..92af4b63d4c
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/simple_bitwise/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"a","type":{"kind":"boolean"},"visibility":"private"},{"name":"b","type":{"kind":"boolean"},"visibility":"private"},{"name":"c","type":{"kind":"integer","sign":"unsigned","width":8},"visibility":"private"},{"name":"d","type":{"kind":"integer","sign":"unsigned","width":8},"visibility":"private"}],"param_witnesses":{"a":[1],"b":[2],"c":[3],"d":[4]},"return_type":{"kind":"integer","sign":"unsigned","width":8},"return_witnesses":[21]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/simple_bitwise/target/witness.tr b/crates/nargo_cli/tests/test_data/simple_bitwise/target/witness.tr
new file mode 100644
index 00000000000..506cdcb8d87
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/simple_bitwise/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/simple_comparison/Nargo.toml b/crates/nargo_cli/tests/test_data/simple_comparison/Nargo.toml
new file mode 100644
index 00000000000..0af7070d974
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/simple_comparison/Nargo.toml
@@ -0,0 +1,6 @@
+[package]
+name = "simple_comparison"
+authors = [""]
+compiler_version = "0.1"
+
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_comparison/Prover.toml b/crates/nargo_cli/tests/test_data/simple_comparison/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/simple_comparison/Prover.toml
rename to crates/nargo_cli/tests/test_data/simple_comparison/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_comparison/src/main.nr b/crates/nargo_cli/tests/test_data/simple_comparison/src/main.nr
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/simple_comparison/src/main.nr
rename to crates/nargo_cli/tests/test_data/simple_comparison/src/main.nr
diff --git a/crates/nargo_cli/tests/test_data/simple_comparison/target/main.json b/crates/nargo_cli/tests/test_data/simple_comparison/target/main.json
new file mode 100644
index 00000000000..dcbf9a8cb95
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/simple_comparison/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"y","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"x":[1],"y":[2]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/81UWw6DIBBc8YFpk57BI7A8FP56lZrisXuWYoq2If1jMU5CgJ+Z7OzsXgHgBh+wcCr4Ynvf4y3ygBUdl4AEmby4PerA0SQ+kJuwGr0KvaIQi6JDolkXbIASo9Z+kh4VPoR0szVCm3m0aNFY85RWKW+1ndzsJuFQK4+LcXKJXHU+l4pcoqGrUZQOMYPzh7gNHB0cEOI2CXF3QIgZYYhbwhB3UC7EjNjD5lx178EF2rzuvDxw9HDAQPAosv1X0SHRpB6IUs3M5bpAmU2Z+pe7BDhhzT1hXwn8+ztYFY1/e80caBcf/MxPijdUC8hSrwoAAA==","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/simple_comparison/target/witness.tr b/crates/nargo_cli/tests/test_data/simple_comparison/target/witness.tr
new file mode 100644
index 00000000000..6a8a4673e7c
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/simple_comparison/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/double_verify_proof/Nargo.toml b/crates/nargo_cli/tests/test_data/simple_mut/Nargo.toml
similarity index 60%
rename from crates/nargo_cli/tests/test_data/double_verify_proof/Nargo.toml
rename to crates/nargo_cli/tests/test_data/simple_mut/Nargo.toml
index 670888e37cd..2d92d708f8d 100644
--- a/crates/nargo_cli/tests/test_data/double_verify_proof/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/simple_mut/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
+name = "simple_mut"
 authors = [""]
 compiler_version = "0.6.0"
 
-[dependencies]
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_mut/Prover.toml b/crates/nargo_cli/tests/test_data/simple_mut/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/simple_mut/Prover.toml
rename to crates/nargo_cli/tests/test_data/simple_mut/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_mut/src/main.nr b/crates/nargo_cli/tests/test_data/simple_mut/src/main.nr
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/simple_mut/src/main.nr
rename to crates/nargo_cli/tests/test_data/simple_mut/src/main.nr
diff --git a/crates/nargo_cli/tests/test_data/simple_mut/target/main.json b/crates/nargo_cli/tests/test_data/simple_mut/target/main.json
new file mode 100644
index 00000000000..f6d2dc9e121
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/simple_mut/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"x":[1]},"return_type":{"kind":"field"},"return_witnesses":[2]},"bytecode":"H4sIAAAAAAAA/62Quw2AMAxEHVjI38TuWIUIZ/8RaIIUiRKuue7p7u0AUOCdbfYxG7+FysISrKrZOEnoRI7uhmq9OjmZ28Uukq7eokfDIJWkYSFjwrb/dvHzfXVQFgc33HLiBSABAAA=","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/simple_mut/target/witness.tr b/crates/nargo_cli/tests/test_data/simple_mut/target/witness.tr
new file mode 100644
index 00000000000..9e7641cea1e
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/simple_mut/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/array_sort/Nargo.toml b/crates/nargo_cli/tests/test_data/simple_not/Nargo.toml
similarity index 60%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/array_sort/Nargo.toml
rename to crates/nargo_cli/tests/test_data/simple_not/Nargo.toml
index 670888e37cd..d64ccb54191 100644
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/array_sort/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/simple_not/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
+name = "simple_not"
 authors = [""]
 compiler_version = "0.6.0"
 
-[dependencies]
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_not/Prover.toml b/crates/nargo_cli/tests/test_data/simple_not/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/simple_not/Prover.toml
rename to crates/nargo_cli/tests/test_data/simple_not/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_not/src/main.nr b/crates/nargo_cli/tests/test_data/simple_not/src/main.nr
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/simple_not/src/main.nr
rename to crates/nargo_cli/tests/test_data/simple_not/src/main.nr
diff --git a/crates/nargo_cli/tests/test_data/simple_not/target/main.json b/crates/nargo_cli/tests/test_data/simple_not/target/main.json
new file mode 100644
index 00000000000..6985d5c7fac
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/simple_not/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"boolean"},"visibility":"private"}],"param_witnesses":{"x":[1]},"return_type":{"kind":"boolean"},"return_witnesses":[2]},"bytecode":"H4sIAAAAAAAA/62QUQrAIAxDq7tQa1tt/3aVyfT+RxhDB7Lf7UFpPkIC2QAgwiBMHeatPJ59fsYs0kpqxHRg8mqKojUbGanpmYy5mVjx6gWdhBt1de44CD9mxSULv0Fh2QJe+u65AK6JrSgwAQAA","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/simple_not/target/witness.tr b/crates/nargo_cli/tests/test_data/simple_not/target/witness.tr
new file mode 100644
index 00000000000..a8e277ea795
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/simple_not/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_add_and_ret_arr/Nargo.toml b/crates/nargo_cli/tests/test_data/simple_print/Nargo.toml
similarity index 58%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/simple_add_and_ret_arr/Nargo.toml
rename to crates/nargo_cli/tests/test_data/simple_print/Nargo.toml
index 670888e37cd..85429d3a080 100644
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_add_and_ret_arr/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/simple_print/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
+name = "simple_print"
 authors = [""]
 compiler_version = "0.6.0"
 
-[dependencies]
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_print/Prover.toml b/crates/nargo_cli/tests/test_data/simple_print/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/simple_print/Prover.toml
rename to crates/nargo_cli/tests/test_data/simple_print/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_print/src/main.nr b/crates/nargo_cli/tests/test_data/simple_print/src/main.nr
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/simple_print/src/main.nr
rename to crates/nargo_cli/tests/test_data/simple_print/src/main.nr
diff --git a/crates/nargo_cli/tests/test_data/simple_print/target/main.json b/crates/nargo_cli/tests/test_data/simple_print/target/main.json
new file mode 100644
index 00000000000..a34f39ce9c1
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/simple_print/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"y","type":{"kind":"field"},"visibility":"public"}],"param_witnesses":{"x":[1],"y":[2]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/simple_print/target/witness.tr b/crates/nargo_cli/tests/test_data/simple_print/target/witness.tr
new file mode 100644
index 00000000000..35e05b7622b
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/simple_print/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/simple_program_addition/Nargo.toml b/crates/nargo_cli/tests/test_data/simple_program_addition/Nargo.toml
new file mode 100644
index 00000000000..98fbb603178
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/simple_program_addition/Nargo.toml
@@ -0,0 +1,6 @@
+[package]
+name = "simple_program_addition"
+authors = [""]
+compiler_version = "0.1"
+
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_program_addition/Prover.toml b/crates/nargo_cli/tests/test_data/simple_program_addition/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/simple_program_addition/Prover.toml
rename to crates/nargo_cli/tests/test_data/simple_program_addition/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_program_addition/src/main.nr b/crates/nargo_cli/tests/test_data/simple_program_addition/src/main.nr
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/simple_program_addition/src/main.nr
rename to crates/nargo_cli/tests/test_data/simple_program_addition/src/main.nr
diff --git a/crates/nargo_cli/tests/test_data/simple_program_addition/target/main.json b/crates/nargo_cli/tests/test_data/simple_program_addition/target/main.json
new file mode 100644
index 00000000000..633bb338133
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/simple_program_addition/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"x":[1]},"return_type":{"kind":"field"},"return_witnesses":[2]},"bytecode":"H4sIAAAAAAAA/62QMRLAIAgE0XwIBBS6fCVO8P9PSGPhJGW8Zrudmz0AIMF3efKcxH+jtLgYq0i0EsR0YfFuiqK9Ghmp6V2MOUysefeGTsJBQ53HlOXNv+DVIC0NHsnD9V4gAQAA","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/simple_program_addition/target/witness.tr b/crates/nargo_cli/tests/test_data/simple_program_addition/target/witness.tr
new file mode 100644
index 00000000000..94ea8c8f2b1
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/simple_program_addition/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/simple_program_no_body/Nargo.toml b/crates/nargo_cli/tests/test_data/simple_program_no_body/Nargo.toml
new file mode 100644
index 00000000000..4c0150d0472
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/simple_program_no_body/Nargo.toml
@@ -0,0 +1,6 @@
+[package]
+name = "simple_program_no_body"
+authors = [""]
+compiler_version = "0.1"
+
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_program_no_body/Prover.toml b/crates/nargo_cli/tests/test_data/simple_program_no_body/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/simple_program_no_body/Prover.toml
rename to crates/nargo_cli/tests/test_data/simple_program_no_body/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_program_no_body/src/main.nr b/crates/nargo_cli/tests/test_data/simple_program_no_body/src/main.nr
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/simple_program_no_body/src/main.nr
rename to crates/nargo_cli/tests/test_data/simple_program_no_body/src/main.nr
diff --git a/crates/nargo_cli/tests/test_data/simple_program_no_body/target/main.json b/crates/nargo_cli/tests/test_data/simple_program_no_body/target/main.json
new file mode 100644
index 00000000000..5b107212932
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/simple_program_no_body/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"_x","type":{"kind":"field"},"visibility":"private"},{"name":"_y","type":{"kind":"field"},"visibility":"public"}],"param_witnesses":{"_x":[1],"_y":[2]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/2NmQABGJBrGZkKSBwDu6/8ELAAAAA==","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/simple_program_no_body/target/witness.tr b/crates/nargo_cli/tests/test_data/simple_program_no_body/target/witness.tr
new file mode 100644
index 00000000000..94ea8c8f2b1
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/simple_program_no_body/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/simple_radix/Nargo.toml b/crates/nargo_cli/tests/test_data/simple_radix/Nargo.toml
new file mode 100644
index 00000000000..85eb02f85b9
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/simple_radix/Nargo.toml
@@ -0,0 +1,6 @@
+[package]
+name = "simple_radix"
+authors = [""]
+compiler_version = "0.6.0"
+
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_radix/Prover.toml b/crates/nargo_cli/tests/test_data/simple_radix/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/simple_radix/Prover.toml
rename to crates/nargo_cli/tests/test_data/simple_radix/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_radix/src/main.nr b/crates/nargo_cli/tests/test_data/simple_radix/src/main.nr
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/simple_radix/src/main.nr
rename to crates/nargo_cli/tests/test_data/simple_radix/src/main.nr
diff --git a/crates/nargo_cli/tests/test_data/simple_radix/target/main.json b/crates/nargo_cli/tests/test_data/simple_radix/target/main.json
new file mode 100644
index 00000000000..07753c79e3a
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/simple_radix/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"x":[1]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/+1Wy27DIBBcHrGbRs2lPwIGYrj1V2oF//8nVFawtEFRD/EQ+ZCRLBYfhp1ZPPKZiL7pBlmeFaKsP2U122AFjsso1vNS61ILpkOwvar2mulboRrqdebifR6HbJ39NUOaYjA+TJdoow0xXIfoXI4+jmlKo0nWu2znkNxcyCSQ6ws4h//8e7bPPN+gcFxXDZwr0r/1XtZAf3sS2DPv98BqXVb54E50DTRRdU7t4/nBO+jhLYZ0aMDbES48Wunu8DO6C6e9e7pCgvtUwD57INergq+nNsH3wep38G3k7IuhaN4j7Tv4Ft1H/IyaBh/S01eFAPDv7y4EPln9DoGNnLoYiuY90b5DYNF9ws+oaQggPRVVjxx/RQgGeJ8QAAA=","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/simple_radix/target/witness.tr b/crates/nargo_cli/tests/test_data/simple_radix/target/witness.tr
new file mode 100644
index 00000000000..83055738290
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/simple_radix/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/simple_range/Nargo.toml b/crates/nargo_cli/tests/test_data/simple_range/Nargo.toml
new file mode 100644
index 00000000000..dafaddbb146
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/simple_range/Nargo.toml
@@ -0,0 +1,6 @@
+[package]
+name = "simple_range"
+authors = [""]
+compiler_version = "0.1"
+
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_range/Prover.toml b/crates/nargo_cli/tests/test_data/simple_range/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/simple_range/Prover.toml
rename to crates/nargo_cli/tests/test_data/simple_range/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_range/src/main.nr b/crates/nargo_cli/tests/test_data/simple_range/src/main.nr
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/simple_range/src/main.nr
rename to crates/nargo_cli/tests/test_data/simple_range/src/main.nr
diff --git a/crates/nargo_cli/tests/test_data/simple_range/target/main.json b/crates/nargo_cli/tests/test_data/simple_range/target/main.json
new file mode 100644
index 00000000000..2546e4583dc
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/simple_range/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"x":[1]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/2NiQABGNBoZAAAl2cYIKAAAAA==","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/simple_range/target/witness.tr b/crates/nargo_cli/tests/test_data/simple_range/target/witness.tr
new file mode 100644
index 00000000000..335f5adfd77
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/simple_range/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/simple_shield/Nargo.toml b/crates/nargo_cli/tests/test_data/simple_shield/Nargo.toml
index 5082c6e12ec..8b22da7ef10 100644
--- a/crates/nargo_cli/tests/test_data/simple_shield/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/simple_shield/Nargo.toml
@@ -1,4 +1,5 @@
 [package]
+name = "simple_shield"
 authors = [""]
 compiler_version = "0.1"
 
diff --git a/crates/nargo_cli/tests/test_data/simple_shield/target/main.json b/crates/nargo_cli/tests/test_data/simple_shield/target/main.json
index 098e7f54e91..963e1ded6ad 100644
--- a/crates/nargo_cli/tests/test_data/simple_shield/target/main.json
+++ b/crates/nargo_cli/tests/test_data/simple_shield/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"priv_key","type":{"kind":"field"},"visibility":"private"},{"name":"note_root","type":{"kind":"field"},"visibility":"public"},{"name":"index","type":{"kind":"field"},"visibility":"private"},{"name":"note_hash_path","type":{"kind":"array","length":3,"type":{"kind":"field"}},"visibility":"private"},{"name":"to_pubkey_x","type":{"kind":"field"},"visibility":"private"},{"name":"to_pubkey_y","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"index":[3],"note_hash_path":[4,5,6],"note_root":[2],"priv_key":[1],"to_pubkey_x":[7],"to_pubkey_y":[8]},"return_type":{"kind":"array","length":2,"type":{"kind":"field"}},"return_witnesses":[13,15]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"priv_key","type":{"kind":"field"},"visibility":"private"},{"name":"note_root","type":{"kind":"field"},"visibility":"public"},{"name":"index","type":{"kind":"field"},"visibility":"private"},{"name":"note_hash_path","type":{"kind":"array","length":3,"type":{"kind":"field"}},"visibility":"private"},{"name":"to_pubkey_x","type":{"kind":"field"},"visibility":"private"},{"name":"to_pubkey_y","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"index":[3],"note_hash_path":[4,5,6],"note_root":[2],"priv_key":[1],"to_pubkey_x":[7],"to_pubkey_y":[8]},"return_type":{"kind":"array","length":2,"type":{"kind":"field"}},"return_witnesses":[13,15]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/simple_shield/target/witness.tr b/crates/nargo_cli/tests/test_data/simple_shield/target/witness.tr
index a86187ab643..a2b9c6c8f76 100644
Binary files a/crates/nargo_cli/tests/test_data/simple_shield/target/witness.tr and b/crates/nargo_cli/tests/test_data/simple_shield/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/simple_shift_left_right/Nargo.toml b/crates/nargo_cli/tests/test_data/simple_shift_left_right/Nargo.toml
new file mode 100644
index 00000000000..7d1e4cf39c0
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/simple_shift_left_right/Nargo.toml
@@ -0,0 +1,6 @@
+[package]
+name = "simple_shift_left_right"
+authors = [""]
+compiler_version = "0.1"
+
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_shift_left_right/Prover.toml b/crates/nargo_cli/tests/test_data/simple_shift_left_right/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/simple_shift_left_right/Prover.toml
rename to crates/nargo_cli/tests/test_data/simple_shift_left_right/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_shift_left_right/src/main.nr b/crates/nargo_cli/tests/test_data/simple_shift_left_right/src/main.nr
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/simple_shift_left_right/src/main.nr
rename to crates/nargo_cli/tests/test_data/simple_shift_left_right/src/main.nr
diff --git a/crates/nargo_cli/tests/test_data/simple_shift_left_right/target/main.json b/crates/nargo_cli/tests/test_data/simple_shift_left_right/target/main.json
new file mode 100644
index 00000000000..96caf4b87da
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/simple_shift_left_right/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"}],"param_witnesses":{"x":[1]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/9WWOw7CMAyG3QflJTEwMTBwBLtJaLJxFSrS+x+BBlIpjZjARmApSqpKfvz+5GQLAHt4WjGuMu6n5AzJ/2CXuONnRgWfL4TMePwSBg2qTAd2Ecq4jkkTQtA6i1kJNkDhWWvftZ4UXbF1vTWoTX+2ZMlYc2utUt5q27nedehIK0+DccoPD6OSwdcQE6v4akRZiAl/GGKaDoGjBXwB4jqu6TsEPYEkxPMGvAleG8GjmhHiBfwLxEicuYIEYyPKzehjCV+AOAQ6JBCHoCuQhHjegM8mMVLDCPESZMDg1o/z9uHUb8Wo38tnCPAPA86c03zXyXl62ZQvmGgEaoIsTq7jDgQHi1ST1gJ+N8AHv1TdG/4ezYbTL2taZDmmdgfT0ibxzA0AAA==","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/simple_shift_left_right/target/witness.tr b/crates/nargo_cli/tests/test_data/simple_shift_left_right/target/witness.tr
new file mode 100644
index 00000000000..9470bbe781a
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/simple_shift_left_right/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/unconstrained_empty/Nargo.toml b/crates/nargo_cli/tests/test_data/slices/Nargo.toml
similarity index 80%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/unconstrained_empty/Nargo.toml
rename to crates/nargo_cli/tests/test_data/slices/Nargo.toml
index 6028aef164e..0b6a804ea1d 100644
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/unconstrained_empty/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/slices/Nargo.toml
@@ -1,4 +1,5 @@
 [package]
+name = "slices"
 authors = [""]
 compiler_version = "0.6.0"
 
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/xor/Prover.toml b/crates/nargo_cli/tests/test_data/slices/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/xor/Prover.toml
rename to crates/nargo_cli/tests/test_data/slices/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/slices/src/main.nr b/crates/nargo_cli/tests/test_data/slices/src/main.nr
similarity index 94%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/slices/src/main.nr
rename to crates/nargo_cli/tests/test_data/slices/src/main.nr
index a0460aafb40..f97078a2143 100644
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/slices/src/main.nr
+++ b/crates/nargo_cli/tests/test_data/slices/src/main.nr
@@ -4,7 +4,7 @@ fn main(x : Field, y : pub Field) {
     /// TODO(#1889): Using slices in if statements where the condition is a witness
     /// is not yet supported
 
-    let mut slice: [Field] = [0; 2];
+    let mut slice = [0; 2];
     assert(slice[0] == 0);
     assert(slice[0] != 1);
     slice[0] = x;
@@ -15,7 +15,7 @@ fn main(x : Field, y : pub Field) {
     assert(slice_plus_10[2] != 8);
     assert(slice_plus_10.len() == 3);
 
-    let mut new_slice: [Field] = [];
+    let mut new_slice = [];
     for i in 0..5 {
         new_slice = new_slice.push_back(i);
     }
diff --git a/crates/nargo_cli/tests/test_data/slices/target/main.json b/crates/nargo_cli/tests/test_data/slices/target/main.json
new file mode 100644
index 00000000000..c9f42181ffb
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/slices/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"y","type":{"kind":"field"},"visibility":"public"}],"param_witnesses":{"x":[1],"y":[2]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/+2UPQ7CMAyF3b9QGDiL3SSNs3EVKtL7HwEVBckqFUsd1AEvjjJ88bPjdwaAC3xGnfMtZ9wXVAuWxdG5FIZElu44xIk9Oj+NTEye/WNgaxM7DnGKASM5m2j20c4Z1iiw0vyKsLCqDf2Vsv5Gj4Wy3nbjXIu7JmdTQBOs3ln38bpxp/p4iSG1Bbgd6H3+Uro7/RmhQB6+p+84svEZUDO++CvjM1DG+E7i/De+nUyTG6rN7eHYxrfo7vVn9NX49vahB/2FqkSdcomeTvjvyB4KAAA=","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/slices/target/witness.tr b/crates/nargo_cli/tests/test_data/slices/target/witness.tr
new file mode 100644
index 00000000000..b1aecf36289
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/slices/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/strings/Nargo.toml b/crates/nargo_cli/tests/test_data/strings/Nargo.toml
index e0b467ce5da..9b29990eb35 100644
--- a/crates/nargo_cli/tests/test_data/strings/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/strings/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
+name = "strings"
 authors = [""]
 compiler_version = "0.1"
 
-[dependencies]
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/strings/target/main.json b/crates/nargo_cli/tests/test_data/strings/target/main.json
index edc2fa3679d..a1c7b8ec6e7 100644
--- a/crates/nargo_cli/tests/test_data/strings/target/main.json
+++ b/crates/nargo_cli/tests/test_data/strings/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"message","type":{"kind":"string","length":11},"visibility":"public"},{"name":"y","type":{"kind":"field"},"visibility":"private"},{"name":"hex_as_string","type":{"kind":"string","length":4},"visibility":"private"},{"name":"hex_as_field","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"hex_as_field":[17],"hex_as_string":[13,14,15,16],"message":[1,2,3,4,5,6,7,8,9,10,11],"y":[12]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"message","type":{"kind":"string","length":11},"visibility":"public"},{"name":"y","type":{"kind":"field"},"visibility":"private"},{"name":"hex_as_string","type":{"kind":"string","length":4},"visibility":"private"},{"name":"hex_as_field","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"hex_as_field":[17],"hex_as_string":[13,14,15,16],"message":[1,2,3,4,5,6,7,8,9,10,11],"y":[12]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/strings/target/witness.tr b/crates/nargo_cli/tests/test_data/strings/target/witness.tr
index cafac454211..d0f4c3b600f 100644
Binary files a/crates/nargo_cli/tests/test_data/strings/target/witness.tr and b/crates/nargo_cli/tests/test_data/strings/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/struct/Nargo.toml b/crates/nargo_cli/tests/test_data/struct/Nargo.toml
index d9434868157..949d3e860b3 100644
--- a/crates/nargo_cli/tests/test_data/struct/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/struct/Nargo.toml
@@ -1,7 +1,6 @@
+[package]
+name = "struct"
+authors = [""]
+compiler_version = "0.1"
 
-        [package]
-        authors = [""]
-        compiler_version = "0.1"
-    
-        [dependencies]
-    
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/struct/src/main.nr b/crates/nargo_cli/tests/test_data/struct/src/main.nr
index 6d61393920d..a6d3eddd8d5 100644
--- a/crates/nargo_cli/tests/test_data/struct/src/main.nr
+++ b/crates/nargo_cli/tests/test_data/struct/src/main.nr
@@ -74,4 +74,6 @@ fn main(x: Field, y: Field) {
     let six = legs + eyes as Field;
 
     assert(six == 6);
+
+    let Animal { legs: _, eyes: _ } = get_dog();
 }
diff --git a/crates/nargo_cli/tests/test_data/struct/target/main.json b/crates/nargo_cli/tests/test_data/struct/target/main.json
index 69e4032a46e..d7cfe325973 100644
--- a/crates/nargo_cli/tests/test_data/struct/target/main.json
+++ b/crates/nargo_cli/tests/test_data/struct/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"y","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"x":[1],"y":[2]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/9WVQQ7CIBBFB2trtdaNF4ECLey8io30/kcwxGKILvsnoX8Dq59582cyNyK6078O6/tYXy1HY8I0BKXVUw5+dlYaO49OOWWdfQ1O6+CMm/zsJ+mV0UEt1utFfiSAXlXmJTcqcUbP4/oXP+xym1TyFuCe1sA+cHHXDNzI/CkTmh+dTxJ6Nw9ArwbYv8QZPU9MGSVv9Iy2VPZuRu6WgbuhfewmOp+kClwn8m4i9/xM+BscPS9MeSdv9Lx3VPaeR+6OgRuZP2UqOJ/vPYo1XpnmNHmj+9BT2XMa/XoGbkH7uEfofHK9AaBB4yHkDQAA","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"y","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"x":[1],"y":[2]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/+1Wyw6CMBDcguID9eKPtLSV9uavSIT//wRDLMmKxEunBhLm0k0P09lZmOyFiK70jSyc93BqeTOmratWafWQlW+clcY2N6ecss4+K6d164yrfeNr6ZXRreqs1518QwC5csYlI9FziYn+xah/GQeF1Mz1bibqjN3l4SwS9ESjd8Y+XibuoI+nGNImAe+WcB9/qr63+BlJRjl7Tweggy8DchXgmf8j+ICaP4Jvx+o1+CI5i2AomndP8w6+vu89fkZJgw/t6YAcrBO58SFD9EDL2x6RmrneI6vXEI3kPARD0bwlzTtE+75L/Ix+hmisDyUtLwQEpQmBE6vXEIjkFMFQNO+Z5h0CPd8ZP6OkmxTS04xp5D/PgBeuN2XbaBMAAA==","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/struct/target/witness.tr b/crates/nargo_cli/tests/test_data/struct/target/witness.tr
index 5f0d45c73eb..71a6b98c022 100644
Binary files a/crates/nargo_cli/tests/test_data/struct/target/witness.tr and b/crates/nargo_cli/tests/test_data/struct/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/struct_array_inputs/Nargo.toml b/crates/nargo_cli/tests/test_data/struct_array_inputs/Nargo.toml
new file mode 100644
index 00000000000..040b5359f33
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/struct_array_inputs/Nargo.toml
@@ -0,0 +1,6 @@
+[package]
+name = "struct_array_inputs"
+authors = [""]
+compiler_version = "0.6.0"
+
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/struct_array_inputs/Prover.toml b/crates/nargo_cli/tests/test_data/struct_array_inputs/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/struct_array_inputs/Prover.toml
rename to crates/nargo_cli/tests/test_data/struct_array_inputs/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/struct_array_inputs/src/main.nr b/crates/nargo_cli/tests/test_data/struct_array_inputs/src/main.nr
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/struct_array_inputs/src/main.nr
rename to crates/nargo_cli/tests/test_data/struct_array_inputs/src/main.nr
diff --git a/crates/nargo_cli/tests/test_data/struct_array_inputs/target/main.json b/crates/nargo_cli/tests/test_data/struct_array_inputs/target/main.json
new file mode 100644
index 00000000000..ae9889ac047
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/struct_array_inputs/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"foos","type":{"kind":"array","length":3,"type":{"kind":"struct","fields":[{"name":"bar","type":{"kind":"field"}},{"name":"baz","type":{"kind":"field"}}]}},"visibility":"private"}],"param_witnesses":{"foos":[1,2,3,4,5,6]},"return_type":{"kind":"field"},"return_witnesses":[7]},"bytecode":"H4sIAAAAAAAA/62QWwqAQAhFp3fL0VEb/WsrDU37X0JFBn0GdUHOx4WjOIYQ6nClc/bOyrvmmNb7u7vTOGcnfAt2P7r6h4tgYi4pFiRcIFpWAZY8KSqKyhqVqChrsmwJDJkKbmK0uWz47y54+9/Kee7eAaHW1ZqoAQAA","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/struct_array_inputs/target/witness.tr b/crates/nargo_cli/tests/test_data/struct_array_inputs/target/witness.tr
new file mode 100644
index 00000000000..82307dcb96e
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/struct_array_inputs/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/struct_fields_ordering/Nargo.toml b/crates/nargo_cli/tests/test_data/struct_fields_ordering/Nargo.toml
index e0b467ce5da..5d2e0d8d9d1 100644
--- a/crates/nargo_cli/tests/test_data/struct_fields_ordering/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/struct_fields_ordering/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
+name = "struct_fields_ordering"
 authors = [""]
 compiler_version = "0.1"
 
-[dependencies]
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/struct_fields_ordering/target/main.json b/crates/nargo_cli/tests/test_data/struct_fields_ordering/target/main.json
index 112aaada86b..a3477f884ca 100644
--- a/crates/nargo_cli/tests/test_data/struct_fields_ordering/target/main.json
+++ b/crates/nargo_cli/tests/test_data/struct_fields_ordering/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"y","type":{"kind":"struct","fields":[{"name":"foo","type":{"kind":"integer","sign":"unsigned","width":32}},{"name":"bar","type":{"kind":"field"}}]},"visibility":"public"}],"param_witnesses":{"y":[1,2]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/9WTXQ7CIBCEt9TWGi/hEVh+yvLmVYrC/Y+gKCToa5dEJyH7NtlvhzkBwBneGp5PlHmBT4kyr2XKfcKh8dJyNSY6FVHjJpUPZKWxYSUktGTvirSOZMj54J30aHTEZL1OxWxk8IrppVvlzJ6H5i6c7NX723fvHSa+HWUv7qkD98jMDZ1y586nirubgjGbGdi6uVXO7HnslFH15v6jC/x2NzP30oF7hv/oJmc+otlRNDs/AKbH/RhsBwAA","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"y","type":{"kind":"struct","fields":[{"name":"foo","type":{"kind":"integer","sign":"unsigned","width":32}},{"name":"bar","type":{"kind":"field"}}]},"visibility":"public"}],"param_witnesses":{"y":[1,2]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/+1UUQ7CIAztYMMZE8/gEWDABn9eZVN2/yPotCaV7G/F7MOXkJJ+vPa18I4AcII3qucRGC/wDYHxilFvg6kIl9W9c2nokrFm1F2cgtfOT30wwfjg712wNgUXhjjFQUfjbDKzj3ZGMsnAleYXbhL156iY9Us+Lk37rVfuguQkRlVAE2R18jmeV3KsxUssqS7A2wDf4y+lu+HfkSaUu5/pB9zGJxj7VMBmfOOvjE9BGeM7kPvf+DZyKhwoN28L+za+RXfLv6Oixsc90wWC9Eo/0QP0CrogLgoAAA==","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/struct_fields_ordering/target/witness.tr b/crates/nargo_cli/tests/test_data/struct_fields_ordering/target/witness.tr
index 37193dab882..4ca94e980e2 100644
Binary files a/crates/nargo_cli/tests/test_data/struct_fields_ordering/target/witness.tr and b/crates/nargo_cli/tests/test_data/struct_fields_ordering/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/struct_inputs/Nargo.toml b/crates/nargo_cli/tests/test_data/struct_inputs/Nargo.toml
index e0b467ce5da..ee51fec2bcd 100644
--- a/crates/nargo_cli/tests/test_data/struct_inputs/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/struct_inputs/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
+name = "struct_inputs"
 authors = [""]
 compiler_version = "0.1"
 
-[dependencies]
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/struct_inputs/target/main.json b/crates/nargo_cli/tests/test_data/struct_inputs/target/main.json
index ab228a047c4..925e2f2a873 100644
--- a/crates/nargo_cli/tests/test_data/struct_inputs/target/main.json
+++ b/crates/nargo_cli/tests/test_data/struct_inputs/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"y","type":{"kind":"struct","fields":[{"name":"foo","type":{"kind":"integer","sign":"unsigned","width":32}},{"name":"bar","type":{"kind":"field"}},{"name":"message","type":{"kind":"string","length":5}}]},"visibility":"public"},{"name":"z","type":{"kind":"struct","fields":[{"name":"val","type":{"kind":"field"}},{"name":"array","type":{"kind":"array","length":2,"type":{"kind":"field"}}},{"name":"message","type":{"kind":"string","length":5}}]},"visibility":"public"},{"name":"a","type":{"kind":"struct","fields":[{"name":"bar_struct","type":{"kind":"struct","fields":[{"name":"val","type":{"kind":"field"}},{"name":"array","type":{"kind":"array","length":2,"type":{"kind":"field"}}},{"name":"message","type":{"kind":"string","length":5}}]}},{"name":"baz","type":{"kind":"field"}}]},"visibility":"public"}],"param_witnesses":{"a":[17,18,19,20,21,22,23,24,25],"x":[1],"y":[2,3,4,5,6,7,8],"z":[9,10,11,12,13,14,15,16]},"return_type":{"kind":"field"},"return_witnesses":[19]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"y","type":{"kind":"struct","fields":[{"name":"foo","type":{"kind":"integer","sign":"unsigned","width":32}},{"name":"bar","type":{"kind":"field"}},{"name":"message","type":{"kind":"string","length":5}}]},"visibility":"public"},{"name":"z","type":{"kind":"struct","fields":[{"name":"val","type":{"kind":"field"}},{"name":"array","type":{"kind":"array","length":2,"type":{"kind":"field"}}},{"name":"message","type":{"kind":"string","length":5}}]},"visibility":"public"},{"name":"a","type":{"kind":"struct","fields":[{"name":"bar_struct","type":{"kind":"struct","fields":[{"name":"val","type":{"kind":"field"}},{"name":"array","type":{"kind":"array","length":2,"type":{"kind":"field"}}},{"name":"message","type":{"kind":"string","length":5}}]}},{"name":"baz","type":{"kind":"field"}}]},"visibility":"public"}],"param_witnesses":{"a":[17,18,19,20,21,22,23,24,25],"x":[1],"y":[2,3,4,5,6,7,8],"z":[9,10,11,12,13,14,15,16]},"return_type":{"kind":"field"},"return_witnesses":[19]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/struct_inputs/target/witness.tr b/crates/nargo_cli/tests/test_data/struct_inputs/target/witness.tr
index 24c7a71935c..6ddf16de41f 100644
Binary files a/crates/nargo_cli/tests/test_data/struct_inputs/target/witness.tr and b/crates/nargo_cli/tests/test_data/struct_inputs/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/submodules/Nargo.toml b/crates/nargo_cli/tests/test_data/submodules/Nargo.toml
index d9434868157..f38965dfa11 100644
--- a/crates/nargo_cli/tests/test_data/submodules/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/submodules/Nargo.toml
@@ -1,7 +1,6 @@
+[package]
+name = "submodules"
+authors = [""]
+compiler_version = "0.1"
 
-        [package]
-        authors = [""]
-        compiler_version = "0.1"
-    
-        [dependencies]
-    
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/submodules/target/main.json b/crates/nargo_cli/tests/test_data/submodules/target/main.json
index c58636cac92..08d52b8608a 100644
--- a/crates/nargo_cli/tests/test_data/submodules/target/main.json
+++ b/crates/nargo_cli/tests/test_data/submodules/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"integer","sign":"unsigned","width":1},"visibility":"private"},{"name":"y","type":{"kind":"integer","sign":"unsigned","width":1},"visibility":"private"}],"param_witnesses":{"x":[1],"y":[2]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/82TQQ4CIQxFCzh6nZbCUHZeRSJz/yPoJDUat9Mm8zfd/fTx6BUAbvBN0HnXicdCQTv/exnXUmbLk5gemPuQiqWOVUioSn1mYZ5SpPXRG3YqPGmrnTctDnY7ogd3fHdEB+7ozG3hZd8xOfwjSzdWvMnYLejbXcDnHj/d1t4XOPc97tyLA3cy5gYn79Z+fvMCBjjRikQGAAA=","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"integer","sign":"unsigned","width":1},"visibility":"private"},{"name":"y","type":{"kind":"integer","sign":"unsigned","width":1},"visibility":"private"}],"param_witnesses":{"x":[1],"y":[2]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/81TSQ7DIAw0ZOmtb7FZgrn1K0Ul/39CKyVIFsqtRspIyODD2J4xKwA84ID5HXtGI94tByK+zuhxC6EmV8nTG10uHDHEsjExRY4fx95XDpxyyQkzBV9pj9nveKDVmDpe/A9kFLms4ryTMlfzQ8IoaznpcaHsd764W5FrO7EOmAm6Or2Oz4ucavERJs0DeBfQW9hRcy/6HqGgvLWmVvQoP0/DF2hpqqLhBQAA","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/submodules/target/witness.tr b/crates/nargo_cli/tests/test_data/submodules/target/witness.tr
index d0f5179dee6..2d05a243aef 100644
Binary files a/crates/nargo_cli/tests/test_data/submodules/target/witness.tr and b/crates/nargo_cli/tests/test_data/submodules/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/to_be_bytes/Nargo.toml b/crates/nargo_cli/tests/test_data/to_be_bytes/Nargo.toml
index e0b467ce5da..7c9cbc964c1 100644
--- a/crates/nargo_cli/tests/test_data/to_be_bytes/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/to_be_bytes/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
+name = "to_be_bytes"
 authors = [""]
 compiler_version = "0.1"
 
-[dependencies]
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/to_be_bytes/target/main.json b/crates/nargo_cli/tests/test_data/to_be_bytes/target/main.json
index cb53e6b16c3..38bc23f8742 100644
--- a/crates/nargo_cli/tests/test_data/to_be_bytes/target/main.json
+++ b/crates/nargo_cli/tests/test_data/to_be_bytes/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"x":[1]},"return_type":{"kind":"array","length":31,"type":{"kind":"integer","sign":"unsigned","width":8}},"return_witnesses":[32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"x":[1]},"return_type":{"kind":"array","length":31,"type":{"kind":"integer","sign":"unsigned","width":8}},"return_witnesses":[32,31,30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/to_be_bytes/target/witness.tr b/crates/nargo_cli/tests/test_data/to_be_bytes/target/witness.tr
index e897895b6b0..201f92cb1b1 100644
Binary files a/crates/nargo_cli/tests/test_data/to_be_bytes/target/witness.tr and b/crates/nargo_cli/tests/test_data/to_be_bytes/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/to_bits/Nargo.toml b/crates/nargo_cli/tests/test_data/to_bits/Nargo.toml
index 5a02ffe4729..3cd694dac88 100644
--- a/crates/nargo_cli/tests/test_data/to_bits/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/to_bits/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
+name = "to_bits"
 authors = [""]
 compiler_version = "0.7.0"
 
-[dependencies]
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/to_bits/target/main.json b/crates/nargo_cli/tests/test_data/to_bits/target/main.json
index d1dbb3968e9..4c3bb072cb3 100644
--- a/crates/nargo_cli/tests/test_data/to_bits/target/main.json
+++ b/crates/nargo_cli/tests/test_data/to_bits/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[],"param_witnesses":{},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/2NkwA0A9IrFgRwAAAA=","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[],"param_witnesses":{},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/2NkIAwAQGbG/yQAAAA=","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/to_bytes_integration/Nargo.toml b/crates/nargo_cli/tests/test_data/to_bytes_integration/Nargo.toml
index 5082c6e12ec..40da1e922ae 100644
--- a/crates/nargo_cli/tests/test_data/to_bytes_integration/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/to_bytes_integration/Nargo.toml
@@ -1,4 +1,5 @@
 [package]
+name = "to_bytes_integration"
 authors = [""]
 compiler_version = "0.1"
 
diff --git a/crates/nargo_cli/tests/test_data/to_bytes_integration/Prover.toml b/crates/nargo_cli/tests/test_data/to_bytes_integration/Prover.toml
index 23f7acea449..bc4693e434a 100644
--- a/crates/nargo_cli/tests/test_data/to_bytes_integration/Prover.toml
+++ b/crates/nargo_cli/tests/test_data/to_bytes_integration/Prover.toml
@@ -1,2 +1,2 @@
 x = "2040124"
-_y = "0x2000000000000000000000000000000000000000000000000000000000000000"
+a = "0x2000000000000000000000000000000000000000000000000000000000000000"
diff --git a/crates/nargo_cli/tests/test_data/to_bytes_integration/src/main.nr b/crates/nargo_cli/tests/test_data/to_bytes_integration/src/main.nr
index 36e6d430e2e..f76df026db7 100644
--- a/crates/nargo_cli/tests/test_data/to_bytes_integration/src/main.nr
+++ b/crates/nargo_cli/tests/test_data/to_bytes_integration/src/main.nr
@@ -1,10 +1,8 @@
 use dep::std;
 
-fn main(x : Field, _y: Field)  {
-    // The result of this byte array will be big-endian
+fn main(x : Field, a: Field)  {
     let y: Field = 2040124;
     let be_byte_array = y.to_be_bytes(31);
-    // The result of this byte array will be little-endian
     let le_byte_array = x.to_le_bytes(31);
     
     assert(le_byte_array[0] == 60);
@@ -23,5 +21,5 @@ fn main(x : Field, _y: Field)  {
     assert(z_bits[0] == 0);
     assert(p_bits[100] == z_bits[100]);
 
-   _y.to_le_bits(std::field::modulus_num_bits() as u32);
-}
\ No newline at end of file
+    a.to_le_bits(std::field::modulus_num_bits() as u32);
+}
diff --git a/crates/nargo_cli/tests/test_data/to_bytes_integration/target/main.json b/crates/nargo_cli/tests/test_data/to_bytes_integration/target/main.json
index ce7aa66235b..71fa3e08251 100644
--- a/crates/nargo_cli/tests/test_data/to_bytes_integration/target/main.json
+++ b/crates/nargo_cli/tests/test_data/to_bytes_integration/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"_y","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"_y":[2],"x":[1]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"a","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"a":[2],"x":[1]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/to_bytes_integration/target/witness.tr b/crates/nargo_cli/tests/test_data/to_bytes_integration/target/witness.tr
index 46a52df3cfe..28d06219edf 100644
Binary files a/crates/nargo_cli/tests/test_data/to_bytes_integration/target/witness.tr and b/crates/nargo_cli/tests/test_data/to_bytes_integration/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/to_le_bytes/Nargo.toml b/crates/nargo_cli/tests/test_data/to_le_bytes/Nargo.toml
index e0b467ce5da..1ad2aac253d 100644
--- a/crates/nargo_cli/tests/test_data/to_le_bytes/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/to_le_bytes/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
+name = "to_le_bytes"
 authors = [""]
 compiler_version = "0.1"
 
-[dependencies]
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/to_le_bytes/target/main.json b/crates/nargo_cli/tests/test_data/to_le_bytes/target/main.json
index 28832c921eb..37b3b3adfc9 100644
--- a/crates/nargo_cli/tests/test_data/to_le_bytes/target/main.json
+++ b/crates/nargo_cli/tests/test_data/to_le_bytes/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"x":[1]},"return_type":{"kind":"array","length":4,"type":{"kind":"integer","sign":"unsigned","width":8}},"return_witnesses":[2,3,4,33]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"x":[1]},"return_type":{"kind":"array","length":4,"type":{"kind":"integer","sign":"unsigned","width":8}},"return_witnesses":[2,3,4,33]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/to_le_bytes/target/witness.tr b/crates/nargo_cli/tests/test_data/to_le_bytes/target/witness.tr
index aed1127db2e..4e1cabb0a84 100644
Binary files a/crates/nargo_cli/tests/test_data/to_le_bytes/target/witness.tr and b/crates/nargo_cli/tests/test_data/to_le_bytes/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/tuples/Nargo.toml b/crates/nargo_cli/tests/test_data/tuples/Nargo.toml
index 5082c6e12ec..1377570c1a4 100644
--- a/crates/nargo_cli/tests/test_data/tuples/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/tuples/Nargo.toml
@@ -1,4 +1,5 @@
 [package]
+name = "tuples"
 authors = [""]
 compiler_version = "0.1"
 
diff --git a/crates/nargo_cli/tests/test_data/tuples/src/main.nr b/crates/nargo_cli/tests/test_data/tuples/src/main.nr
index b1d310b1412..45d8380372b 100644
--- a/crates/nargo_cli/tests/test_data/tuples/src/main.nr
+++ b/crates/nargo_cli/tests/test_data/tuples/src/main.nr
@@ -19,7 +19,7 @@ fn main(x: Field, y: Field) {
 
     // Test mutating tuples
     let mut mutable = ((0, 0), 1, 2, 3);
-    mutable.0 = pair;
+    mutable.0 = (x, y);
     mutable.2 = 7;
     assert(mutable.0.0 == 1);
     assert(mutable.0.1 == 0);
diff --git a/crates/nargo_cli/tests/test_data/tuples/target/main.json b/crates/nargo_cli/tests/test_data/tuples/target/main.json
index 27061601d2e..a971c0ba0d0 100644
--- a/crates/nargo_cli/tests/test_data/tuples/target/main.json
+++ b/crates/nargo_cli/tests/test_data/tuples/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"y","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"x":[1],"y":[2]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"y","type":{"kind":"field"},"visibility":"private"}],"param_witnesses":{"x":[1],"y":[2]},"return_type":null,"return_witnesses":[]},"bytecode":"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","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/tuples/target/witness.tr b/crates/nargo_cli/tests/test_data/tuples/target/witness.tr
index 733d80f6135..9cf062282e8 100644
Binary files a/crates/nargo_cli/tests/test_data/tuples/target/witness.tr and b/crates/nargo_cli/tests/test_data/tuples/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/unconstrained_empty/Nargo.toml b/crates/nargo_cli/tests/test_data/unconstrained_empty/Nargo.toml
new file mode 100644
index 00000000000..63689725523
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/unconstrained_empty/Nargo.toml
@@ -0,0 +1,6 @@
+[package]
+name = "unconstrained_empty"
+authors = [""]
+compiler_version = "0.6.0"
+
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/unconstrained_empty/Prover.toml b/crates/nargo_cli/tests/test_data/unconstrained_empty/Prover.toml
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/unconstrained_empty/Prover.toml
rename to crates/nargo_cli/tests/test_data/unconstrained_empty/Prover.toml
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/unconstrained_empty/src/main.nr b/crates/nargo_cli/tests/test_data/unconstrained_empty/src/main.nr
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/unconstrained_empty/src/main.nr
rename to crates/nargo_cli/tests/test_data/unconstrained_empty/src/main.nr
diff --git a/crates/nargo_cli/tests/test_data/unconstrained_empty/target/main.json b/crates/nargo_cli/tests/test_data/unconstrained_empty/target/main.json
new file mode 100644
index 00000000000..d6e9953cd42
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/unconstrained_empty/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[],"param_witnesses":{},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/62Puw0AIAhEj6jYOYtu4P5TqZHiGip4CbmE4j4CQPAp8GmmSr9tOoModcjyfH2reY17nTKyByw4HCZCYW5dAQAA","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/unconstrained_empty/target/witness.tr b/crates/nargo_cli/tests/test_data/unconstrained_empty/target/witness.tr
new file mode 100644
index 00000000000..4e90289d5e1
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/unconstrained_empty/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_pedersen/Nargo.toml b/crates/nargo_cli/tests/test_data/unit/Nargo.toml
similarity index 82%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/brillig_pedersen/Nargo.toml
rename to crates/nargo_cli/tests/test_data/unit/Nargo.toml
index fb93b9aa2a7..433e130173e 100644
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_pedersen/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/unit/Nargo.toml
@@ -1,6 +1,6 @@
 [package]
+name = "unit"
 authors = [""]
 compiler_version = "0.1"
 
 [dependencies]
-    
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/unit/src/main.nr b/crates/nargo_cli/tests/test_data/unit/src/main.nr
new file mode 100644
index 00000000000..2cb1f7d7c66
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/unit/src/main.nr
@@ -0,0 +1,14 @@
+fn main() {
+    let _a = ();
+    let _b: () = _a;
+    let _c: () = ();
+    let _d = f1();
+    let _e: () = f2();
+    let _f: () = f3();
+    let _g = f4();
+}
+
+fn f1() {}
+fn f2() { () }
+fn f3() -> () {}
+fn f4() -> () { () }
diff --git a/crates/nargo_cli/tests/test_data/unit/target/main.json b/crates/nargo_cli/tests/test_data/unit/target/main.json
new file mode 100644
index 00000000000..4c3bb072cb3
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/unit/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[],"param_witnesses":{},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/2NkIAwAQGbG/yQAAAA=","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/unit/target/witness.tr b/crates/nargo_cli/tests/test_data/unit/target/witness.tr
new file mode 100644
index 00000000000..4e90289d5e1
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/unit/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/vectors/Nargo.toml b/crates/nargo_cli/tests/test_data/vectors/Nargo.toml
similarity index 62%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/vectors/Nargo.toml
rename to crates/nargo_cli/tests/test_data/vectors/Nargo.toml
index 7cae77988e3..7f768c1fd23 100644
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/vectors/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/vectors/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
+name = "vectors"
 authors = [""]
 compiler_version = "0.7.1"
 
-[dependencies]
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/vectors/Prover.toml b/crates/nargo_cli/tests/test_data/vectors/Prover.toml
new file mode 100644
index 00000000000..f28f2f8cc48
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/vectors/Prover.toml
@@ -0,0 +1,2 @@
+x = "5"
+y = "10"
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/vectors/src/main.nr b/crates/nargo_cli/tests/test_data/vectors/src/main.nr
similarity index 100%
rename from crates/nargo_cli/tests/test_data_ssa_refactor/vectors/src/main.nr
rename to crates/nargo_cli/tests/test_data/vectors/src/main.nr
diff --git a/crates/nargo_cli/tests/test_data/vectors/target/main.json b/crates/nargo_cli/tests/test_data/vectors/target/main.json
new file mode 100644
index 00000000000..358da43be69
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/vectors/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"y","type":{"kind":"field"},"visibility":"public"}],"param_witnesses":{"x":[1],"y":[2]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/2NmQABGJBrGZkKSBwDu6/8ELAAAAA==","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/vectors/target/witness.tr b/crates/nargo_cli/tests/test_data/vectors/target/witness.tr
new file mode 100644
index 00000000000..3530c6f59c1
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/vectors/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/workspace/crates/a/Nargo.toml b/crates/nargo_cli/tests/test_data/workspace/crates/a/Nargo.toml
index dc0c2f8917c..5ff1a743e3d 100644
--- a/crates/nargo_cli/tests/test_data/workspace/crates/a/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/workspace/crates/a/Nargo.toml
@@ -1,4 +1,5 @@
 [package]
+name = "a"
 authors = [""]
 compiler_version = "0.8.0"
 
diff --git a/crates/nargo_cli/tests/test_data/workspace/crates/b/Nargo.toml b/crates/nargo_cli/tests/test_data/workspace/crates/b/Nargo.toml
index dc0c2f8917c..8ae69a781eb 100644
--- a/crates/nargo_cli/tests/test_data/workspace/crates/b/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/workspace/crates/b/Nargo.toml
@@ -1,4 +1,5 @@
 [package]
+name = "b"
 authors = [""]
 compiler_version = "0.8.0"
 
diff --git a/crates/nargo_cli/tests/test_data/workspace_default_member/a/Nargo.toml b/crates/nargo_cli/tests/test_data/workspace_default_member/a/Nargo.toml
index dc0c2f8917c..5ff1a743e3d 100644
--- a/crates/nargo_cli/tests/test_data/workspace_default_member/a/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/workspace_default_member/a/Nargo.toml
@@ -1,4 +1,5 @@
 [package]
+name = "a"
 authors = [""]
 compiler_version = "0.8.0"
 
diff --git a/crates/nargo_cli/tests/test_data/workspace_default_member/target/main.json b/crates/nargo_cli/tests/test_data/workspace_default_member/target/main.json
new file mode 100644
index 00000000000..5b013404f52
--- /dev/null
+++ b/crates/nargo_cli/tests/test_data/workspace_default_member/target/main.json
@@ -0,0 +1 @@
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"field"},"visibility":"private"},{"name":"y","type":{"kind":"field"},"visibility":"public"}],"param_witnesses":{"x":[1],"y":[2]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/7WTMRLEIAhFMYkp9ywgGrHbq6yz5v5H2JkdCyaxC9LgWDw+H9gBwMM91p7fPeOzIKdYjEeMLYdGTB8MpUrCmOohJJQkfYMwN4mSSy0ZC0VudKbCZ4cthqzVrsc/yw28dMZeWmrWerfBexnsxD6hJ7jUufr4GvyZFp8xpG0C14Pd8s/q29vPCBXypvmpDx7sD8opnfqIfsM1RNtxBQAA","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/workspace_default_member/target/witness.tr b/crates/nargo_cli/tests/test_data/workspace_default_member/target/witness.tr
new file mode 100644
index 00000000000..a51064da4b6
Binary files /dev/null and b/crates/nargo_cli/tests/test_data/workspace_default_member/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data/xor/Nargo.toml b/crates/nargo_cli/tests/test_data/xor/Nargo.toml
index e0b467ce5da..b1bc5f3a4dd 100644
--- a/crates/nargo_cli/tests/test_data/xor/Nargo.toml
+++ b/crates/nargo_cli/tests/test_data/xor/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
+name = "xor"
 authors = [""]
 compiler_version = "0.1"
 
-[dependencies]
\ No newline at end of file
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_data/xor/target/main.json b/crates/nargo_cli/tests/test_data/xor/target/main.json
index a35aab91a50..31f5d0e3f1a 100644
--- a/crates/nargo_cli/tests/test_data/xor/target/main.json
+++ b/crates/nargo_cli/tests/test_data/xor/target/main.json
@@ -1 +1 @@
-{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"},{"name":"y","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"public"}],"param_witnesses":{"x":[1],"y":[2]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/82RbwrDIAzFU9t1O8aOkBit8duuMpne/wj7p5AN+qkW+kBCDPx4LzkDwAW+Gl7P1HpVvVH9oObtf4RfmVpvteI20ahYjItzOdhMTHe0MYlH59MiJOTFP6wwZ3ESYooBIznOVHzkUmFTB1YuH4WW8808qR32zN7Y/9yte5j7ecS9cs875J4654aVux/oPtS8GeX3CXNzhvn4AwAA","proving_key":null,"verification_key":null}
\ No newline at end of file
+{"backend":"acvm-backend-barretenberg","abi":{"parameters":[{"name":"x","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"private"},{"name":"y","type":{"kind":"integer","sign":"unsigned","width":32},"visibility":"public"}],"param_witnesses":{"x":[1],"y":[2]},"return_type":null,"return_witnesses":[]},"bytecode":"H4sIAAAAAAAA/7VTSw4CIQwt80FXnsEjtAMMZedVnAj3P4JGMak4uykvIaUlef08egKAM3xgXmeo9ir8QfhGvH/jI/xiqPZWLR4DjYLL4ep9jksmR3dc0sYBfdhWJqbA4bGwc5k9x7SliIm8y1RCcqWSTQpcubwRxzqLFka5/0mPC2W9s7hPjXYgdLUdeoImTzvHy05MNXkPkeYOvBb0Pn+vvq2+Rigo/2o+OgcL+gtlRJ1yiZ6k/dzRYQUAAA==","proving_key":null,"verification_key":null}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data/xor/target/witness.tr b/crates/nargo_cli/tests/test_data/xor/target/witness.tr
index 723b311edfa..33813f242f6 100644
Binary files a/crates/nargo_cli/tests/test_data/xor/target/witness.tr and b/crates/nargo_cli/tests/test_data/xor/target/witness.tr differ
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/1327_concrete_in_generic/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/1327_concrete_in_generic/Nargo.toml
deleted file mode 100644
index 670888e37cd..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/1327_concrete_in_generic/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.6.0"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/1_mul/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/1_mul/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/1_mul/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/1_mul/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/1_mul/Prover.toml
deleted file mode 100644
index 9bff601c75a..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/1_mul/Prover.toml
+++ /dev/null
@@ -1,3 +0,0 @@
-x = "3"
-y = "4"
-z = "429981696"
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/1_mul/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/1_mul/src/main.nr
deleted file mode 100644
index 4587b4b5947..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/1_mul/src/main.nr
+++ /dev/null
@@ -1,9 +0,0 @@
-// Test unsafe integer multiplication with overflow: 12^8 = 429 981 696
-// The circuit should handle properly the growth of the bit size
-fn main(mut x: u32, y: u32, z: u32) {
-    x *= y;
-    x *= x;  //144
-    x *= x;  //20736
-    x *= x;  //429 981 696
-    assert(x == z);
-}
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/2_div/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/2_div/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/2_div/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/2_div/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/2_div/src/main.nr
deleted file mode 100644
index ff0dee755cc..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/2_div/src/main.nr
+++ /dev/null
@@ -1,7 +0,0 @@
-// Testing integer division: 7/3 = 2
-fn main(mut x: u32, y: u32, z: u32) {
-    let a = x % y;
-    assert(x / y == z);
-    assert(a == x - z*y);
-    assert((50 as u64) % (9 as u64) == 5);
-}
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/3_add/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/3_add/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/3_add/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/3_add/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/3_add/Prover.toml
deleted file mode 100644
index 5d777c023db..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/3_add/Prover.toml
+++ /dev/null
@@ -1,3 +0,0 @@
-x = "3"
-y = "4"
-z = "7"
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/3_add/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/3_add/src/main.nr
deleted file mode 100644
index 2884415b81a..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/3_add/src/main.nr
+++ /dev/null
@@ -1,8 +0,0 @@
-// Test integer addition: 3 + 4 = 7
-fn main(mut x: u32, y: u32, z: u32) {
-    x += y;
-    assert(x == z);
-
-    x *= 8;
-    assert(x>9);
-}
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/4_sub/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/4_sub/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/4_sub/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/4_sub/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/4_sub/Prover.toml
deleted file mode 100644
index 1240475dee3..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/4_sub/Prover.toml
+++ /dev/null
@@ -1,3 +0,0 @@
-x = "12"
-y = "2418266113"
-z = "1876701195"
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/4_sub/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/4_sub/src/main.nr
deleted file mode 100644
index 80fc0177e41..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/4_sub/src/main.nr
+++ /dev/null
@@ -1,5 +0,0 @@
-// Test unsafe integer subtraction with underflow: 12 - 2418266113 = 1876701195 modulo 2^32
-fn main(mut x: u32, y: u32, z: u32) {
-    x -= y;
-    assert(x == z);
-}
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/5_over/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/5_over/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/5_over/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/5_over/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/5_over/Prover.toml
deleted file mode 100644
index 9a1986329ca..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/5_over/Prover.toml
+++ /dev/null
@@ -1,2 +0,0 @@
-x = "43046721"
-y = "3793632897"
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/5_over/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/5_over/src/main.nr
deleted file mode 100644
index 4fdff16c5c0..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/5_over/src/main.nr
+++ /dev/null
@@ -1,9 +0,0 @@
-// Test unsafe integer arithmetic
-// Test odd bits integer
-fn main(mut x: u32, y: u32) {
-    x = x * x;
-    assert(y == x);
-
-    let c:u3 = 2;
-    assert(c > x as u3);
-}
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/6/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/6/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/6/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/6/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/6/Prover.toml
deleted file mode 100644
index 1c52aef063c..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/6/Prover.toml
+++ /dev/null
@@ -1,39 +0,0 @@
-
-# hello as bytes
-# used : https://emn178.github.io/online-tools/sha256.html
-x = [104, 101, 108, 108, 111]
-
-result = [
-        0x2c,
-        0xf2,
-        0x4d,
-        0xba,
-        0x5f,
-        0xb0,
-        0xa3,
-        0x0e,
-        0x26,
-        0xe8,
-        0x3b,
-        0x2a,
-        0xc5,
-        0xb9,
-        0xe2,
-        0x9e,
-        0x1b,
-        0x16,
-        0x1e,
-        0x5c,
-        0x1f,
-        0xa7,
-        0x42,
-        0x5e,
-        0x73,
-        0x04,
-        0x33,
-        0x62,
-        0x93,
-        0x8b,
-        0x98,
-        0x24,
-]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/6/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/6/src/main.nr
deleted file mode 100644
index 8b350de16c1..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/6/src/main.nr
+++ /dev/null
@@ -1,20 +0,0 @@
-// Sha256 circuit where the input is 5 bytes
-// not five field elements since sha256 operates over
-// bytes.
-//
-// If you do not cast, it will take all the bytes from the field element!
-
-// Mimc input is an array of field elements
-// The function is called mimc_bn254 to emphasize its parameters are chosen for bn254 curve, it should be used only with a proving system using the same curve (e.g Plonk from Aztec)
-use dep::std;
-
-fn main(x: [u8; 5], result: pub [u8; 32]) {
-    let mut digest = std::hash::sha256(x);
-    digest[0] = 5 as u8;
-    digest = std::hash::sha256(x);
-    assert(digest == result);
-
-    let y = [12,45,78,41];
-    let h = std::hash::mimc_bn254(y);
-   assert(h == 18226366069841799622585958305961373004333097209608110160936134895615261821931);
-}
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/6_array/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/6_array/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/6_array/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/6_array/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/6_array/Prover.toml
deleted file mode 100644
index 2e2ed310ba1..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/6_array/Prover.toml
+++ /dev/null
@@ -1,8 +0,0 @@
-x = [104, 101, 108, 108, 111]
-y = [10, 81, 18, 48, 0]
-z = "59"
-t = "10"
-
-#7128
-#15309
-#16349
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/6_array/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/6_array/src/main.nr
deleted file mode 100644
index b9ed6b6f345..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/6_array/src/main.nr
+++ /dev/null
@@ -1,53 +0,0 @@
-//Basic tests for arrays 
-fn main(x: [u32; 5], y: [u32; 5], mut z: u32, t: u32) {  
-    let mut c = 2301;
-    z = y[4];
-    //Test 1: 
-    for i in 0..5 {
-       c = z*z*y[i];
-       z -= c;
-    }
-    assert(z==0);    //y[4]=0, so c and z are always 0
-
-    //Test 2:
-    c = 2301 as u32;
-    for i in 0..5 {
-       c = t+2 as u32;
-       c = z*z*x[i];
-       z += x[i]*y[i] - c;
-    }
-    assert(z==3814912846);
-
-    //Test 3:
-    c = 2300001 as u32;
-    z = y[4];
-    for i in 0..5 {
-       z  = z + x[i]*y[i];
-        for _i in 0..3 {
-            c = i as u32 - 2 as u32;
-            z *= c;
-        }
-    }
-    assert(z==41472);
-
-    //Test 4:
-    z = y[4];
-    for i in 0..3 {
-       z += x[i] * y[i];
-       for j in 0..2 {
-          z += x[i+j] - y[i+j];
-       }
-    }
-    assert(z ==11539);
-
-    //Test 5:
-    let cc = if z < 1 { x } else { y };
-    assert(cc[0] == y[0]);
-
-    // Test 6: for-each loops
-    for y_elem in y {
-        for x_elem in x {
-            assert(x_elem != y_elem);
-        }
-    }
-}
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/7/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/7/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/7/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/7/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/7/Prover.toml
deleted file mode 100644
index bc3784726d2..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/7/Prover.toml
+++ /dev/null
@@ -1,38 +0,0 @@
-
-# hello as bytes
-# https://toolkitbay.com/tkb/tool/BLAKE2s_256
-x = [104, 101, 108, 108, 111]
-result = [
-        0x19,
-        0x21,
-        0x3b,
-        0xac,
-        0xc5,
-        0x8d,
-        0xee,
-        0x6d,
-        0xbd,
-        0xe3,
-        0xce,
-        0xb9,
-        0xa4,
-        0x7c,
-        0xbb,
-        0x33,
-        0x0b,
-        0x3d,
-        0x86,
-        0xf8,
-        0xcc,
-        0xa8,
-        0x99,
-        0x7e,
-        0xb0,
-        0x0b,
-        0xe4,
-        0x56,
-        0xf1,
-        0x40,
-        0xca,
-        0x25,
-]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/7/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/7/src/main.nr
deleted file mode 100644
index a6bba978644..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/7/src/main.nr
+++ /dev/null
@@ -1,10 +0,0 @@
-// This is the same as Blake2s example.
-//
-// Pre-alpha dependencies must now be prefixed with the word "dep".
-// The line below indicates that we would like to pull in the standard library dependency.
-use dep::std;
-
-fn main(x: [u8; 5], result: [u8; 32]) {
-    let digest = std::hash::blake2s(x);
-    assert(digest == result);
-}
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/7_function/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/7_function/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/7_function/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/7_function/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/7_function/Prover.toml
deleted file mode 100644
index 9140e7f7530..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/7_function/Prover.toml
+++ /dev/null
@@ -1,6 +0,0 @@
-x = "59"
-y = "5"
-a = "1"
-
-arr1=[3320379920, 1938147428, 1942509796, 1795943184, 24853, 0, 0, 0, 0]
-arr2=[2912727897, 3590519536, 1687587470, 3896107618, 1092831095, 0, 0, 0, 0]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/7_function/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/7_function/src/main.nr
deleted file mode 100644
index 26ecf6dda28..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/7_function/src/main.nr
+++ /dev/null
@@ -1,151 +0,0 @@
-//Tests for function calling 
-use dep::std;
-
-fn f1(mut x: Field) -> Field {
-    x = x + 1;
-    x = f2(x);
-    x
-}
-
-fn f2(mut x: Field) -> Field{
-    x += 2;
-    x
-}
-
-// Simple example
-fn test0(mut a: Field) {
-    a = f2(a);
-    assert(a == 3);
-}
-
-// Nested call
-fn test1(mut a: Field) {
-    a = f1(a);
-    assert(a == 4);
-}
-
-fn test2(z: Field, t: u32 ) { 
-    let a = z + t as Field;
-    assert(a == 64);
-    let e = pow(z, t as Field);
-    assert(e == 714924299);
-}
-
-fn pow(base: Field, exponent: Field) -> Field {
-    let mut r = 1 as Field;
-    let b = exponent.to_le_bits(32 as u32);
-    for i in 1..33 {
-        r = r*r;
-        r = (b[32-i] as Field) * (r * base) + (1 - b[32-i] as Field) * r;
-    }
-    r
-}
-
-fn test3(x: [u8; 3]) -> [u8; 3] {
-    let mut buffer = [0 as u8; 3];
-    for i in 0..3 {
-        buffer[i] = x[i];
-    }
-    assert(buffer == x);
-    buffer
-}
-
-fn test_multiple(x: u32, y: u32) -> (u32, u32) {
-    (y,x)
-}
-
-fn test_multiple2() -> my_struct {
-    my_struct { a: 5 as u32, b: 7 as u32 }
-}
-
-fn test_multiple3(x: u32, y: u32) {
-    assert(x == y);
-}
-
-struct my_struct {
-    a: u32,
-    b: u32,
-}
-
-struct my2 {
-    aa: my_struct,
-    bb: my_struct,
-}
-
-fn test_multiple4(s: my_struct) {
-    assert(s.a == s.b+2);
-}
-
-fn test_multiple5(a: (u32, u32)) {
-    assert(a.0 == a.1+2);
-}
-
-
-fn test_multiple6(a: my2, b: my_struct, c: (my2, my_struct)) {
-    test_multiple4(a.aa);
-    test_multiple5((b.a, b.b));
-    assert(c.0.aa.a == c.1.a);
-}
-
-
-
-fn foo<N>(a: [Field; N]) -> [Field; N] {
-    a
-}
-
-fn bar() -> [Field; 1] {
-    foo([0])
-}
-
-fn main(x: u32 , y: u32 , a: Field, arr1: [u32; 9], arr2: [u32; 9]) {  
-    let mut ss: my_struct = my_struct { b: x, a: x+2, };
-    test_multiple4(ss);
-    test_multiple5((ss.a,ss.b));
-    let my = my2 {
-        aa: ss,
-        bb: ss,
-    };
-    ss.a = 61;
-    test_multiple6(my, ss, (my,ss));
-
-    let my_block = { 
-        let mut ab = f2(a);
-        ab = ab + a;
-        (x,ab)
-    };
-    assert(my_block.1 == 4);
-    
-    test0(a);
-    test1(a);
-    test2(x as Field, y);
-    assert(bar()[0] == 0);
-
-    let mut b = [0 as u8, 5 as u8, 2 as u8];
-    let c = test3(b);
-    assert(b == c);
-    b[0] = 1 as u8;
-    let cc = test3(b);
-    assert(c != cc);
-    let e = test_multiple(x, y);
-    assert(e.1 == e.0 + 54 as u32);
-    let d = test_multiple2();
-    assert(d.b == d.a + 2 as u32);
-    test_multiple3(y, y);
-
-    //Regression test for issue #628:
-    let result = first(arr_to_field(arr1), arr_to_field(arr2));
-    assert(result[0] == arr1[0] as Field);
-}
-
-// Issue #628
-fn arr_to_field(arr: [u32; 9]) -> [Field; 9] {
-    let mut as_field: [Field; 9] = [0 as Field; 9];
-    for i in 0..9 {
-        as_field[i] = arr[i] as Field;
-    }
-    as_field
-}
-
-fn first(a: [Field; 9], _b: [Field; 9]) -> [Field; 9] {
-    a
-}
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/8_integration/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/8_integration/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/8_integration/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/8_integration/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/8_integration/Prover.toml
deleted file mode 100644
index e4b4fa41073..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/8_integration/Prover.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-a=[867393132, 2339025230, 220695592, 603045882, 2511105607, 2829384008, 3709060370, 165831136, 1055242736, 1021386699, 504214651, 3662346416, 1830680088, 3882307476, 2426040416, 1802701977, 2663953820, 442532338, 1174156258, 2943965281, 2059435796, 2505576606, 666729718, 3602851575, 2784009587, 3495199106, 1721163808, 3787454896, 315490254, 2761503044, 1222736857, 3669200722, 1595984236, 1113969718, 486680564, 3162990949, 3264361924, 2006416798, 2386200406, 315797713, 2613961431, 2248446788, 1487182619, 1426297375, 1728644913, 1251844809, 1725705662, 1593325285, 2204175104, 2086772782, 3535562424, 171941432, 1454717338, 346500936, 3226869878, 1868934392, 4256057877, 1568150812, 3256749490, 2594788417, 1807197388, 3087252400, 1649310565, 2748668146, 3716823811, 3800017989, 932498547, 2480193018, 333760602, 97095822, 4100736518, 2777593334, 2339587180, 3771453942, 3867894936, 3650805881, 1824779553, 1642205658, 4264337791, 4071013475, 1985859040, 4202403275, 2148375036, 2428793574, 314105769, 4225849095, 3500808841, 2684237013, 848348764, 723628347, 1455798875, 3707853370, 1746878741, 1139375098, 3478206320, 3069213335, 112605790, 2440244355, 1471127557, 4092108893]
-b=[3828535814, 348916743, 1199414553, 737248839, 756047272, 1292160882, 4257951637, 291617875, 2966142224, 3814394488, 3878026466, 700807834, 2969962294, 1306796485, 3854250602, 898180304, 3427925197, 604266260, 1075521373, 3406840156, 3396422198, 890966269, 1079444598, 988299705, 3071209797, 3808577073, 2135889094, 1194271359, 4006125262, 566871018, 1292670770, 3445252242, 1897364157, 1587048323, 1240078226, 1678980405, 262815752, 304362997, 1104680912, 2632486420, 2463291218, 2187725560, 1870618568, 2652926282, 3004775258, 1952884887, 561428664, 2467226612, 2683547316, 3452779168, 976229927, 1449738410, 3252038428, 2805606398, 1462658417, 1592183545, 2019693157, 3278803512, 3026040550, 566335611, 703403330, 936890230, 2567824938, 890552997, 4217401169, 258050408, 29872215, 812502992, 3871770414, 4261908330, 3703871063, 2429703152, 1496772760, 3466865862, 2739387475, 547994854, 240736540, 3737530356, 545555875, 1243531855, 826369375, 392660683, 262937837, 3055809624, 1979941188, 3982865811, 2062520214, 1365494964, 3851477194, 4086198942, 4210993448, 3262645997, 766395054, 1585427862, 1824837360, 105660195, 3008983983, 845249279, 2566786179, 205438487]
-c=[867393132, 2339025230, 220695592, 603045882, ]
-d=[3828535814, 348916743, 1199414553, 737248839, ]
-m=[77,75,108,209,54,16,50,202,155,210,174,185,217,0,170,77,69,217,234,216,10,201,66,51,116,196,81,167,37,77,7,102]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/8_integration/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/8_integration/src/main.nr
deleted file mode 100644
index 56b02650c27..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/8_integration/src/main.nr
+++ /dev/null
@@ -1,283 +0,0 @@
-fn matrix_mul_2(a: [u32; 4], b: [u32; 4]) ->[u32; 4] {
-    let mut c = [0 as u32; 4];
-    for i in 0..2 {
-        for j in 0..2 {
-            c[i+2*j] = 0;
-            for k in 0..2 {
-               c[i+2*j] += a[i+2*k] * b[k+2*j];
-            }
-        }
-    }
-    c
-}
-
-fn matrix_mul_10(a: [u32; 100], b: [u32; 100]) -> [u32; 100] {
-    let mut c = [0 as u32; 100];
-    for i in 0..10 {
-        for j in 0..10 {
-            c[i+10*j] = 0 as u32;
-
-            for k in 0..10 {
-               c[i+10*j] += a[i+10*k] * b[k+10*j];
-            }
-        }
-    }
-    c
-}
-
-
-fn siggy(x: u32) -> u32 {
-    x * (10 as u32)
-}
-
-
-fn test4 (mut a: [u32; 4]) -> [u32; 4] {
-    for i in 3..4 {
-        a[i] = siggy(a[i-2]);
-    }
-    a
-}
-
-fn iterate1(mut a0: u32) -> u32{
-    let mut t1 = 0 as u32;
-    let mut t2 = 0 as u32;
-    let mut a = 1 as u32;
-    let mut f = 2 as u32;
-    let mut g = 3 as u32;
-    let mut h = 4 as u32;
-
-    for _i in 0..2 {
-        t1 = h;
-        h = g;
-        g = f;
-        a = t1 + t2;
-    }
-    a0 += a;
-    a0
-}
-
-fn array_noteq(a: [u32; 4], b: [u32; 4]) {
-    assert(a != b);
-}
-
-fn test3(mut b: [Field; 4]) -> [Field; 4] {
-    for i in 0..4 {
-        b[i] = i;
-    }
-    b
-}
-
-fn iterate2(mut hash: [u32; 8]) -> [u32; 8] {
-    let mut t1 = 0 as u32;
-  
-    let mut a = hash[0];
-    let mut e = hash[4];
-    let mut f = hash[5];
-    let mut g = hash[6];
-    let mut h = hash[7];
-
-    for _i in 0..2 { 
-        t1 = ch2(e, f);
-        h = g;
-        g = f;
-        a = t1;
-    }
-
-    hash[0] = hash[0] + a;
-    hash
-}
-
-fn iterate3( mut hash: [u32; 8]) -> [u32; 8] {
-    let mut t1 = 0 as u32;
-    let mut t2 = 0 as u32;
-    let mut a = hash[0];
-    let mut b = hash[1];
-    let mut c = hash[2];
-    let mut d = hash[3];
-    let mut e = hash[4];
-    let mut f = hash[5];
-    let mut g = hash[6];
-    let mut h = hash[7];
-
-    for _i in 0..3 { 
-        t1 = ep2(e)+ch2(e, f);
-        h = g;
-        g = f;
-        a = t1+t2;
-    }
-    assert(a == 2470696267);
-    hash[0] = hash[0] + a;
-    hash[1] = hash[1] + b;
-    hash[2] = hash[2] + c;
-    hash[3] = hash[3] + d;
-    hash[4] = hash[4] + e;
-    hash[5] = hash[5] + f;
-    hash[6] = hash[6] + g;
-    hash[7] = hash[7] + h;
-    hash
-}
-
-
-fn test5() {
-    let mut sha_hash = [
-        0 as u32, 1, 2, 3,
-        4, 5, 6, 7
-    ];
-
-    sha_hash = iterate2(sha_hash);
-
-    assert(sha_hash[0] == 9);
-}
-
-
-fn ch2(x: u32, y: u32) -> u32 {
-    x + y
-}
-
-fn ep2(x: u32) -> u32 {
-    (2 as u32) * too(x)
-}
-
-fn too(x: u32) -> u32 {
-    (x + 17 as u32) * (x + 3 as u32)
-}
-
-fn test6(x: [u8; 32]) ->  [u32; 8] {
-    let mut sha_m = [0 as u32; 64];
-
-    let mut sha_hash = [
-        1 as u32, 2, 3, 4, 5, 6, 7, 8
-    ];
-
-    let mut buffer = [0 as u8; 64];
-    for i in 0..32 {  
-       buffer[i] = x[i];
-    }
-
-    sha_m = iterate6_1(sha_m, buffer);
-    sha_hash = iterate6_2(sha_m, sha_hash);
-    sha_hash
-}
-
-fn iterate6_1(mut sha_m: [u32; 64], next_chunk: [u8; 64]) -> [u32; 64] {
-    let mut j = 0;
-    for i in 0..16 {
-        j = (i ) * 4;
-        sha_m[i] = ((next_chunk[j] as u32) << 24 as u32)  
-            | ((next_chunk[j + 1] as u32) << 16 as u32) 
-            | ((next_chunk[j + 2] as u32) << 8 as u32) 
-            | (next_chunk[j + 3] as u32);
-    }
-    for i in 16..64 {
-        sha_m[i] = sig1(sha_m[i - 2])+(sha_m[i - 7])+(sig0(sha_m[i - 15]))+(sha_m[i - 16]);
-    }
-    sha_m
-}
-
-fn iterate6_2(sha_m: [u32; 64], mut hash: [u32; 8]) -> [u32; 8] {
-    let mut t1 = 0 as u32;
-    let mut t2 = 0 as u32;
-    let mut a = 1 as u32;
-    let mut b = 2 as u32;
-    let mut c = 3 as u32;
-    let mut d = 4 as u32;
-    let mut e = 5 as u32;
-    let mut f = 6 as u32;
-    let mut g = 7 as u32;
-    let mut h = 8 as u32;
-
-    for i in 0..11 { 
-        t1 = h + ep1(e) + ch(e, f, g) + sha_m[i];
-        t2 = epo(a) + maj(a, b, c);
-        h = g;
-        g = f;
-        f = e;
-        e = d+t1;
-        d = c;
-        c = b;
-        b = a;
-        a = t1+t2;
-    }
-
-    hash[0] = hash[0]+a;
-    hash[1] = hash[1]+b;
-    hash[2] = hash[2]+c;
-    hash[3] = hash[3]+d;
-    hash[4] = hash[4]+e;
-    hash[5] = hash[5]+f;
-    hash[6] = hash[6]+g;
-    hash[7] = hash[7]+h;
-    hash
-}
-
-fn rot_right(a: u32, b: u32) -> u32 {
-    ((a >> b) | (a << (32 as u32 - b)))
-}
-
-
-fn ch(x: u32, y: u32, z: u32) -> u32 {
-    ((x & y) ^ (!x & z))
-}
-
-
-fn maj(x: u32, y: u32, z: u32) -> u32 {
-    ((x & y) ^ (x & z) ^ (y & z))
-}
-
-
-fn epo(x: u32) -> u32 {
-    (rot_right(x, 2) ^ rot_right(x, 13) ^ rot_right(x, 22))
-}
-
-fn ep1(x: u32) -> u32 {
-   (rot_right(x, 6) ^ rot_right(x, 11) ^ rot_right(x, 25))
-}
-
-fn sig0(x: u32) -> u32 {
-    (rot_right(x, 7) ^ rot_right(x, 18) ^ (x >> 3))
-}
-
-fn sig1(x: u32) -> u32 {
-    (rot_right(x, 17) ^ rot_right(x, 19) ^ (x >> 10))
-}
-
-
-fn main(a: [u32; 100], b: [u32; 100], c: [u32; 4], mut d: [u32; 4], m: [u8; 32]) {  
-    let e = matrix_mul_10(a,b);
-    assert(e[6] == 1866842232);
-    let f = matrix_mul_2(c,d);
-    assert(f[3] == 2082554100);
-
-    let mut a = [1 as u32, 2, 3, 4];
-    a = test4(a);
-    assert(a[3] == 20);
-    a = test4(c);
-    assert(a[3] == c[1] * 10);
-
-    d[0] += c[0];
-    d[0] += c[1];
-    assert(d[0] == 2739986880);
-
-    let h = iterate1(1);
-    assert(h == 4);
-
-    let x = d;
-    array_noteq(x, [d[0], d[1], d[2], 0]);
-
-    let mut h5 = [d[0] as Field, d[1] as Field, d[2] as Field, d[3] as Field];
-    let t5 = test3(h5);
-    assert(t5[3] == 3);
-    h5 = test3(h5);
-    assert(h5[3] == 3);
-
-    test5();
-
-    let mut sha_hash = [
-        0x6a09e667 as u32, 0xbb67ae85, 0x3c6ef372, 0xa54ff53a,
-        0x510e527f, 0x9b05688c, 0x1f83d9ab, 0x5be0cd19
-    ];
-    sha_hash = iterate3(sha_hash);
-
-    let h6 = test6(m);
-    assert(h6[0]== 523008072); //31.. 3800709683
-}
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/arithmetic_binary_operations/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/arithmetic_binary_operations/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/arithmetic_binary_operations/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/array_len/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/array_len/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/array_len/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/array_len/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/array_len/Prover.toml
deleted file mode 100644
index 3c3295e6848..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/array_len/Prover.toml
+++ /dev/null
@@ -1,2 +0,0 @@
-len3 = [1, 2, 3]
-len4 = [1, 2, 3, 4]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/array_len/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/array_len/src/main.nr
deleted file mode 100644
index 9099cfa2144..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/array_len/src/main.nr
+++ /dev/null
@@ -1,23 +0,0 @@
-use dep::std;
-
-fn len_plus_1<T>(array: [T]) -> Field {
-    array.len() + 1
-}
-
-fn add_lens<T>(a: [T], b: [Field]) -> Field {
-    a.len() + b.len()
-}
-
-fn nested_call(b: [Field]) -> Field {
-    len_plus_1(b)
-}
-
-fn main(len3: [u8; 3], len4: [Field; 4]) {
-    assert(len_plus_1(len3) == 4);
-    assert(len_plus_1(len4) == 5);
-    assert(add_lens(len3, len4) == 7);
-    assert(nested_call(len4) == 5);
-
-    // std::array::len returns a comptime value
-    assert(len4[len3.len()] == 4);
-}
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/array_neq/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/array_neq/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/array_neq/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/array_neq/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/array_neq/Prover.toml
deleted file mode 100644
index 3aad77f6d4d..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/array_neq/Prover.toml
+++ /dev/null
@@ -1,2 +0,0 @@
-a = [77,75,108,209,54,16,50,202,155,210,174,185,217,0,170,77,69,217,234,216,10,201,66,51,116,196,81,167,37,77,7,102]
-b = [44,75,108,209,54,16,50,202,155,210,174,185,217,0,170,77,69,217,234,216,10,201,66,51,116,196,81,167,37,77,7,102]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/array_neq/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/array_neq/src/main.nr
deleted file mode 100644
index be734dea368..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/array_neq/src/main.nr
+++ /dev/null
@@ -1,4 +0,0 @@
-// Simple example of checking where two arrays are different
-fn main(a: [Field; 32], b: [Field; 32]) {
-     assert(a != b);
-}
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/array_sort/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/array_sort/Prover.toml
deleted file mode 100644
index e0d79da4da6..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/array_sort/Prover.toml
+++ /dev/null
@@ -1 +0,0 @@
-xs = [2, 1, 3]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/array_sort/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/array_sort/src/main.nr
deleted file mode 100644
index 17df7b23551..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/array_sort/src/main.nr
+++ /dev/null
@@ -1,6 +0,0 @@
-fn main(xs : [u8; 3]) {
-    let sorted = xs.sort();
-    assert(sorted[0] == 1);
-    assert(sorted[1] == 2);
-    assert(sorted[2] == 3);
-}
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/assert/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/assert/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/assert/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/assert/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/assert/src/main.nr
deleted file mode 100644
index 00e94414c0b..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/assert/src/main.nr
+++ /dev/null
@@ -1,3 +0,0 @@
-fn main(x: Field) {
-    assert(x == 1);
-}
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/assert_statement/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/assert_statement/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/assert_statement/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/assign_ex/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/assign_ex/Nargo.toml
deleted file mode 100644
index d9434868157..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/assign_ex/Nargo.toml
+++ /dev/null
@@ -1,7 +0,0 @@
-
-        [package]
-        authors = [""]
-        compiler_version = "0.1"
-    
-        [dependencies]
-    
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/assign_ex/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/assign_ex/Prover.toml
deleted file mode 100644
index 8c12ebba6cf..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/assign_ex/Prover.toml
+++ /dev/null
@@ -1,2 +0,0 @@
-x = "1"
-y = "2"
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/assign_ex/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/assign_ex/src/main.nr
deleted file mode 100644
index b0626d63c8e..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/assign_ex/src/main.nr
+++ /dev/null
@@ -1,6 +0,0 @@
-fn main(x: Field, y: Field) {
-    let mut z = x + y;
-    assert(z == 3);
-    z = x * y;
-    assert(z == 2);
-}
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/bit_and/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/bit_and/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/bit_and/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/bit_and/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/bit_and/Prover.toml
deleted file mode 100644
index 40ce2b0bc27..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/bit_and/Prover.toml
+++ /dev/null
@@ -1,2 +0,0 @@
-x = "0x00"
-y = "0x10"
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/bit_and/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/bit_and/src/main.nr
deleted file mode 100644
index f4805960a33..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/bit_and/src/main.nr
+++ /dev/null
@@ -1,18 +0,0 @@
-// You can only do bit operations with integers.
-// (Kobi/Daira/Circom/#37) https://github.com/iden3/circom/issues/37
-fn main(x : Field, y : Field) {
-    let x_as_u8 = x as u8;
-    let y_as_u8 = y as u8;
-    
-    assert((x_as_u8 & y_as_u8) == x_as_u8);
-
-    //bitwise and with 1 bit:
-    let flag = (x == 0) & (y == 16);
-    assert(flag);
-
-    //bitwise and with odd bits:
-    let x_as_u11 = x as u11;
-    let y_as_u11 = y as u11;
-    assert((x_as_u11 & y_as_u11) == x_as_u11);
-}
-    
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/bit_shifts_comptime/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/bit_shifts_comptime/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/bit_shifts_comptime/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/bit_shifts_comptime/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/bit_shifts_comptime/Prover.toml
deleted file mode 100644
index cfd62c406cb..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/bit_shifts_comptime/Prover.toml
+++ /dev/null
@@ -1 +0,0 @@
-x = 64
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/bit_shifts_comptime/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/bit_shifts_comptime/src/main.nr
deleted file mode 100644
index c1c6890febb..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/bit_shifts_comptime/src/main.nr
+++ /dev/null
@@ -1,13 +0,0 @@
-fn main(x: u64) {
-	let two: u64 = 2;
-	let three: u64 = 3;
-
-	// comptime shifts on comptime values
-	assert(two << 2 == 8);
-	assert((two << 3) / 8 == two);
-	assert((three >> 1) == 1);
-
-	// comptime shifts on runtime values
-	assert(x << 1 == 128);
-	assert(x >> 2 == 16);
-}
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/blackbox_func_simple_call/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/blackbox_func_simple_call/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/blackbox_func_simple_call/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/bool_not/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/bool_not/Nargo.toml
deleted file mode 100644
index d9434868157..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/bool_not/Nargo.toml
+++ /dev/null
@@ -1,7 +0,0 @@
-
-        [package]
-        authors = [""]
-        compiler_version = "0.1"
-    
-        [dependencies]
-    
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/bool_not/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/bool_not/src/main.nr
deleted file mode 100644
index d6b4d7a9fad..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/bool_not/src/main.nr
+++ /dev/null
@@ -1,5 +0,0 @@
-use dep::std;
-fn main(x: u1) {
-    assert(!x == 0);
-}
-    
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/bool_or/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/bool_or/Nargo.toml
deleted file mode 100644
index d9434868157..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/bool_or/Nargo.toml
+++ /dev/null
@@ -1,7 +0,0 @@
-
-        [package]
-        authors = [""]
-        compiler_version = "0.1"
-    
-        [dependencies]
-    
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/bool_or/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/bool_or/src/main.nr
deleted file mode 100644
index 4a74027e4aa..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/bool_or/src/main.nr
+++ /dev/null
@@ -1,7 +0,0 @@
-use dep::std;
-fn main(x: u1, y: u1) {
-    assert(x | y == 1);
-
-    assert(x | y | x == 1);
-}
-    
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_acir_as_brillig/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_acir_as_brillig/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_acir_as_brillig/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_arrays/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_arrays/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_arrays/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_assert/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_assert/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_assert/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_assert/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_assert/Prover.toml
deleted file mode 100644
index 4dd6b405159..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_assert/Prover.toml
+++ /dev/null
@@ -1 +0,0 @@
-x = "1"
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_assert_fail/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_assert_fail/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_assert_fail/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_blake2s/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_blake2s/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_blake2s/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_calls/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_calls/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_calls/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_calls_array/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_calls_array/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_calls_array/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_calls_conditionals/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_calls_conditionals/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_calls_conditionals/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_cast/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_cast/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_cast/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_conditional/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_conditional/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_conditional/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_conditional/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_conditional/Prover.toml
deleted file mode 100644
index 4dd6b405159..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_conditional/Prover.toml
+++ /dev/null
@@ -1 +0,0 @@
-x = "1"
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_ecdsa/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_ecdsa/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_ecdsa/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_field_binary_operations/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_field_binary_operations/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_field_binary_operations/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_fns_as_values/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_fns_as_values/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_fns_as_values/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_hash_to_field/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_hash_to_field/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_hash_to_field/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_identity_function/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_identity_function/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_identity_function/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_integer_binary_operations/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_integer_binary_operations/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_integer_binary_operations/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_keccak/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_keccak/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_keccak/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_loop/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_loop/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_loop/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_modulo/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_modulo/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_modulo/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_not/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_not/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_not/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_not/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_not/Prover.toml
deleted file mode 100644
index a0397e89477..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_not/Prover.toml
+++ /dev/null
@@ -1,2 +0,0 @@
-x = "1"
-y = "0"
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_oracle/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_oracle/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_oracle/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_recursion/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_recursion/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_recursion/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_scalar_mul/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_scalar_mul/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_scalar_mul/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_schnorr/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_schnorr/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_schnorr/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_sha256/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_sha256/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_sha256/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_top_level/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_top_level/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/brillig_top_level/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/cast_bool/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/cast_bool/Nargo.toml
deleted file mode 100644
index d9434868157..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/cast_bool/Nargo.toml
+++ /dev/null
@@ -1,7 +0,0 @@
-
-        [package]
-        authors = [""]
-        compiler_version = "0.1"
-    
-        [dependencies]
-    
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/cast_bool/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/cast_bool/Prover.toml
deleted file mode 100644
index f489cbac003..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/cast_bool/Prover.toml
+++ /dev/null
@@ -1,2 +0,0 @@
-x = "10"
-y = "10"
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/cast_bool/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/cast_bool/src/main.nr
deleted file mode 100644
index 57af8120b33..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/cast_bool/src/main.nr
+++ /dev/null
@@ -1,6 +0,0 @@
-fn main(x: Field, y: Field) {
-    let z = x == y;
-    let t = z as u8;
-    assert(t == 1);
-}
-    
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/comptime_array_access/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/comptime_array_access/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/comptime_array_access/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/comptime_array_access/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/comptime_array_access/Prover.toml
deleted file mode 100644
index ec8d8e34856..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/comptime_array_access/Prover.toml
+++ /dev/null
@@ -1 +0,0 @@
-a = [1, 2, 3]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/comptime_array_access/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/comptime_array_access/src/main.nr
deleted file mode 100644
index 04f08bb70c5..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/comptime_array_access/src/main.nr
+++ /dev/null
@@ -1,17 +0,0 @@
-fn main(a: [Field; 3]) {
-    let i = 1;
-
-    // Using a comptime variable as a parameter should not make it non-comptime
-    let ii = foo(i);
-    let elem1 = a[i];
-
-    // Nor should using it in an expression with a non-comptime variable.
-    let two = i + ii;
-    assert(i == ii);
-
-    let elem2 = a[i];
-    assert(elem1 == elem2);
-    assert(two == 2);
-}
-
-fn foo(x: Field) -> Field { x }
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/comptime_recursion_regression/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/comptime_recursion_regression/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/comptime_recursion_regression/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/comptime_recursion_regression/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/comptime_recursion_regression/Prover.toml
deleted file mode 100644
index 745ce7c2361..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/comptime_recursion_regression/Prover.toml
+++ /dev/null
@@ -1,2 +0,0 @@
-x = 5
-y = 6
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/comptime_recursion_regression/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/comptime_recursion_regression/src/main.nr
deleted file mode 100644
index 0461fd9c4cb..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/comptime_recursion_regression/src/main.nr
+++ /dev/null
@@ -1,4 +0,0 @@
-fn main(x: Field, y: Field) {
-    let flag = (x == 1) | (y == 2);
-    assert(flag | false == flag);
-}
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/config.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/config.toml
deleted file mode 100644
index 66525b5048d..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/config.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-exclude = []
-
-
-# List of tests (as their directory name) expecting to fail: if the test pass, we report an error.
-fail = ["brillig_assert_fail"]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/constant_return/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/constant_return/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/constant_return/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/contracts/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/contracts/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/contracts/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/contracts/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/contracts/Prover.toml
deleted file mode 100644
index 97d5b1e0eed..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/contracts/Prover.toml
+++ /dev/null
@@ -1,2 +0,0 @@
-x = 3
-y = 2
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/contracts/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/contracts/src/main.nr
deleted file mode 100644
index c8d70cc2d0e..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/contracts/src/main.nr
+++ /dev/null
@@ -1,10 +0,0 @@
-fn main(x : Field, y : pub Field) {
-    assert(x * 2 == y * 3);
-}
-
-contract Foo {
-    fn double(x: Field) -> pub Field { x * 2 }
-    fn triple(x: Field) -> pub Field { x * 3 }
-    internal fn quadruple(x: Field) -> pub Field { x * 4 }
-    open internal fn skibbidy(x: Field) -> pub Field { x * 5 }
-}
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/diamond_deps_0/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/diamond_deps_0/Nargo.toml
deleted file mode 100644
index d5094940130..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/diamond_deps_0/Nargo.toml
+++ /dev/null
@@ -1,7 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.7.1"
-
-[dependencies]
-dep1 = { path = "../../test_libraries/diamond_deps_1" }
-dep2 = { path = "../../test_libraries/diamond_deps_2" }
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/diamond_deps_0/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/diamond_deps_0/Prover.toml
deleted file mode 100644
index a713241e7dd..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/diamond_deps_0/Prover.toml
+++ /dev/null
@@ -1,3 +0,0 @@
-x = 1
-y = 1
-return = 5
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/diamond_deps_0/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/diamond_deps_0/src/main.nr
deleted file mode 100644
index f01491171bb..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/diamond_deps_0/src/main.nr
+++ /dev/null
@@ -1,7 +0,0 @@
-use dep::dep1::call_dep1_then_dep2;
-use dep::dep2::call_dep2;
-use dep::dep2::RESOLVE_THIS;
-
-fn main(x : Field, y : pub Field) -> pub Field {
-    call_dep1_then_dep2(x, y) + call_dep2(x, y) + RESOLVE_THIS
-}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/distinct_keyword/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/distinct_keyword/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/distinct_keyword/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/ec_baby_jubjub/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/ec_baby_jubjub/src/main.nr
deleted file mode 100644
index 3372e969d4b..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/ec_baby_jubjub/src/main.nr
+++ /dev/null
@@ -1,226 +0,0 @@
-// Tests may be checked against https://github.com/cfrg/draft-irtf-cfrg-hash-to-curve/tree/main/poc
-
-use dep::std::ec::tecurve::affine::Curve as AffineCurve;
-use dep::std::ec::tecurve::affine::Point as Gaffine;
-use dep::std::ec::tecurve::curvegroup::Curve;
-use dep::std::ec::tecurve::curvegroup::Point as G;
-
-use dep::std::ec::swcurve::affine::Point as SWGaffine;
-use dep::std::ec::swcurve::curvegroup::Point as SWG;
-
-use dep::std::ec::montcurve::affine::Point as MGaffine;
-use dep::std::ec::montcurve::curvegroup::Point as MG;
-
-fn main() {
-    // This test only makes sense if Field is the right prime field.
-    if 21888242871839275222246405745257275088548364400416034343698204186575808495617 == 0
-    {
-        // Define Baby Jubjub (ERC-2494) parameters in affine representation
-        let bjj_affine = AffineCurve::new(168700, 168696, Gaffine::new(995203441582195749578291179787384436505546430278305826713579947235728471134,5472060717959818805561601436314318772137091100104008585924551046643952123905));
-
-        // Test addition
-        let p1_affine = Gaffine::new(17777552123799933955779906779655732241715742912184938656739573121738514868268, 2626589144620713026669568689430873010625803728049924121243784502389097019475);
-        let p2_affine = Gaffine::new(16540640123574156134436876038791482806971768689494387082833631921987005038935, 20819045374670962167435360035096875258406992893633759881276124905556507972311);
-        
-        let p3_affine = bjj_affine.add(p1_affine, p2_affine);
-        assert(
-            p3_affine.eq(Gaffine::new(
-                7916061937171219682591368294088513039687205273691143098332585753343424131937,
-                14035240266687799601661095864649209771790948434046947201833777492504781204499
-            ))
-        );
-
-        // Test scalar multiplication
-        let p4_affine = bjj_affine.mul(2, p1_affine);
-        assert(
-            p4_affine.eq(Gaffine::new(
-                6890855772600357754907169075114257697580319025794532037257385534741338397365,
-                4338620300185947561074059802482547481416142213883829469920100239455078257889
-            ))
-        );
-        assert(p4_affine.eq(bjj_affine.bit_mul([0,1], p1_affine)));
-
-        // Test subtraction
-        let p5_affine = bjj_affine.subtract(p3_affine, p3_affine);
-        assert(p5_affine.eq(Gaffine::zero()));
-
-        // Check that these points are on the curve
-        assert(
-            bjj_affine.contains(bjj_affine.gen) &
-            bjj_affine.contains(p1_affine) &
-            bjj_affine.contains(p2_affine) &
-            bjj_affine.contains(p3_affine) &
-            bjj_affine.contains(p4_affine) &
-            bjj_affine.contains(p5_affine)
-        );
-        
-        // Test CurveGroup equivalents
-        let bjj = bjj_affine.into_group(); // Baby Jubjub
-
-        let p1 = p1_affine.into_group();
-        let p2 = p2_affine.into_group();
-        let p3 = p3_affine.into_group();
-        let p4 = p4_affine.into_group();
-        let p5 = p5_affine.into_group(); 
-
-        // Test addition
-        assert(p3.eq(bjj.add(p1, p2)));
-
-        // Test scalar multiplication
-        assert(p4.eq(bjj.mul(2, p1)));
-        assert(p4.eq(bjj.bit_mul([0,1], p1)));
-
-        // Test subtraction
-        assert(G::zero().eq(bjj.subtract(p3, p3)));
-        assert(p5.eq(G::zero()));
-
-        // Check that these points are on the curve
-        assert(
-            bjj.contains(bjj.gen) &
-            bjj.contains(p1) &
-            bjj.contains(p2) &
-            bjj.contains(p3) &
-            bjj.contains(p4) &
-            bjj.contains(p5)
-        );
-        
-        // Test SWCurve equivalents of the above
-        // First the affine representation
-        let bjj_swcurve_affine = bjj_affine.into_swcurve();
-
-        let p1_swcurve_affine = bjj_affine.map_into_swcurve(p1_affine);
-        let p2_swcurve_affine = bjj_affine.map_into_swcurve(p2_affine);
-        let p3_swcurve_affine = bjj_affine.map_into_swcurve(p3_affine);
-        let p4_swcurve_affine = bjj_affine.map_into_swcurve(p4_affine);
-        let p5_swcurve_affine = bjj_affine.map_into_swcurve(p5_affine);
-        
-        // Addition
-        assert(
-            p3_swcurve_affine.eq(
-                bjj_swcurve_affine.add(
-                p1_swcurve_affine,
-                p2_swcurve_affine
-                )
-            )
-        );
-        
-        // Doubling
-        assert(p4_swcurve_affine.eq(bjj_swcurve_affine.mul(2, p1_swcurve_affine)));
-        assert(p4_swcurve_affine.eq(bjj_swcurve_affine.bit_mul([0,1], p1_swcurve_affine)));
-
-        // Subtraction
-        assert(SWGaffine::zero().eq(bjj_swcurve_affine.subtract(p3_swcurve_affine, p3_swcurve_affine)));
-        assert(p5_swcurve_affine.eq(SWGaffine::zero()));
-
-        // Check that these points are on the curve
-        assert(
-            bjj_swcurve_affine.contains(bjj_swcurve_affine.gen) &
-            bjj_swcurve_affine.contains(p1_swcurve_affine) &
-            bjj_swcurve_affine.contains(p2_swcurve_affine) &
-            bjj_swcurve_affine.contains(p3_swcurve_affine) &
-            bjj_swcurve_affine.contains(p4_swcurve_affine) &
-            bjj_swcurve_affine.contains(p5_swcurve_affine)
-        );
-        
-        // Then the CurveGroup representation
-        let bjj_swcurve = bjj.into_swcurve();
-
-        let p1_swcurve = bjj.map_into_swcurve(p1);
-        let p2_swcurve = bjj.map_into_swcurve(p2);
-        let p3_swcurve = bjj.map_into_swcurve(p3);
-        let p4_swcurve = bjj.map_into_swcurve(p4);
-        let p5_swcurve = bjj.map_into_swcurve(p5);
-        
-        // Addition
-        assert(p3_swcurve.eq(bjj_swcurve.add(p1_swcurve,p2_swcurve)));
-        
-        // Doubling
-        assert(p4_swcurve.eq(bjj_swcurve.mul(2, p1_swcurve)));
-        assert(p4_swcurve.eq(bjj_swcurve.bit_mul([0,1], p1_swcurve)));
-
-        // Subtraction
-        assert(SWG::zero().eq(bjj_swcurve.subtract(p3_swcurve, p3_swcurve)));
-        assert(p5_swcurve.eq(SWG::zero()));
-
-        // Check that these points are on the curve
-        assert(
-            bjj_swcurve.contains(bjj_swcurve.gen) &
-            bjj_swcurve.contains(p1_swcurve) &
-            bjj_swcurve.contains(p2_swcurve) &
-            bjj_swcurve.contains(p3_swcurve) &
-            bjj_swcurve.contains(p4_swcurve) &
-            bjj_swcurve.contains(p5_swcurve)
-        );
-
-        // Test MontCurve conversions
-        // First the affine representation
-        let bjj_montcurve_affine = bjj_affine.into_montcurve();
-
-        let p1_montcurve_affine = p1_affine.into_montcurve();
-        let p2_montcurve_affine = p2_affine.into_montcurve();
-        let p3_montcurve_affine = p3_affine.into_montcurve();
-        let p4_montcurve_affine = p4_affine.into_montcurve();
-        let p5_montcurve_affine = p5_affine.into_montcurve();
-        
-        // Addition
-        assert(p3_montcurve_affine.eq(bjj_montcurve_affine.add(p1_montcurve_affine, p2_montcurve_affine)));
-        
-        // Doubling
-        assert(p4_montcurve_affine.eq(bjj_montcurve_affine.mul(2, p1_montcurve_affine)));
-        assert(p4_montcurve_affine.eq(bjj_montcurve_affine.bit_mul([0,1], p1_montcurve_affine)));
-
-        // Subtraction
-        assert(MGaffine::zero().eq(bjj_montcurve_affine.subtract(p3_montcurve_affine, p3_montcurve_affine)));
-        assert(p5_montcurve_affine.eq(MGaffine::zero()));
-
-        // Check that these points are on the curve
-        assert(
-            bjj_montcurve_affine.contains(bjj_montcurve_affine.gen) &
-            bjj_montcurve_affine.contains(p1_montcurve_affine) &
-            bjj_montcurve_affine.contains(p2_montcurve_affine) &
-            bjj_montcurve_affine.contains(p3_montcurve_affine) &
-            bjj_montcurve_affine.contains(p4_montcurve_affine) &
-            bjj_montcurve_affine.contains(p5_montcurve_affine)
-        );
-
-        // Then the CurveGroup representation
-        let bjj_montcurve = bjj.into_montcurve();
-
-        let p1_montcurve = p1_montcurve_affine.into_group();
-        let p2_montcurve = p2_montcurve_affine.into_group();
-        let p3_montcurve = p3_montcurve_affine.into_group();
-        let p4_montcurve = p4_montcurve_affine.into_group();
-        let p5_montcurve = p5_montcurve_affine.into_group();
-        
-        // Addition
-        assert(p3_montcurve.eq(bjj_montcurve.add(p1_montcurve, p2_montcurve)));
-
-        // Doubling
-        assert(p4_montcurve.eq(bjj_montcurve.mul(2, p1_montcurve)));
-        assert(p4_montcurve.eq(bjj_montcurve.bit_mul([0,1], p1_montcurve)));
-
-        // Subtraction
-        assert(MG::zero().eq(bjj_montcurve.subtract(p3_montcurve, p3_montcurve)));
-        assert(p5_montcurve.eq(MG::zero()));
-
-        // Check that these points are on the curve
-        assert(
-            bjj_montcurve.contains(bjj_montcurve.gen) &
-            bjj_montcurve.contains(p1_montcurve) &
-            bjj_montcurve.contains(p2_montcurve) &
-            bjj_montcurve.contains(p3_montcurve) &
-            bjj_montcurve.contains(p4_montcurve) &
-            bjj_montcurve.contains(p5_montcurve)
-        );
-        
-        // Elligator 2 map-to-curve
-        let ell2_pt_map = bjj_affine.elligator2_map(27);
-
-        assert(ell2_pt_map.eq(MGaffine::new(7972459279704486422145701269802978968072470631857513331988813812334797879121, 8142420778878030219043334189293412482212146646099536952861607542822144507872).into_tecurve()));
-
-        // SWU map-to-curve
-        let swu_pt_map = bjj_affine.swu_map(5,27);
-        
-        assert(swu_pt_map.eq(bjj_affine.map_from_swcurve(SWGaffine::new(2162719247815120009132293839392097468339661471129795280520343931405114293888, 5341392251743377373758788728206293080122949448990104760111875914082289313973))));        
-    }            
-}
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/ecdsa_secp256k1/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/ecdsa_secp256k1/Prover.toml
deleted file mode 100644
index 412c7b36e4c..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/ecdsa_secp256k1/Prover.toml
+++ /dev/null
@@ -1,209 +0,0 @@
-
-hashed_message = [
-    0x3a,
-    0x73,
-    0xf4,
-    0x12,
-    0x3a,
-    0x5c,
-    0xd2,
-    0x12,
-    0x1f,
-    0x21,
-    0xcd,
-    0x7e,
-    0x8d,
-    0x35,
-    0x88,
-    0x35,
-    0x47,
-    0x69,
-    0x49,
-    0xd0,
-    0x35,
-    0xd9,
-    0xc2,
-    0xda,
-    0x68,
-    0x06,
-    0xb4,
-    0x63,
-    0x3a,
-    0xc8,
-    0xc1,
-    0xe2,
-]
-message = [
-    0x49,
-    0x6e,
-    0x73,
-    0x74,
-    0x72,
-    0x75,
-    0x63,
-    0x74,
-    0x69,
-    0x6f,
-    0x6e,
-    0x73,
-    0x20,
-    0x75,
-    0x6e,
-    0x63,
-    0x6c,
-    0x65,
-    0x61,
-    0x72,
-    0x2c,
-    0x20,
-    0x61,
-    0x73,
-    0x6b,
-    0x20,
-    0x61,
-    0x67,
-    0x61,
-    0x69,
-    0x6e,
-    0x20,
-    0x6c,
-    0x61,
-    0x74,
-    0x65,
-    0x72,
-    0x2e,
-]
-pub_key_x = [
-    0xa0,
-    0x43,
-    0x4d,
-    0x9e,
-    0x47,
-    0xf3,
-    0xc8,
-    0x62,
-    0x35,
-    0x47,
-    0x7c,
-    0x7b,
-    0x1a,
-    0xe6,
-    0xae,
-    0x5d,
-    0x34,
-    0x42,
-    0xd4,
-    0x9b,
-    0x19,
-    0x43,
-    0xc2,
-    0xb7,
-    0x52,
-    0xa6,
-    0x8e,
-    0x2a,
-    0x47,
-    0xe2,
-    0x47,
-    0xc7,
-]
-pub_key_y = [
-    0x89,
-    0x3a,
-    0xba,
-    0x42,
-    0x54,
-    0x19,
-    0xbc,
-    0x27,
-    0xa3,
-    0xb6,
-    0xc7,
-    0xe6,
-    0x93,
-    0xa2,
-    0x4c,
-    0x69,
-    0x6f,
-    0x79,
-    0x4c,
-    0x2e,
-    0xd8,
-    0x77,
-    0xa1,
-    0x59,
-    0x3c,
-    0xbe,
-    0xe5,
-    0x3b,
-    0x03,
-    0x73,
-    0x68,
-    0xd7,
-]
-signature = [
-    0xe5,
-    0x08,
-    0x1c,
-    0x80,
-    0xab,
-    0x42,
-    0x7d,
-    0xc3,
-    0x70,
-    0x34,
-    0x6f,
-    0x4a,
-    0x0e,
-    0x31,
-    0xaa,
-    0x2b,
-    0xad,
-    0x8d,
-    0x97,
-    0x98,
-    0xc3,
-    0x80,
-    0x61,
-    0xdb,
-    0x9a,
-    0xe5,
-    0x5a,
-    0x4e,
-    0x8d,
-    0xf4,
-    0x54,
-    0xfd,
-    0x28,
-    0x11,
-    0x98,
-    0x94,
-    0x34,
-    0x4e,
-    0x71,
-    0xb7,
-    0x87,
-    0x70,
-    0xcc,
-    0x93,
-    0x1d,
-    0x61,
-    0xf4,
-    0x80,
-    0xec,
-    0xbb,
-    0x0b,
-    0x89,
-    0xd6,
-    0xeb,
-    0x69,
-    0x69,
-    0x01,
-    0x61,
-    0xe4,
-    0x9a,
-    0x71,
-    0x5f,
-    0xcd,
-    0x55,
-]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/ecdsa_secp256k1/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/ecdsa_secp256k1/src/main.nr
deleted file mode 100644
index dfac8673b38..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/ecdsa_secp256k1/src/main.nr
+++ /dev/null
@@ -1,11 +0,0 @@
-use dep::std;
-
-
-fn main(message : [u8;38],hashed_message : [u8;32], pub_key_x : [u8;32], pub_key_y : [u8;32], signature : [u8;64]) {
-     // Hash the message, since secp256k1 expects a hashed_message
-     let expected= std::hash::sha256(message);
-     assert(hashed_message == expected);
-
-     let valid_signature = std::ecdsa_secp256k1::verify_signature(pub_key_x, pub_key_y, signature, hashed_message);
-     assert(valid_signature);
-}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/ecdsa_secp256r1/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/ecdsa_secp256r1/Prover.toml
deleted file mode 100644
index a45f799877b..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/ecdsa_secp256r1/Prover.toml
+++ /dev/null
@@ -1,20 +0,0 @@
-hashed_message = [
-    84, 112, 91, 163, 186, 175, 219, 223, 186, 140, 95, 154, 112, 247, 168, 155, 238, 152,
-    217, 6, 181, 62, 49, 7, 77, 167, 186, 236, 220, 13, 169, 173,
-]
-pub_key_x = [
-    85, 15, 71, 16, 3, 243, 223, 151, 195, 223, 80, 106, 199, 151, 246, 114, 31, 177, 161,
-    251, 123, 143, 111, 131, 210, 36, 73, 138, 101, 200, 142, 36,
-]
-pub_key_y = [
-    19, 96, 147, 215, 1, 46, 80, 154, 115, 113, 92, 189, 11, 0, 163, 204, 15, 244, 181,
-    192, 27, 63, 250, 25, 106, 177, 251, 50, 112, 54, 184, 230,
-]
-signature = [
-    44,  112, 168, 208, 132, 182, 43,  252, 92,  224, 54, 65, 202, 249, 247, 42,
-    212, 218, 140, 129, 191, 230, 236, 148, 135, 187, 94, 27, 239, 98,  161, 50,
-    24,  173, 158, 226, 158, 175, 53,  31,  220, 80,  241, 82,  12,  66, 94, 155,
-    144, 138, 7,   39,  139, 67,  176, 236, 123, 135, 39,  120, 193, 78, 7,  132 
-]
-
-
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/ecdsa_secp256r1/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/ecdsa_secp256r1/src/main.nr
deleted file mode 100644
index 058f4ca8fb1..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/ecdsa_secp256r1/src/main.nr
+++ /dev/null
@@ -1,7 +0,0 @@
-use dep::std;
-
-
-fn main(hashed_message : [u8;32], pub_key_x : [u8;32], pub_key_y : [u8;32], signature : [u8;64]) {
-     let valid_signature = std::ecdsa_secp256r1::verify_signature(pub_key_x, pub_key_y, signature, hashed_message);
-     assert(valid_signature);
-}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/generics/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/generics/Nargo.toml
deleted file mode 100644
index d9434868157..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/generics/Nargo.toml
+++ /dev/null
@@ -1,7 +0,0 @@
-
-        [package]
-        authors = [""]
-        compiler_version = "0.1"
-    
-        [dependencies]
-    
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/generics/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/generics/Prover.toml
deleted file mode 100644
index 85f1e9f96f2..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/generics/Prover.toml
+++ /dev/null
@@ -1,2 +0,0 @@
-x = "2"
-y = "2"
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/generics/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/generics/src/main.nr
deleted file mode 100644
index bfde9d3c957..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/generics/src/main.nr
+++ /dev/null
@@ -1,57 +0,0 @@
-struct Bar<T> {
-    one: Field,
-    two: Field,
-    other: T,
-}
-
-fn foo<T>(bar: Bar<T>) {
-    assert(bar.one == bar.two);
-}
-
-struct BigInt<N> {
-    limbs: [u32; N],
-}
-
-impl<N> BigInt<N> {
-    // `N` is in scope of all methods in the impl
-    fn first(first: BigInt<N>, second: BigInt<N>) -> Self {
-        assert(first.limbs != second.limbs);
-        first
-    }
-
-    fn second(first: BigInt<N>, second: Self) -> Self {
-        assert(first.limbs != second.limbs);
-        second
-    }
-}
-
-impl Bar<Field> {
-    fn get_other(self) -> Field {
-        self.other
-    }
-}
-
-fn main(x: Field, y: Field) {
-    let bar1: Bar<Field> = Bar { one: x, two: y, other: 0 };
-    let bar2 = Bar { one: x, two: y, other: [0] };
-
-    foo(bar1);
-    foo(bar2);
-
-    // Test generic impls
-    let int1 = BigInt { limbs: [1] };
-    let int2 = BigInt { limbs: [2] };
-    let BigInt { limbs } = int1.second(int2).first(int1);
-    assert(limbs == int2.limbs);
-
-    // Test impl exclusively for Bar<Field>
-    assert(bar1.get_other() == bar1.other);
-
-    // Expected type error
-    // assert(bar2.get_other() == bar2.other);
-
-    let one = x;
-    let two = y;
-    let nested_generics: Bar<Bar<Field>> = Bar { one, two, other: Bar { one, two, other: 0 } };
-    assert(nested_generics.other.other == bar1.get_other());
-}
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/global_consts/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/global_consts/Nargo.toml
deleted file mode 100644
index d9434868157..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/global_consts/Nargo.toml
+++ /dev/null
@@ -1,7 +0,0 @@
-
-        [package]
-        authors = [""]
-        compiler_version = "0.1"
-    
-        [dependencies]
-    
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/global_consts/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/global_consts/Prover.toml
deleted file mode 100644
index 66f7feb1dda..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/global_consts/Prover.toml
+++ /dev/null
@@ -1,4 +0,0 @@
-a = [77,75,108,209,54,16,50,202,155,210,174,185,217,0,170,77,69,217,234,216,10,201,66,51,116,196,81,167,37,77,7,102]
-b = [44,75,108,209,54,16,50,202,155,210,174,185,217,0,170,77,69,217,234,216,10,201,66,51,116,196,81,167,37,77,7,102]
-c = [3, 3, 3]
-d = [5, 5, 5, 5, 5]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/global_consts/src/baz.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/global_consts/src/baz.nr
deleted file mode 100644
index e52efc52eae..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/global_consts/src/baz.nr
+++ /dev/null
@@ -1,5 +0,0 @@
-fn from_baz(x : [Field; crate::foo::MAGIC_NUMBER]) {
-     for i in 0..crate::foo::MAGIC_NUMBER {
-          assert(x[i] == crate::foo::MAGIC_NUMBER);
-     };
-}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/global_consts/src/foo.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/global_consts/src/foo.nr
deleted file mode 100644
index 2db74fb1ff7..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/global_consts/src/foo.nr
+++ /dev/null
@@ -1,11 +0,0 @@
-mod bar;
-
-global N: Field = 5;
-global MAGIC_NUMBER: Field = 3;
-global TYPE_INFERRED = 42;
-
-fn from_foo(x : [Field; bar::N]) {
-     for i in 0..bar::N {
-          assert(x[i] == bar::N);
-     };
-}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/global_consts/src/foo/bar.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/global_consts/src/foo/bar.nr
deleted file mode 100644
index 1b4d472b1e8..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/global_consts/src/foo/bar.nr
+++ /dev/null
@@ -1,5 +0,0 @@
-global N: Field = 5;
-
-fn from_bar(x : Field) -> Field {
-    x * N
-}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/global_consts/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/global_consts/src/main.nr
deleted file mode 100644
index 9bcca2b8071..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/global_consts/src/main.nr
+++ /dev/null
@@ -1,88 +0,0 @@
-mod foo;
-mod baz;
-
-global M: Field = 32;
-global L: Field = 10; // Unused globals currently allowed
-global N: Field = 5;
-global T_LEN = 2; // Type inference is allowed on globals
-//global N: Field = 5; // Uncomment to see duplicate globals error 
-
-struct Dummy {
-     x: [Field; N],
-     y: [Field; foo::MAGIC_NUMBER]
-}
-
-fn main(a: [Field; M + N - N], b: [Field; 30 + N / 2], c : pub [Field; foo::MAGIC_NUMBER], d: [Field; foo::bar::N]) {
-     let test_struct = Dummy { x: d, y: c };
-
-     for i in 0..foo::MAGIC_NUMBER {
-          assert(c[i] == foo::MAGIC_NUMBER);
-          assert(test_struct.y[i] == foo::MAGIC_NUMBER);
-     }
-
-     assert(N != M);
-     
-     let expected: u32 = 42;
-     assert(foo::TYPE_INFERRED == expected);
-
-     let mut y = 5;
-     let mut x = M;
-     for i in 0..N*N {
-          let M: comptime Field = 10;
-          x = M;
-          
-          y = i;
-     }
-     assert(y == 24);
-     assert(x == 10);
-
-     let q = multiplyByM(3);
-     assert(q == 96);
-
-     arrays_neq(a, b);
-
-     let t: [Field; T_LEN] = [N, M];
-     assert(t[1] == 32);
-
-     assert(15 == mysubmodule::my_helper());
-     
-     let add_submodules_N = mysubmodule::N + foo::bar::N;
-     assert(15 == add_submodules_N);
-     let add_from_bar_N = mysubmodule::N + foo::bar::from_bar(1);
-     assert(15 == add_from_bar_N);
-
-     // Example showing an array filled with (mysubmodule::N + 2) 0's
-     let sugared = [0; mysubmodule::N + 2];
-     assert(sugared[mysubmodule::N + 1] == 0);
-
-     let arr: [Field; mysubmodule::N] = [N; 10];
-     assert((arr[0] == 5) & (arr[9] == 5));
-
-     foo::from_foo(d);
-     baz::from_baz(c);
-}
-
-fn multiplyByM(x: Field) -> Field {
-     x * M
-}
-
-fn arrays_neq(a: [Field; M], b: [Field; M]) {
-     assert(a != b);
-}
-
-mod mysubmodule {
-    use dep::std;
-
-    global N: Field = 10;
-    global L: Field = 50;
-
-    fn my_bool_or(x: u1, y: u1) {
-        assert(x | y == 1);
-    }
-
-    fn my_helper() -> comptime Field {
-        let N: comptime Field = 15; // Like in Rust, local variables override globals
-        let x = N;
-        x
-    }
-}
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/hash_to_field/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/hash_to_field/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/hash_to_field/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/hash_to_field/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/hash_to_field/Prover.toml
deleted file mode 100644
index f6597d3f78a..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/hash_to_field/Prover.toml
+++ /dev/null
@@ -1 +0,0 @@
-input = "1"
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/hash_to_field/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/hash_to_field/src/main.nr
deleted file mode 100644
index ffc334179ee..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/hash_to_field/src/main.nr
+++ /dev/null
@@ -1,5 +0,0 @@
-use dep::std;
-
-fn main(input : Field) -> pub Field {
-    std::hash::hash_to_field([input])
-}
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/if_else_chain/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/if_else_chain/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/if_else_chain/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/if_else_chain/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/if_else_chain/Prover.toml
deleted file mode 100644
index 84aeb36ac21..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/if_else_chain/Prover.toml
+++ /dev/null
@@ -1,2 +0,0 @@
-a=0
-c=[2, 4, 3, 0, ]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/if_else_chain/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/if_else_chain/src/main.nr
deleted file mode 100644
index 5105c18c7de..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/if_else_chain/src/main.nr
+++ /dev/null
@@ -1,16 +0,0 @@
-
-fn main(a: u32, mut c: [u32; 4]){
-    if a == c[0] {
-        assert(c[0] == 0);
-    } else if a == c[1] {
-        assert(c[1] == 0);
-    } else if a == c[2] {
-        assert(c[2] == 0);
-    } else if a == c[3] {
-        // expect to match this case
-        assert(c[3] == 0);
-    } else {
-       assert(c[0] == 10);
-    }
-}
-
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/integer_array_indexing/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/integer_array_indexing/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/integer_array_indexing/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/keccak256/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/keccak256/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/keccak256/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/keccak256/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/keccak256/Prover.toml
deleted file mode 100644
index d65c4011d3f..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/keccak256/Prover.toml
+++ /dev/null
@@ -1,35 +0,0 @@
-x = 0xbd
-result = [
-        0x5a,
-        0x50,
-        0x2f,
-        0x9f,
-        0xca,
-        0x46,
-        0x7b,
-        0x26,
-        0x6d,
-        0x5b,
-        0x78,
-        0x33,
-        0x65,
-        0x19,
-        0x37,
-        0xe8,
-        0x05,
-        0x27,
-        0x0c,
-        0xa3,
-        0xf3,
-        0xaf,
-        0x1c,
-        0x0d,
-        0xd2,
-        0x46,
-        0x2d,
-        0xca,
-        0x4b,
-        0x3b,
-        0x1a,
-        0xbf,
-]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/keccak256/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/keccak256/src/main.nr
deleted file mode 100644
index ba3ed7d07af..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/keccak256/src/main.nr
+++ /dev/null
@@ -1,22 +0,0 @@
-// Keccak256 example
-//
-use dep::std;
-
-fn main(x: Field, result: [u8; 32]) {
-    // We use the `as` keyword here to denote the fact that we want to take just the first byte from the x Field
-    // The padding is taken care of by the program
-    let digest = std::hash::keccak256([x as u8], 1);
-    assert(digest == result);
-    
-    //#1399: variable meesage size 
-    let message_size = 4;
-    let hash_a = std::hash::keccak256([1,2,3,4], message_size);
-    let hash_b = std::hash::keccak256([1,2,3,4,0,0,0,0], message_size);
-
-    assert(hash_a == hash_b);
-
-    let message_size_big = 8;
-    let hash_c = std::hash::keccak256([1,2,3,4,0,0,0,0], message_size_big);
-
-    assert(hash_a != hash_c);
-}
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/main_bool_arg/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/main_bool_arg/Prover.toml
deleted file mode 100644
index f932e0b4817..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/main_bool_arg/Prover.toml
+++ /dev/null
@@ -1,2 +0,0 @@
-x = true
-y = [true, false]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/main_bool_arg/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/main_bool_arg/src/main.nr
deleted file mode 100644
index 0615a7dbca4..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/main_bool_arg/src/main.nr
+++ /dev/null
@@ -1,8 +0,0 @@
-fn main(x : bool, y: [bool;2]) {
-    if x {
-        assert(1 != 2);
-    }
-
-    assert(x);
-    assert(y[0] != y[1]);
-}
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/main_return/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/main_return/Prover.toml
deleted file mode 100644
index 63e9878811a..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/main_return/Prover.toml
+++ /dev/null
@@ -1 +0,0 @@
-x = "8"
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/main_return/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/main_return/src/main.nr
deleted file mode 100644
index 06347eb0919..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/main_return/src/main.nr
+++ /dev/null
@@ -1,3 +0,0 @@
-fn main(x: pub Field) -> pub Field {
-    x
-}
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/merkle_insert/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/merkle_insert/Nargo.toml
deleted file mode 100644
index d9434868157..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/merkle_insert/Nargo.toml
+++ /dev/null
@@ -1,7 +0,0 @@
-
-        [package]
-        authors = [""]
-        compiler_version = "0.1"
-    
-        [dependencies]
-    
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/merkle_insert/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/merkle_insert/Prover.toml
deleted file mode 100644
index fca4a077df4..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/merkle_insert/Prover.toml
+++ /dev/null
@@ -1,11 +0,0 @@
-old_root = "0x285785b10eca49cf456b935f1c9787ff571f306c1bc62549c31a9199a633f9f8"
-old_leaf = "0x1cdcf02431ba623767fe389337d011df1048dcc24b98ed81cec97627bab454a0"
-old_hash_path = [
-    "0x1cdcf02431ba623767fe389337d011df1048dcc24b98ed81cec97627bab454a0",
-    "0x0b5e9666e7323ce925c28201a97ddf4144ac9d148448ed6f49f9008719c1b85b",
-    "0x22ec636f8ad30ef78c42b7fe2be4a4cacf5a445cfb5948224539f59a11d70775",
-]
-new_root = "0x2d05c2650e6c2ef02c6dc7fae7f517b8ac191386666c0b5a68130a8c11092f5f"
-leaf = "0x085ca53be9c9d95b57e6e5fc91c5d531ad9e63e85dd71af7e35562991774b435"
-index = "0"
-mimc_input = [12,45,78,41]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/merkle_insert/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/merkle_insert/src/main.nr
deleted file mode 100644
index 3de10520037..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/merkle_insert/src/main.nr
+++ /dev/null
@@ -1,21 +0,0 @@
-use dep::std;
-
-fn main(
-    old_root: Field,
-    old_leaf: Field,
-    old_hash_path: [Field; 3],
-    new_root: pub Field,
-    leaf: Field,
-    index: Field,
-    mimc_input: [Field; 4],
-) {
-    assert(old_root == std::merkle::compute_merkle_root(old_leaf, index, old_hash_path));
-
-    let calculated_root = std::merkle::compute_merkle_root(leaf, index, old_hash_path);
-    assert(new_root == calculated_root);
-
-    let h = std::hash::mimc_bn254(mimc_input);
-    // Regression test for PR #891
-    std::println(h);
-    assert(h == 18226366069841799622585958305961373004333097209608110160936134895615261821931);
-}
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/modules/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/modules/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/modules/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/modules/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/modules/Prover.toml
deleted file mode 100644
index c0a0cdfbeb0..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/modules/Prover.toml
+++ /dev/null
@@ -1,2 +0,0 @@
-x = "2"
-y = "13"
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/modules/src/foo.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/modules/src/foo.nr
deleted file mode 100644
index 1f771fa9425..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/modules/src/foo.nr
+++ /dev/null
@@ -1,3 +0,0 @@
-fn hello(x : Field) -> Field {
-    x
-}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/modules/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/modules/src/main.nr
deleted file mode 100644
index 167f7e671a0..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/modules/src/main.nr
+++ /dev/null
@@ -1,14 +0,0 @@
-mod foo;
-// This is a comment.
-//
-// `main` is the entry point to a binary
-//
-// You can have a `Binary` or a `Library`
-// Release : 0.2
-//
-// To run a proof on the command line, type `cargo run prove {proof_name}`
-//
-// To verify that proof, type `cargo run verify {proof_name}`
-fn main(x: Field, y: pub Field) {
-    assert(x != foo::hello(y));
-}
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/modules_more/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/modules_more/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/modules_more/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/modules_more/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/modules_more/Prover.toml
deleted file mode 100644
index 39a4ddb9d15..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/modules_more/Prover.toml
+++ /dev/null
@@ -1,4 +0,0 @@
-
-        x = "5"
-        y = "15"
-    
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/modules_more/src/foo.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/modules_more/src/foo.nr
deleted file mode 100644
index ee0d20082f5..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/modules_more/src/foo.nr
+++ /dev/null
@@ -1,5 +0,0 @@
-mod bar;
-
-fn hello(x : Field) -> Field {
-    x
-}
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/modules_more/src/foo/bar.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/modules_more/src/foo/bar.nr
deleted file mode 100644
index a92fb81dceb..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/modules_more/src/foo/bar.nr
+++ /dev/null
@@ -1,3 +0,0 @@
-fn from_bar(x : Field) -> Field {
-    x
-}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/modules_more/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/modules_more/src/main.nr
deleted file mode 100644
index 8862e5a8650..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/modules_more/src/main.nr
+++ /dev/null
@@ -1,6 +0,0 @@
-mod foo;
-
-// An example of the module system
-fn main(x: Field, y: Field) {
-    assert(x != foo::bar::from_bar(y));
-}
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/modulus/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/modulus/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/modulus/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/modulus/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/modulus/Prover.toml
deleted file mode 100644
index d435609bb1a..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/modulus/Prover.toml
+++ /dev/null
@@ -1,290 +0,0 @@
-bn254_modulus_be_bytes = [
-    48,
-    100,
-    78,
-    114,
-    225,
-    49,
-    160,
-    41,
-    184,
-    80,
-    69,
-    182,
-    129,
-    129,
-    88,
-    93,
-    40,
-    51,
-    232,
-    72,
-    121,
-    185,
-    112,
-    145,
-    67,
-    225,
-    245,
-    147,
-    240,
-    0,
-    0,
-    1,
-]
-bn254_modulus_be_bits = [
-    1,
-    1,
-    0,
-    0,
-    0,
-    0,
-    0,
-    1,
-    1,
-    0,
-    0,
-    1,
-    0,
-    0,
-    0,
-    1,
-    0,
-    0,
-    1,
-    1,
-    1,
-    0,
-    0,
-    1,
-    1,
-    1,
-    0,
-    0,
-    1,
-    0,
-    1,
-    1,
-    1,
-    0,
-    0,
-    0,
-    0,
-    1,
-    0,
-    0,
-    1,
-    1,
-    0,
-    0,
-    0,
-    1,
-    1,
-    0,
-    1,
-    0,
-    0,
-    0,
-    0,
-    0,
-    0,
-    0,
-    1,
-    0,
-    1,
-    0,
-    0,
-    1,
-    1,
-    0,
-    1,
-    1,
-    1,
-    0,
-    0,
-    0,
-    0,
-    1,
-    0,
-    1,
-    0,
-    0,
-    0,
-    0,
-    0,
-    1,
-    0,
-    0,
-    0,
-    1,
-    0,
-    1,
-    1,
-    0,
-    1,
-    1,
-    0,
-    1,
-    1,
-    0,
-    1,
-    0,
-    0,
-    0,
-    0,
-    0,
-    0,
-    1,
-    1,
-    0,
-    0,
-    0,
-    0,
-    0,
-    0,
-    1,
-    0,
-    1,
-    0,
-    1,
-    1,
-    0,
-    0,
-    0,
-    0,
-    1,
-    0,
-    1,
-    1,
-    1,
-    0,
-    1,
-    0,
-    0,
-    1,
-    0,
-    1,
-    0,
-    0,
-    0,
-    0,
-    0,
-    1,
-    1,
-    0,
-    0,
-    1,
-    1,
-    1,
-    1,
-    1,
-    0,
-    1,
-    0,
-    0,
-    0,
-    0,
-    1,
-    0,
-    0,
-    1,
-    0,
-    0,
-    0,
-    0,
-    1,
-    1,
-    1,
-    1,
-    0,
-    0,
-    1,
-    1,
-    0,
-    1,
-    1,
-    1,
-    0,
-    0,
-    1,
-    0,
-    1,
-    1,
-    1,
-    0,
-    0,
-    0,
-    0,
-    1,
-    0,
-    0,
-    1,
-    0,
-    0,
-    0,
-    1,
-    0,
-    1,
-    0,
-    0,
-    0,
-    0,
-    1,
-    1,
-    1,
-    1,
-    1,
-    0,
-    0,
-    0,
-    0,
-    1,
-    1,
-    1,
-    1,
-    1,
-    0,
-    1,
-    0,
-    1,
-    1,
-    0,
-    0,
-    1,
-    0,
-    0,
-    1,
-    1,
-    1,
-    1,
-    1,
-    1,
-    0,
-    0,
-    0,
-    0,
-    0,
-    0,
-    0,
-    0,
-    0,
-    0,
-    0,
-    0,
-    0,
-    0,
-    0,
-    0,
-    0,
-    0,
-    0,
-    0,
-    0,
-    0,
-    0,
-    0,
-    0,
-    0,
-    0,
-    1,
-]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/modulus/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/modulus/src/main.nr
deleted file mode 100644
index 4a13a6e06ba..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/modulus/src/main.nr
+++ /dev/null
@@ -1,27 +0,0 @@
-use dep::std;
-
-fn main(bn254_modulus_be_bytes : [u8; 32], bn254_modulus_be_bits : [u1; 254]) -> pub Field {
-    let modulus_size = std::field::modulus_num_bits();
-    // NOTE: The constraints used in this circuit will only work when testing nargo with the plonk bn254 backend
-    assert(modulus_size == 254);
- 
-    let modulus_be_byte_array = std::field::modulus_be_bytes();
-    for i in 0..32 {
-        assert(modulus_be_byte_array[i] == bn254_modulus_be_bytes[i]);
-    }
-    let modulus_le_byte_array = std::field::modulus_le_bytes();
-    for i in 0..32 {
-        assert(modulus_le_byte_array[i] == bn254_modulus_be_bytes[31-i]);
-    }
-
-    let modulus_be_bits = std::field::modulus_be_bits();
-    for i in 0..254 {
-        assert(modulus_be_bits[i] == bn254_modulus_be_bits[i]);
-    }
-    let modulus_le_bits = std::field::modulus_le_bits();
-    for i in 0..254 {
-        assert(modulus_le_bits[i] == bn254_modulus_be_bits[253-i]);
-    }
-
-    modulus_size
-}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/numeric_generics/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/numeric_generics/Nargo.toml
deleted file mode 100644
index d9434868157..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/numeric_generics/Nargo.toml
+++ /dev/null
@@ -1,7 +0,0 @@
-
-        [package]
-        authors = [""]
-        compiler_version = "0.1"
-    
-        [dependencies]
-    
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/numeric_generics/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/numeric_generics/src/main.nr
deleted file mode 100644
index f1efafc19fd..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/numeric_generics/src/main.nr
+++ /dev/null
@@ -1,39 +0,0 @@
-fn main() {
-    let a = id([1, 2]);
-    let b = id([1, 2, 3]);
-
-    let itWorks1 = MyStruct { data: a };
-    assert(itWorks1.data[1] == 2);
-    let itWorks2 = MyStruct { data: b };
-    assert(itWorks2.data[1] == 2);
-
-    let c = [1, 2];
-    let itAlsoWorks = MyStruct { data: c };
-    assert(itAlsoWorks.data[1] == 2);
-
-    assert(foo(itWorks2).data[0] == itWorks2.data[0] + 1);
-}
-
-fn id<I>(x: [Field; I]) -> [Field; I] {
-    x
-}
-
-struct MyStruct<S> {
-    data: [Field; S],
-}
-
-impl<S> MyStruct<S> {
-    fn insert(mut self: Self, index: comptime Field, elem: Field) -> Self {
-        // Regression test for numeric generics on impls
-        assert(index as u64 < S as u64);
-
-        self.data[index] = elem;
-        self
-    }
-}
-
-fn foo(mut s: MyStruct<2+1>) -> MyStruct<10/2-2> {
-    s.data[0] = s.data[0] + 1;
-    s
-}
-
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/pedersen_check/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/pedersen_check/Nargo.toml
deleted file mode 100644
index d9434868157..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/pedersen_check/Nargo.toml
+++ /dev/null
@@ -1,7 +0,0 @@
-
-        [package]
-        authors = [""]
-        compiler_version = "0.1"
-    
-        [dependencies]
-    
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/pedersen_check/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/pedersen_check/Prover.toml
deleted file mode 100644
index 2fb3b1e1abf..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/pedersen_check/Prover.toml
+++ /dev/null
@@ -1,6 +0,0 @@
-x = "0"
-y = "1"
-salt = "42"
-
-out_x = "0x0c5e1ddecd49de44ed5e5798d3f6fb7c71fe3d37f5bee8664cf88a445b5ba0af"
-out_y = "0x230294a041e26fe80b827c2ef5cb8784642bbaa83842da2714d62b1f3c4f9752"
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/pedersen_check/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/pedersen_check/src/main.nr
deleted file mode 100644
index 37fc3f61188..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/pedersen_check/src/main.nr
+++ /dev/null
@@ -1,17 +0,0 @@
-use dep::std;
-
-fn main(x: Field, y: Field, salt: Field, out_x: Field, out_y: Field ) {
-    let res = std::hash::pedersen([x, y]);
-    assert(res[0] == out_x);
-    assert(res[1] == out_y);
-
-    let raw_data = [x,y];
-    let mut state = 0;
-    for i in 0..2 {
-        state = state * 8 + raw_data[i];
-    }
-    state += salt;
-    let hash = std::hash::pedersen([state]);
-    assert(std::hash::pedersen([43])[0] == hash[0]);
-}
-    
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/poseidon_bn254_hash/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/poseidon_bn254_hash/Nargo.toml
deleted file mode 100644
index 6a061f5a217..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/poseidon_bn254_hash/Nargo.toml
+++ /dev/null
@@ -1,6 +0,0 @@
-[package]
-name = "Poseidon 254-bit permutation test on 3 elements with alpha = 5"
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/poseidon_bn254_hash/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/poseidon_bn254_hash/Prover.toml
deleted file mode 100644
index 8eecf9a3db2..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/poseidon_bn254_hash/Prover.toml
+++ /dev/null
@@ -1,4 +0,0 @@
-x1 = [1,2]
-y1 = "0x115cc0f5e7d690413df64c6b9662e9cf2a3617f2743245519e19607a4417189a"
-x2 = [1,2,3,4]
-y2 = "0x299c867db6c1fdd79dcefa40e4510b9837e60ebb1ce0663dbaa525df65250465"
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/poseidon_bn254_hash/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/poseidon_bn254_hash/src/main.nr
deleted file mode 100644
index 37621c732a8..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/poseidon_bn254_hash/src/main.nr
+++ /dev/null
@@ -1,10 +0,0 @@
-use dep::std::hash::poseidon;
-
-fn main(x1: [Field; 2], y1: pub Field, x2: [Field; 4], y2: pub Field)
-{
-    let hash1 = poseidon::bn254::hash_2(x1);
-    assert(hash1 == y1);
-
-    let hash2 = poseidon::bn254::hash_4(x2);
-    assert(hash2 == y2);
-}
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/poseidonsponge_x5_254/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/poseidonsponge_x5_254/Nargo.toml
deleted file mode 100644
index 902abd85754..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/poseidonsponge_x5_254/Nargo.toml
+++ /dev/null
@@ -1,6 +0,0 @@
-[package]
-name = "Variable-length Poseidon-128 sponge test on 7 elements with alpha = 5"
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/poseidonsponge_x5_254/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/poseidonsponge_x5_254/Prover.toml
deleted file mode 100644
index f8a6be57b24..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/poseidonsponge_x5_254/Prover.toml
+++ /dev/null
@@ -1 +0,0 @@
-x = [1,2,3,4,5,6,7]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/poseidonsponge_x5_254/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/poseidonsponge_x5_254/src/main.nr
deleted file mode 100644
index 3addc1cec97..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/poseidonsponge_x5_254/src/main.nr
+++ /dev/null
@@ -1,9 +0,0 @@
-use dep::std::hash::poseidon;
-
-fn main(x: [Field; 7])
-{
-    // Test optimised sponge
-    let result = poseidon::bn254::sponge(x);
-    
-    assert(result == 0x080ae1669d62f0197190573d4a325bfb8d8fc201ce3127cbac0c47a7ac81ac48);
-}
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/pred_eq/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/pred_eq/Nargo.toml
deleted file mode 100644
index d9434868157..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/pred_eq/Nargo.toml
+++ /dev/null
@@ -1,7 +0,0 @@
-
-        [package]
-        authors = [""]
-        compiler_version = "0.1"
-    
-        [dependencies]
-    
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/pred_eq/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/pred_eq/src/main.nr
deleted file mode 100644
index c7986cb7af3..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/pred_eq/src/main.nr
+++ /dev/null
@@ -1,6 +0,0 @@
-use dep::std;
-
-fn main(x: Field, y: Field) {
-    let p = x == y;
-    assert(p == true);
-}
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/regression_method_cannot_be_found/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/regression_method_cannot_be_found/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/regression_method_cannot_be_found/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/regression_method_cannot_be_found/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/regression_method_cannot_be_found/Prover.toml
deleted file mode 100644
index 8b137891791..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/regression_method_cannot_be_found/Prover.toml
+++ /dev/null
@@ -1 +0,0 @@
-
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/scalar_mul/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/scalar_mul/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/scalar_mul/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/scalar_mul/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/scalar_mul/Prover.toml
deleted file mode 100644
index 69b91cb5f31..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/scalar_mul/Prover.toml
+++ /dev/null
@@ -1,7 +0,0 @@
-a = "1"
-a_pub_x = "0x0000000000000000000000000000000000000000000000000000000000000001"
-a_pub_y = "0x0000000000000002cf135e7506a45d632d270d45f1181294833fc48d823f272c"
-
-b = "2"
-b_pub_x = "0x06ce1b0827aafa85ddeb49cdaa36306d19a74caa311e13d46d8bc688cdbffffe"
-b_pub_y = "0x1c122f81a3a14964909ede0ba2a6855fc93faf6fa1a788bf467be7e7a43f80ac"
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/scalar_mul/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/scalar_mul/src/main.nr
deleted file mode 100644
index d9d267f1dcd..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/scalar_mul/src/main.nr
+++ /dev/null
@@ -1,22 +0,0 @@
-use dep::std;
-
-fn main(
-     a: Field, 
-     a_pub_x: pub Field, 
-     a_pub_y: pub Field,
-     b: Field,
-     b_pub_x: pub Field,
-     b_pub_y: pub Field
-) {
-     let mut priv_key = a;
-     let mut pub_x: Field = a_pub_x;
-     let mut pub_y: Field = a_pub_y;
-     if a != 1 { // Change `a` in Prover.toml to test input `b`
-          priv_key = b;
-          pub_x = b_pub_x;
-          pub_y = b_pub_y;
-     }
-     let res = std::scalar_mul::fixed_base(priv_key);
-     assert(res[0] == pub_x);
-     assert(res[1] == pub_y);
-}
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/schnorr/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/schnorr/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/schnorr/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/schnorr/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/schnorr/Prover.toml
deleted file mode 100644
index c5c3ab5101a..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/schnorr/Prover.toml
+++ /dev/null
@@ -1,9 +0,0 @@
-message = [0,1,2,3,4,5,6,7,8,9]
-pub_key_x = "0x17cbd3ed3151ccfd170efe1d54280a6a4822640bf5c369908ad74ea21518a9c5"
-pub_key_y = "0x0e0456e3795c1a31f20035b741cd6158929eeccd320d299cfcac962865a6bc74"
-signature = [
-    5, 202, 31, 146, 81, 242, 246, 69, 43, 107, 249, 153, 198, 44, 14, 111, 191, 121, 137, 166, 
-    160, 103, 18, 181, 243, 233, 226, 95, 67, 16, 37, 128, 85, 76, 19, 253, 30, 77, 192, 53, 138, 
-    205, 69, 33, 236, 163, 83, 194, 84, 137, 184, 221, 176, 121, 179, 27, 63, 70, 54, 16, 176, 
-    250, 39, 239,
-]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/schnorr/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/schnorr/src/main.nr
deleted file mode 100644
index c0933b23029..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/schnorr/src/main.nr
+++ /dev/null
@@ -1,10 +0,0 @@
-use dep::std;
-
-// Note: If main has any unsized types, then the verifier will never be able
-// to figure out the circuit instance
-fn main(message: [u8; 10], pub_key_x: Field, pub_key_y: Field, signature: [u8; 64]) {
-    // Is there ever a situation where someone would want 
-    // to ensure that a signature was invalid?
-    let valid_signature = std::schnorr::verify_signature(pub_key_x,pub_key_y,signature, message);
-    assert(valid_signature);
-}
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/sha256/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/sha256/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/sha256/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/sha256/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/sha256/Prover.toml
deleted file mode 100644
index c4df1b749bb..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/sha256/Prover.toml
+++ /dev/null
@@ -1,36 +0,0 @@
-
-x = 0xbd
-result = [
-        0x68,
-        0x32,
-        0x57,
-        0x20,
-        0xaa,
-        0xbd,
-        0x7c,
-        0x82,
-        0xf3,
-        0x0f,
-        0x55,
-        0x4b,
-        0x31,
-        0x3d,
-        0x05,
-        0x70,
-        0xc9,
-        0x5a,
-        0xcc,
-        0xbb,
-        0x7d,
-        0xc4,
-        0xb5,
-        0xaa,
-        0xe1,
-        0x12,
-        0x04,
-        0xc0,
-        0x8f,
-        0xfe,
-        0x73,
-        0x2b,
-]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/sha256/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/sha256/src/main.nr
deleted file mode 100644
index fd5340e2384..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/sha256/src/main.nr
+++ /dev/null
@@ -1,19 +0,0 @@
-// Sha256 example
-// 
-// Calls Sha256 from the standard library.
-//
-// The Compiler sees this special function and creates an ACIR gate
-//
-// The ACIR SHA256 gate is passed to PLONK who should
-// know how to create the necessary constraints.
-//
-// Not yet here: For R1CS, it is more about manipulating arithmetic gates to get performance
-// This can be done in ACIR!
-use dep::std;
-
-fn main(x: Field, result: [u8; 32]) {
-    // We use the `as` keyword here to denote the fact that we want to take just the first byte from the x Field
-    // The padding is taken care of by the program
-    let digest = std::hash::sha256([x as u8]);
-    assert(digest == result);
-}
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/sha2_blocks/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/sha2_blocks/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/sha2_blocks/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/sha2_blocks/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/sha2_blocks/Prover.toml
deleted file mode 100644
index 3fe435ea07f..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/sha2_blocks/Prover.toml
+++ /dev/null
@@ -1,4 +0,0 @@
-# From https://csrc.nist.gov/CSRC/media/Projects/Cryptographic-Standards-and-Guidelines/documents/examples/SHA256.pdf and https://csrc.nist.gov/CSRC/media/Projects/Cryptographic-Standards-and-Guidelines/documents/examples/SHA512.pdf
-x = [0x61, 0x62, 0x63] # "abc"
-result256 = [0xba, 0x78, 0x16, 0xbf, 0x8f, 0x01, 0xcf, 0xea, 0x41, 0x41, 0x40, 0xde, 0x5d, 0xae, 0x22, 0x23, 0xb0, 0x03, 0x61, 0xa3, 0x96, 0x17, 0x7a, 0x9c, 0xb4, 0x10, 0xff, 0x61, 0xf2, 0x00, 0x15, 0xad]
-result512 = [0xdd, 0xaf, 0x35, 0xa1, 0x93, 0x61, 0x7a, 0xba, 0xcc, 0x41, 0x73, 0x49, 0xae, 0x20, 0x41, 0x31, 0x12, 0xe6, 0xfa, 0x4e, 0x89, 0xa9, 0x7e, 0xa2, 0x0a, 0x9e, 0xee, 0xe6, 0x4b, 0x55, 0xd3, 0x9a, 0x21, 0x92, 0x99, 0x2a, 0x27, 0x4f, 0xc1, 0xa8, 0x36, 0xba, 0x3c, 0x23, 0xa3, 0xfe, 0xeb, 0xbd, 0x45, 0x4d, 0x44, 0x23, 0x64, 0x3c, 0xe8, 0x0e, 0x2a, 0x9a, 0xc9, 0x4f, 0xa5, 0x4c, 0xa4, 0x9f]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/sha2_blocks/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/sha2_blocks/src/main.nr
deleted file mode 100644
index fcdcdb8684f..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/sha2_blocks/src/main.nr
+++ /dev/null
@@ -1,22 +0,0 @@
-// Test Noir implementations of SHA256 and SHA512 on one- and two-block (padded) messages.
-use dep::std;
-
-fn main(x: [u8; 3], result256: [u8; 32], result512: [u8; 64])
-{
-	// One-block tests.
-	let mut digest256 = std::sha256::digest(x);
-	assert(digest256 == result256);
-
-	let mut digest512 = std::sha512::digest(x);
-	assert(digest512 == result512);
-
-	// Two-block SHA256 test. Taken from https://csrc.nist.gov/CSRC/media/Projects/Cryptographic-Standards-and-Guidelines/documents/examples/SHA256.pdf
-	let y: [u8; 56] = [97,98,99,100,98,99,100,101,99,100,101,102,100,101,102,103,101,102,103,104,102,103,104,105,103,104,105,106,104,105,106,107,105,106,107,108,106,107,108,109,107,108,109,110,108,109,110,111,109,110,111,112,110,111,112,113]; // "abcdbcdecdefdefgefghfghighijhijkijkljklmklmnlmnomnopnopq"
-	digest256 = std::sha256::digest(y);
-	assert(digest256 == [36,141,106,97,210,6,56,184,229,192,38,147,12,62,96,57,163,60,228,89,100,255,33,103,246,236,237,212,25,219,6,193]);
-
-	// Two-block SHA256 test. Taken from https://csrc.nist.gov/CSRC/media/Projects/Cryptographic-Standards-and-Guidelines/documents/examples/SHA512.pdf
-	let z: [u8; 112] = [97,98,99,100,101,102,103,104,98,99,100,101,102,103,104,105,99,100,101,102,103,104,105,106,100,101,102,103,104,105,106,107,101,102,103,104,105,106,107,108,102,103,104,105,106,107,108,109,103,104,105,106,107,108,109,110,104,105,106,107,108,109,110,111,105,106,107,108,109,110,111,112,106,107,108,109,110,111,112,113,107,108,109,110,111,112,113,114,108,109,110,111,112,113,114,115,109,110,111,112,113,114,115,116,110,111,112,113,114,115,116,117]; // "abcdefghbcdefghicdefghijdefghijkefghijklfghijklmghijklmnhijklmnoijklmnopjklmnopqklmnopqrlmnopqrsmnopqrstnopqrstu"
-	digest512 = std::sha512::digest(z);
-	assert(digest512 == [142,149,155,117,218,227,19,218,140,244,247,40,20,252,20,63,143,119,121,198,235,159,127,161,114,153,174,173,182,136,144,24,80,29,40,158,73,0,247,228,51,27,153,222,196,181,67,58,199,211,41,238,182,221,38,84,94,150,229,91,135,75,233,9]);
-}
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/sha2_byte/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/sha2_byte/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/sha2_byte/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/sha2_byte/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/sha2_byte/Prover.toml
deleted file mode 100644
index 2f82f14a58d..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/sha2_byte/Prover.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-# Values obtainable from https://emn178.github.io/online-tools/sha256.html and https://emn178.github.io/online-tools/sha512.html
-x = 0xbd
-result256 = [0x68, 0x32, 0x57, 0x20, 0xaa, 0xbd, 0x7c, 0x82, 0xf3, 0x0f, 0x55, 0x4b, 0x31, 0x3d, 0x05, 0x70, 0xc9, 0x5a, 0xcc, 0xbb, 0x7d, 0xc4, 0xb5, 0xaa, 0xe1, 0x12, 0x04, 0xc0, 0x8f, 0xfe, 0x73, 0x2b]
-result512 = [0x29, 0x6e, 0x22, 0x67, 0xd7, 0x4c, 0x27, 0x8d, 0xaa, 0xaa, 0x94, 0x0d, 0x17, 0xb0, 0xcf, 0xb7, 0x4a, 0x50, 0x83, 0xf8, 0xe0, 0x69, 0x72, 0x6d, 0x8c, 0x84, 0x1c, 0xbe, 0x59, 0x6e, 0x04, 0x31, 0xcb, 0x77, 0x41, 0xa5, 0xb5, 0x0f, 0x71, 0x66, 0x6c, 0xfd, 0x54, 0xba, 0xcb, 0x7b, 0x00, 0xae, 0xa8, 0x91, 0x49, 0x9c, 0xf4, 0xef, 0x6a, 0x03, 0xc8, 0xa8, 0x3f, 0xe3, 0x7c, 0x3f, 0x7b, 0xaf]
-
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/sha2_byte/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/sha2_byte/src/main.nr
deleted file mode 100644
index a7cc9daebb9..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/sha2_byte/src/main.nr
+++ /dev/null
@@ -1,11 +0,0 @@
-// Test Noir implementations of SHA256 and SHA512 on a one-byte message.
-use dep::std;
-
-fn main(x: Field, result256: [u8; 32], result512: [u8; 64])
-{
-	let digest256 = std::sha256::digest([x as u8]);
-	assert(digest256 == result256);
-
-	let digest512 = std::sha512::digest([x as u8]);
-	assert(digest512 == result512);
-}
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/signed_division/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/signed_division/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/signed_division/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/signed_division/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/signed_division/Prover.toml
deleted file mode 100644
index ee6f0ef229a..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/signed_division/Prover.toml
+++ /dev/null
@@ -1,3 +0,0 @@
-x = "7"
-y = "3"
-z = "2"
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_array_param/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/simple_array_param/Nargo.toml
deleted file mode 100644
index 670888e37cd..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_array_param/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.6.0"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_bitwise/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/simple_bitwise/Nargo.toml
deleted file mode 100644
index 670888e37cd..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_bitwise/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.6.0"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_comparison/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/simple_comparison/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_comparison/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_mut/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/simple_mut/Nargo.toml
deleted file mode 100644
index 670888e37cd..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_mut/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.6.0"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_not/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/simple_not/Nargo.toml
deleted file mode 100644
index 670888e37cd..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_not/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.6.0"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_print/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/simple_print/Nargo.toml
deleted file mode 100644
index 670888e37cd..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_print/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.6.0"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_program_addition/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/simple_program_addition/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_program_addition/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_program_no_body/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/simple_program_no_body/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_program_no_body/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_radix/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/simple_radix/Nargo.toml
deleted file mode 100644
index 670888e37cd..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_radix/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.6.0"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_range/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/simple_range/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_range/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_shield/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/simple_shield/Prover.toml
deleted file mode 100644
index 5a9b2f21b9b..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_shield/Prover.toml
+++ /dev/null
@@ -1,11 +0,0 @@
-# Random test key
-priv_key = "0x000000000000000000000000000000000000000000000000000000616c696365"
-note_root = "0x21386402d57460963f45f32577dc3902c38a6f6fab9ec7b1b708a92e48745de7"
-index = "0"
-note_hash_path = [
-    "0x1cdcf02431ba623767fe389337d011df1048dcc24b98ed81cec97627bab454a0",
-    "0x0b5e9666e7323ce925c28201a97ddf4144ac9d148448ed6f49f9008719c1b85b",
-    "0x22ec636f8ad30ef78c42b7fe2be4a4cacf5a445cfb5948224539f59a11d70775",
-]
-to_pubkey_x = "0x0000000000000000000000000000000000000000000000000000000000000001"
-to_pubkey_y = "0x0000000000000002cf135e7506a45d632d270d45f1181294833fc48d823f272c"
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_shield/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/simple_shield/src/main.nr
deleted file mode 100644
index 18fccd862b5..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_shield/src/main.nr
+++ /dev/null
@@ -1,35 +0,0 @@
-use dep::std;
-
-fn main(
-  // Public key of note
-  // all notes have the same denomination
-  priv_key: Field, 
-
-  // Merkle membership proof
-  note_root: pub Field, 
-  index: Field,
-  note_hash_path: [Field; 3],
-
-  // Receiver public key
-  to_pubkey_x: Field, 
-  to_pubkey_y: Field, 
-) -> pub [Field; 2] {
-    // Compute public key from private key to show ownership
-    let pubkey = std::scalar_mul::fixed_base(priv_key);
-    let pubkey_x = pubkey[0];
-    let pubkey_y = pubkey[1];
-
-    // Compute input note commitment
-    let note_commitment = std::hash::pedersen([pubkey_x, pubkey_y]);
-    
-    // Compute input note nullifier
-    let nullifier = std::hash::pedersen([note_commitment[0], index, priv_key]);
-
-    // Compute output note nullifier
-    let receiver_note_commitment = std::hash::pedersen([to_pubkey_x, to_pubkey_y]);
-
-    // Check that the input note nullifier is in the root
-    assert(note_root == std::merkle::compute_merkle_root(note_commitment[0], index, note_hash_path));
-
-    [nullifier[0], receiver_note_commitment[0]]
-}
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_shift_left_right/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/simple_shift_left_right/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/simple_shift_left_right/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/slices/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/slices/Nargo.toml
deleted file mode 100644
index 670888e37cd..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/slices/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.6.0"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/strings/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/strings/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/strings/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/strings/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/strings/Prover.toml
deleted file mode 100644
index 0d1bd92b5de..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/strings/Prover.toml
+++ /dev/null
@@ -1,4 +0,0 @@
-message = "hello world"
-y = 5
-hex_as_string = "0x41"
-hex_as_field = "0x41"
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/strings/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/strings/src/main.nr
deleted file mode 100644
index bee2370201c..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/strings/src/main.nr
+++ /dev/null
@@ -1,56 +0,0 @@
-use dep::std;
-
-fn main(message : pub str<11>, y : Field, hex_as_string : str<4>, hex_as_field : Field) {
-    let mut bad_message = "hello world";
-
-    assert(message == "hello world");
-    bad_message = "helld world";
-    let x = 10;
-    let z = x * 5;
-    std::println(10);
-
-    std::println(z); // x * 5 in println not yet supported
-    std::println(x);
-
-    let array = [1, 2, 3, 5, 8];
-    assert(y == 5); // Change to y != 5 to see how the later print statements are not called
-    std::println(array);
-
-    std::println(bad_message);
-    assert(message != bad_message);
-
-    let hash = std::hash::pedersen([x]);
-    std::println(hash);
-    
-    assert(hex_as_string == "0x41");
-    // assert(hex_as_string != 0x41); This will fail with a type mismatch between str[4] and Field
-    assert(hex_as_field == 0x41);
-}
-
-#[test]
-fn test_prints_strings() {
-    let message = "hello world!";
-
-    std::println(message);
-    std::println("goodbye world");
-}
-
-#[test]
-fn test_prints_array() {
-    let array = [1, 2, 3, 5, 8];
-
-    // TODO: Printing structs currently not supported
-    // let s = Test { a: 1, b: 2, c: [3, 4] };
-    // std::println(s);
-
-    std::println(array);
-
-    let hash = std::hash::pedersen(array);
-    std::println(hash);
-}
-
-struct Test {
-    a: Field,
-    b: Field,
-    c: [Field; 2],
-}
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/struct/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/struct/Nargo.toml
deleted file mode 100644
index d9434868157..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/struct/Nargo.toml
+++ /dev/null
@@ -1,7 +0,0 @@
-
-        [package]
-        authors = [""]
-        compiler_version = "0.1"
-    
-        [dependencies]
-    
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/struct/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/struct/Prover.toml
deleted file mode 100644
index 7d59cc81807..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/struct/Prover.toml
+++ /dev/null
@@ -1,2 +0,0 @@
-x = "0"
-y = "1"
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/struct/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/struct/src/main.nr
deleted file mode 100644
index 6d61393920d..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/struct/src/main.nr
+++ /dev/null
@@ -1,77 +0,0 @@
-use dep::std;
-
-struct Foo {
-    bar: Field,
-    array: [Field; 2],
-}
-
-struct Pair {
-    first: Foo,
-    second: Field,
-}
-
-impl Foo {
-    fn default(x: Field,y: Field) -> Self {
-        Self { bar: 0, array: [x,y] }
-    }
-}
-
-impl Pair {
-    fn foo(p: Self) -> Foo {
-        p.first
-    }
-
-    fn bar(self) -> Field {
-        self.foo().bar
-    }
-}
-
-struct Nested {
-    a: Field,
-    b: Field
-}
-struct MyStruct {
-    my_bool: bool,
-    my_int: u32,
-    my_nest: Nested,
-}
-fn test_struct_in_tuple(a_bool : bool,x:Field, y:Field) -> (MyStruct, bool) {
-    let my_struct = MyStruct {
-        my_bool: a_bool,
-        my_int: 5,
-        my_nest: Nested{a:x,b:y},
-    };
-    (my_struct, a_bool)
-}
-
-struct Animal {
-    legs: Field,
-    eyes: u8,
-}
-
-fn get_dog() -> Animal {
-    let dog = Animal { legs: 4, eyes: 2 };
-    dog
-}
-
-fn main(x: Field, y: Field) {
-    let first = Foo::default(x,y);
-    let p = Pair { first, second: 1 };
-
-    assert(p.bar() == x);
-    assert(p.second == y);
-    assert(p.first.array[0] != p.first.array[1]);
-
-    // Nested structs
-    let (struct_from_tuple, a_bool) = test_struct_in_tuple(true,x,y);
-    assert(struct_from_tuple.my_bool == true);
-    assert(a_bool == true);
-    assert(struct_from_tuple.my_int == 5);
-    assert(struct_from_tuple.my_nest.a == 0);
-
-    // Regression test for issue #670
-    let Animal { legs, eyes } = get_dog();
-    let six = legs + eyes as Field;
-
-    assert(six == 6);
-}
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/struct_array_inputs/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/struct_array_inputs/Nargo.toml
deleted file mode 100644
index 670888e37cd..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/struct_array_inputs/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.6.0"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/struct_fields_ordering/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/struct_fields_ordering/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/struct_fields_ordering/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/struct_fields_ordering/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/struct_fields_ordering/Prover.toml
deleted file mode 100644
index 70640bba4cc..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/struct_fields_ordering/Prover.toml
+++ /dev/null
@@ -1,3 +0,0 @@
-[y]
-foo = "5"
-bar = "7"
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/struct_fields_ordering/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/struct_fields_ordering/src/main.nr
deleted file mode 100644
index 0d6e411addf..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/struct_fields_ordering/src/main.nr
+++ /dev/null
@@ -1,14 +0,0 @@
-use dep::std;
-
-// Note that fields are not in alphabetical order.
-// We want to check that this ordering is maintained
-struct myStruct {
-    foo: u32,
-    bar: Field,
-}
-
-fn main(y : pub myStruct) {
-    assert(y.foo == 5);
-    assert(y.bar == 7);
-}
-
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/struct_inputs/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/struct_inputs/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/struct_inputs/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/struct_inputs/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/struct_inputs/Prover.toml
deleted file mode 100644
index 339da5b1a00..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/struct_inputs/Prover.toml
+++ /dev/null
@@ -1,19 +0,0 @@
-x = "5"
-
-[y]
-foo = "5"
-bar = "10"
-message = "hello"
-
-[z]
-val = "1"
-array = [0, 1]
-message = "helld"
-
-[a]
-baz = 0
-
-[a.bar_struct]
-val = "1"
-array = [0, 1]
-message = "hello"
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/struct_inputs/src/foo.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/struct_inputs/src/foo.nr
deleted file mode 100644
index 281769cfb07..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/struct_inputs/src/foo.nr
+++ /dev/null
@@ -1,6 +0,0 @@
-mod bar;
-
-struct fooStruct {
-    bar_struct: bar::barStruct,
-    baz: Field,
-}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/struct_inputs/src/foo/bar.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/struct_inputs/src/foo/bar.nr
deleted file mode 100644
index d1963f4a0a7..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/struct_inputs/src/foo/bar.nr
+++ /dev/null
@@ -1,7 +0,0 @@
-global N = 2;
-
-struct barStruct {
-    val: Field,
-    array: [Field; 2],
-    message: str<5>,
-}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/struct_inputs/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/struct_inputs/src/main.nr
deleted file mode 100644
index fe77ed6eee6..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/struct_inputs/src/main.nr
+++ /dev/null
@@ -1,36 +0,0 @@
-use dep::std;
-
-mod foo;
-
-struct myStruct {
-    foo: u32,
-    bar: Field,
-    message: str<5>,
-}
-
-fn main(x : Field, y : pub myStruct, z: pub foo::bar::barStruct, a: pub foo::fooStruct) -> pub Field {
-    let struct_from_bar = foo::bar::barStruct { val: 1, array: [0, 1], message: "hello" };
-
-    check_inner_struct(a, z);
-
-    for i in 0 .. struct_from_bar.array.len() {
-        assert(struct_from_bar.array[i] == z.array[i]);
-    }
-    assert(z.val == struct_from_bar.val);
-
-    assert((struct_from_bar.val * x) == x);
-
-    assert(x != y.bar);
-
-    assert(y.message == "hello");
-    assert(a.bar_struct.message == struct_from_bar.message);
-    
-    a.bar_struct.array[1]
-}
-
-fn check_inner_struct(a: foo::fooStruct, z: foo::bar::barStruct) {
-    assert(a.bar_struct.val == z.val);
-    for i in 0.. a.bar_struct.array.len() {
-        assert(a.bar_struct.array[i] == z.array[i]);
-    }
-}
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/submodules/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/submodules/Nargo.toml
deleted file mode 100644
index d9434868157..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/submodules/Nargo.toml
+++ /dev/null
@@ -1,7 +0,0 @@
-
-        [package]
-        authors = [""]
-        compiler_version = "0.1"
-    
-        [dependencies]
-    
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/submodules/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/submodules/Prover.toml
deleted file mode 100644
index b6626a67e19..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/submodules/Prover.toml
+++ /dev/null
@@ -1,2 +0,0 @@
-x = 1
-y = 0
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/submodules/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/submodules/src/main.nr
deleted file mode 100644
index 9bfe382663f..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/submodules/src/main.nr
+++ /dev/null
@@ -1,17 +0,0 @@
-use mysubmodule::my_helper;
-
-fn main(x: u1, y: u1) {
-    my_helper();
-    mysubmodule::my_bool_or(x, y);
-}
-
-mod mysubmodule {
-    use dep::std;
-
-    fn my_bool_or(x: u1, y: u1) {
-        assert(x | y == 1);
-    }
-
-    fn my_helper() {}
-}
-    
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/to_be_bytes/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/to_be_bytes/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/to_be_bytes/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/to_bytes_integration/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/to_bytes_integration/Nargo.toml
deleted file mode 100644
index 5082c6e12ec..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/to_bytes_integration/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/to_bytes_integration/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/to_bytes_integration/Prover.toml
deleted file mode 100644
index bc4693e434a..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/to_bytes_integration/Prover.toml
+++ /dev/null
@@ -1,2 +0,0 @@
-x = "2040124"
-a = "0x2000000000000000000000000000000000000000000000000000000000000000"
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/to_le_bytes/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/to_le_bytes/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/to_le_bytes/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/tuples/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/tuples/Nargo.toml
deleted file mode 100644
index 5082c6e12ec..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/tuples/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/tuples/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/tuples/Prover.toml
deleted file mode 100644
index a0397e89477..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/tuples/Prover.toml
+++ /dev/null
@@ -1,2 +0,0 @@
-x = "1"
-y = "0"
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/tuples/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/tuples/src/main.nr
deleted file mode 100644
index 45d8380372b..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/tuples/src/main.nr
+++ /dev/null
@@ -1,29 +0,0 @@
-use dep::std;
-
-fn main(x: Field, y: Field) {
-    let pair = (x, y);
-    assert(pair.0 == 1);
-    assert(pair.1 == 0);
-
-    let (a, b) = if true { (0, 1) } else { (2, 3) };
-    assert(a == 0);
-    assert(b == 1);
-
-    let (u,v) = if x as u32 < 1 {
-        (x, x + 1)
-    } else {
-        (x + 1, x)
-    };
-    assert(u == x+1);
-    assert(v == x);
-
-    // Test mutating tuples
-    let mut mutable = ((0, 0), 1, 2, 3);
-    mutable.0 = (x, y);
-    mutable.2 = 7;
-    assert(mutable.0.0 == 1);
-    assert(mutable.0.1 == 0);
-    assert(mutable.1 == 1);
-    assert(mutable.2 == 7);
-    assert(mutable.3 == 3);
-}
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/workspace/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/workspace/Nargo.toml
deleted file mode 100644
index 36db098686f..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/workspace/Nargo.toml
+++ /dev/null
@@ -1,2 +0,0 @@
-[workspace]
-members = ["crates/a", "crates/b"]
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/workspace/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/workspace/Prover.toml
deleted file mode 100644
index a0397e89477..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/workspace/Prover.toml
+++ /dev/null
@@ -1,2 +0,0 @@
-x = "1"
-y = "0"
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/workspace/crates/a/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/workspace/crates/a/src/main.nr
deleted file mode 100644
index 81847a9031d..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/workspace/crates/a/src/main.nr
+++ /dev/null
@@ -1,11 +0,0 @@
-fn main(x : Field, y : pub Field) {
-    assert(x != y);
-}
-
-#[test]
-fn a() {
-    main(1, 2);
-
-    // Uncomment to make test fail
-    // main(1, 1);
-}
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/workspace/crates/b/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/workspace/crates/b/src/main.nr
deleted file mode 100644
index 512f99feeca..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/workspace/crates/b/src/main.nr
+++ /dev/null
@@ -1,11 +0,0 @@
-fn main(x : Field, y : pub Field) {
-    assert(x != y);
-}
-
-#[test]
-fn b() {
-    main(1, 2);
-
-    // Uncomment to make test fail
-    // main(1, 1);
-}
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/workspace_default_member/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/workspace_default_member/Nargo.toml
deleted file mode 100644
index 3828c5d0677..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/workspace_default_member/Nargo.toml
+++ /dev/null
@@ -1,3 +0,0 @@
-[workspace]
-members = ["a"]
-default-member = "a"
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/workspace_default_member/Prover.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/workspace_default_member/Prover.toml
deleted file mode 100644
index 8c12ebba6cf..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/workspace_default_member/Prover.toml
+++ /dev/null
@@ -1,2 +0,0 @@
-x = "1"
-y = "2"
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/workspace_default_member/a/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/workspace_default_member/a/Nargo.toml
deleted file mode 100644
index dc0c2f8917c..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/workspace_default_member/a/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.8.0"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/workspace_default_member/a/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/workspace_default_member/a/src/main.nr
deleted file mode 100644
index 206dc46d57a..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/workspace_default_member/a/src/main.nr
+++ /dev/null
@@ -1,11 +0,0 @@
-fn main(x : Field, y : pub Field) {
-    assert(x != y);
-}
-
-#[test]
-fn test_main() {
-    main(1, 2);
-
-    // Uncomment to make test fail
-    // main(1, 1);
-}
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/xor/Nargo.toml b/crates/nargo_cli/tests/test_data_ssa_refactor/xor/Nargo.toml
deleted file mode 100644
index e0b467ce5da..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/xor/Nargo.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[package]
-authors = [""]
-compiler_version = "0.1"
-
-[dependencies]
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_data_ssa_refactor/xor/src/main.nr b/crates/nargo_cli/tests/test_data_ssa_refactor/xor/src/main.nr
deleted file mode 100644
index e893c938fc3..00000000000
--- a/crates/nargo_cli/tests/test_data_ssa_refactor/xor/src/main.nr
+++ /dev/null
@@ -1,5 +0,0 @@
-fn main(x : u32, y : pub u32) {
-    let m = x ^ y;
-
-    assert(m != 10);
-}
\ No newline at end of file
diff --git a/crates/nargo_cli/tests/test_libraries/bad_impl/Nargo.toml b/crates/nargo_cli/tests/test_libraries/bad_impl/Nargo.toml
new file mode 100644
index 00000000000..8e64e10fc64
--- /dev/null
+++ b/crates/nargo_cli/tests/test_libraries/bad_impl/Nargo.toml
@@ -0,0 +1,6 @@
+[package]
+name = "bad_impl"
+authors = [""]
+compiler_version = "0.7.1"
+
+[dependencies]
diff --git a/crates/nargo_cli/tests/test_libraries/bad_impl/src/lib.nr b/crates/nargo_cli/tests/test_libraries/bad_impl/src/lib.nr
new file mode 100644
index 00000000000..a96a6cbf91f
--- /dev/null
+++ b/crates/nargo_cli/tests/test_libraries/bad_impl/src/lib.nr
@@ -0,0 +1,5 @@
+impl Field {
+    fn something(self) -> Field {
+        self
+    }
+}
diff --git a/crates/nargo_cli/tests/test_libraries/diamond_deps_1/Nargo.toml b/crates/nargo_cli/tests/test_libraries/diamond_deps_1/Nargo.toml
index 1241b147d83..7e8927d3907 100644
--- a/crates/nargo_cli/tests/test_libraries/diamond_deps_1/Nargo.toml
+++ b/crates/nargo_cli/tests/test_libraries/diamond_deps_1/Nargo.toml
@@ -1,6 +1,7 @@
 [package]
+name = "diamond_deps_1"
 authors = [""]
 compiler_version = "0.7.1"
 
 [dependencies]
-dep2 = { path = "../diamond_deps_2" }
\ No newline at end of file
+dep2 = { path = "../diamond_deps_2" }
diff --git a/crates/nargo_cli/tests/test_libraries/diamond_deps_2/Nargo.toml b/crates/nargo_cli/tests/test_libraries/diamond_deps_2/Nargo.toml
index 7cae77988e3..7b5fd01b8d6 100644
--- a/crates/nargo_cli/tests/test_libraries/diamond_deps_2/Nargo.toml
+++ b/crates/nargo_cli/tests/test_libraries/diamond_deps_2/Nargo.toml
@@ -1,5 +1,6 @@
 [package]
+name = "diamond_deps_2"
 authors = [""]
 compiler_version = "0.7.1"
 
-[dependencies]
\ No newline at end of file
+[dependencies]
diff --git a/crates/noirc_abi/src/input_parser/json.rs b/crates/noirc_abi/src/input_parser/json.rs
index 748c0d09e04..6468b48c857 100644
--- a/crates/noirc_abi/src/input_parser/json.rs
+++ b/crates/noirc_abi/src/input_parser/json.rs
@@ -59,7 +59,7 @@ pub(crate) fn serialize_to_json(
 
 #[derive(Debug, Deserialize, Serialize, Clone)]
 #[serde(untagged)]
-enum JsonTypes {
+pub(super) enum JsonTypes {
     // This is most likely going to be a hex string
     // But it is possible to support UTF-8
     String(String),
@@ -78,14 +78,13 @@ enum JsonTypes {
 }
 
 impl JsonTypes {
-    fn try_from_input_value(
+    pub(super) fn try_from_input_value(
         value: &InputValue,
         abi_type: &AbiType,
     ) -> Result<JsonTypes, InputParserError> {
         let json_value = match (value, abi_type) {
             (InputValue::Field(f), AbiType::Field | AbiType::Integer { .. }) => {
-                let f_str = format!("0x{}", f.to_hex());
-                JsonTypes::String(f_str)
+                JsonTypes::String(Self::format_field_string(*f))
             }
             (InputValue::Field(f), AbiType::Boolean) => JsonTypes::Bool(f.is_one()),
 
@@ -109,6 +108,21 @@ impl JsonTypes {
         };
         Ok(json_value)
     }
+
+    /// This trims any leading zeroes.
+    /// A singular '0' will be prepended as well if the trimmed string has an odd length.
+    /// A hex string's length needs to be even to decode into bytes, as two digits correspond to
+    /// one byte.
+    fn format_field_string(field: FieldElement) -> String {
+        if field.is_zero() {
+            return "0x00".to_owned();
+        }
+        let mut trimmed_field = field.to_hex().trim_start_matches('0').to_owned();
+        if trimmed_field.len() % 2 != 0 {
+            trimmed_field = "0".to_owned() + &trimmed_field;
+        }
+        "0x".to_owned() + &trimmed_field
+    }
 }
 
 impl InputValue {
@@ -161,3 +175,13 @@ impl InputValue {
         Ok(input_value)
     }
 }
+
+impl std::fmt::Display for JsonTypes {
+    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
+        // From the docs: https://doc.rust-lang.org/std/fmt/struct.Error.html
+        // This type does not support transmission of an error other than that an error
+        // occurred. Any extra information must be arranged to be transmitted through
+        // some other means.
+        write!(f, "{}", serde_json::to_string(&self).map_err(|_| std::fmt::Error)?)
+    }
+}
diff --git a/crates/noirc_abi/src/input_parser/mod.rs b/crates/noirc_abi/src/input_parser/mod.rs
index da9d777d0ab..e4adbb3d8cf 100644
--- a/crates/noirc_abi/src/input_parser/mod.rs
+++ b/crates/noirc_abi/src/input_parser/mod.rs
@@ -1,13 +1,13 @@
 mod json;
 mod toml;
 
-use std::{collections::BTreeMap, path::Path};
+use std::collections::BTreeMap;
 
 use acvm::FieldElement;
 use serde::Serialize;
 
-use crate::errors::InputParserError;
-use crate::{Abi, AbiType};
+use crate::errors::{AbiError, InputParserError};
+use crate::{decode_value, Abi, AbiType};
 /// This is what all formats eventually transform into
 /// For example, a toml file will parse into TomlTypes
 /// and those TomlTypes will be mapped to Value
@@ -67,10 +67,33 @@ impl InputValue {
     }
 }
 
-/// Parses the initial Witness Values that are needed to seed the
-/// Partial Witness generator
-pub trait InitialWitnessParser {
-    fn parse_initial_witness<P: AsRef<Path>>(&self, path: P) -> BTreeMap<String, InputValue>;
+/// In order to display an `InputValue` we need an `AbiType` to accurately
+/// convert the value into a human-readable format.
+pub struct InputValueDisplay {
+    input_value: InputValue,
+    abi_type: AbiType,
+}
+
+impl InputValueDisplay {
+    pub fn try_from_fields(
+        field_iterator: &mut impl Iterator<Item = FieldElement>,
+        abi_type: AbiType,
+    ) -> Result<Self, AbiError> {
+        let input_value = decode_value(field_iterator, &abi_type)?;
+        Ok(InputValueDisplay { input_value, abi_type })
+    }
+}
+
+impl std::fmt::Display for InputValueDisplay {
+    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
+        // From the docs: https://doc.rust-lang.org/std/fmt/struct.Error.html
+        // This type does not support transmission of an error other than that an error
+        // occurred. Any extra information must be arranged to be transmitted through
+        // some other means.
+        let json_value = json::JsonTypes::try_from_input_value(&self.input_value, &self.abi_type)
+            .map_err(|_| std::fmt::Error)?;
+        write!(f, "{}", serde_json::to_string(&json_value).map_err(|_| std::fmt::Error)?)
+    }
 }
 
 /// The different formats that are supported when parsing
diff --git a/crates/noirc_abi/src/lib.rs b/crates/noirc_abi/src/lib.rs
index 856889b3860..5f8c22a6652 100644
--- a/crates/noirc_abi/src/lib.rs
+++ b/crates/noirc_abi/src/lib.rs
@@ -117,15 +117,6 @@ pub enum Sign {
 }
 
 impl AbiType {
-    pub fn num_elements(&self) -> usize {
-        match self {
-            AbiType::Field | AbiType::Integer { .. } | AbiType::Boolean => 1,
-            AbiType::Array { length, typ: _ } => *length as usize,
-            AbiType::Struct { fields, .. } => fields.len(),
-            AbiType::String { length } => *length as usize,
-        }
-    }
-
     /// Returns the number of field elements required to represent the type once encoded.
     pub fn field_count(&self) -> u32 {
         match self {
@@ -345,7 +336,7 @@ impl Abi {
                             .copied()
                     })?;
 
-                Self::decode_value(&mut param_witness_values.into_iter(), &typ)
+                decode_value(&mut param_witness_values.into_iter(), &typ)
                     .map(|input_value| (name.clone(), input_value))
             })?;
 
@@ -362,7 +353,7 @@ impl Abi {
                         .copied()
                 })
             {
-                Some(Self::decode_value(&mut return_witness_values.into_iter(), return_type)?)
+                Some(decode_value(&mut return_witness_values.into_iter(), return_type)?)
             } else {
                 // Unlike for the circuit inputs, we tolerate not being able to find the witness values for the return value.
                 // This is because the user may be decoding a partial witness map for which is hasn't been calculated yet.
@@ -375,49 +366,48 @@ impl Abi {
 
         Ok((public_inputs_map, return_value))
     }
+}
 
-    fn decode_value(
-        field_iterator: &mut impl Iterator<Item = FieldElement>,
-        value_type: &AbiType,
-    ) -> Result<InputValue, AbiError> {
-        // This function assumes that `field_iterator` contains enough `FieldElement`s in order to decode a `value_type`
-        // `Abi.decode` enforces that the encoded inputs matches the expected length defined by the ABI so this is safe.
-        let value = match value_type {
-            AbiType::Field | AbiType::Integer { .. } | AbiType::Boolean => {
-                let field_element = field_iterator.next().unwrap();
-
-                InputValue::Field(field_element)
-            }
-            AbiType::Array { length, typ } => {
-                let length = *length as usize;
-                let mut array_elements = Vec::with_capacity(length);
-                for _ in 0..length {
-                    array_elements.push(Self::decode_value(field_iterator, typ)?);
-                }
-
-                InputValue::Vec(array_elements)
+fn decode_value(
+    field_iterator: &mut impl Iterator<Item = FieldElement>,
+    value_type: &AbiType,
+) -> Result<InputValue, AbiError> {
+    // This function assumes that `field_iterator` contains enough `FieldElement`s in order to decode a `value_type`
+    // `Abi.decode` enforces that the encoded inputs matches the expected length defined by the ABI so this is safe.
+    let value = match value_type {
+        AbiType::Field | AbiType::Integer { .. } | AbiType::Boolean => {
+            let field_element = field_iterator.next().unwrap();
+
+            InputValue::Field(field_element)
+        }
+        AbiType::Array { length, typ } => {
+            let length = *length as usize;
+            let mut array_elements = Vec::with_capacity(length);
+            for _ in 0..length {
+                array_elements.push(decode_value(field_iterator, typ)?);
             }
-            AbiType::String { length } => {
-                let field_elements: Vec<FieldElement> =
-                    field_iterator.take(*length as usize).collect();
 
-                InputValue::String(decode_string_value(&field_elements))
-            }
-            AbiType::Struct { fields, .. } => {
-                let mut struct_map = BTreeMap::new();
+            InputValue::Vec(array_elements)
+        }
+        AbiType::String { length } => {
+            let field_elements: Vec<FieldElement> = field_iterator.take(*length as usize).collect();
 
-                for (field_key, param_type) in fields {
-                    let field_value = Self::decode_value(field_iterator, param_type)?;
+            InputValue::String(decode_string_value(&field_elements))
+        }
+        AbiType::Struct { fields, .. } => {
+            let mut struct_map = BTreeMap::new();
 
-                    struct_map.insert(field_key.to_owned(), field_value);
-                }
+            for (field_key, param_type) in fields {
+                let field_value = decode_value(field_iterator, param_type)?;
 
-                InputValue::Struct(struct_map)
+                struct_map.insert(field_key.to_owned(), field_value);
             }
-        };
 
-        Ok(value)
-    }
+            InputValue::Struct(struct_map)
+        }
+    };
+
+    Ok(value)
 }
 
 pub fn decode_string_value(field_elements: &[FieldElement]) -> String {
diff --git a/crates/noirc_driver/src/lib.rs b/crates/noirc_driver/src/lib.rs
index b4d0e636e20..f2537bb88fe 100644
--- a/crates/noirc_driver/src/lib.rs
+++ b/crates/noirc_driver/src/lib.rs
@@ -7,14 +7,14 @@ use clap::Args;
 use fm::FileId;
 use noirc_abi::FunctionSignature;
 use noirc_errors::{CustomDiagnostic, FileDiagnostic};
-use noirc_evaluator::{create_circuit, ssa_refactor::experimental_create_circuit};
-use noirc_frontend::graph::{CrateId, CrateName, CrateType, LOCAL_CRATE};
+use noirc_evaluator::create_circuit;
+use noirc_frontend::graph::{CrateId, CrateName, CrateType};
 use noirc_frontend::hir::def_map::{Contract, CrateDefMap};
 use noirc_frontend::hir::Context;
 use noirc_frontend::monomorphization::monomorphize;
 use noirc_frontend::node_interner::FuncId;
 use serde::{Deserialize, Serialize};
-use std::path::{Path, PathBuf};
+use std::path::Path;
 
 mod contract;
 mod program;
@@ -22,12 +22,15 @@ mod program;
 pub use contract::{CompiledContract, ContractFunction, ContractFunctionType};
 pub use program::CompiledProgram;
 
-#[derive(Args, Clone, Debug, Serialize, Deserialize)]
+#[derive(Args, Clone, Debug, Default, Serialize, Deserialize)]
 pub struct CompileOptions {
     /// Emit debug information for the intermediate SSA IR
     #[arg(short, long)]
     pub show_ssa: bool,
 
+    #[arg(long)]
+    pub show_brillig: bool,
+
     /// Display the ACIR for compiled circuit
     #[arg(long)]
     pub print_acir: bool,
@@ -35,26 +38,6 @@ pub struct CompileOptions {
     /// Treat all warnings as errors
     #[arg(short, long)]
     pub deny_warnings: bool,
-
-    /// Display output of `println` statements
-    #[arg(long)]
-    pub show_output: bool,
-
-    /// Compile and optimize using the new experimental SSA pass
-    #[arg(long)]
-    pub experimental_ssa: bool,
-}
-
-impl Default for CompileOptions {
-    fn default() -> Self {
-        Self {
-            show_ssa: false,
-            print_acir: false,
-            deny_warnings: false,
-            show_output: true,
-            experimental_ssa: false,
-        }
-    }
 }
 
 /// Helper type used to signify where only warnings are expected in file diagnostics
@@ -67,10 +50,10 @@ pub type ErrorsAndWarnings = Vec<FileDiagnostic>;
 // with the restricted version which only uses one file
 pub fn compile_file(
     context: &mut Context,
-    root_file: PathBuf,
+    root_file: &Path,
 ) -> Result<(CompiledProgram, Warnings), ErrorsAndWarnings> {
-    create_local_crate(context, root_file, CrateType::Binary);
-    compile_main(context, &CompileOptions::default())
+    let crate_id = create_local_crate(context, root_file, CrateType::Binary);
+    compile_main(context, crate_id, &CompileOptions::default())
 }
 
 /// Adds the File with the local crate root to the file system
@@ -79,33 +62,24 @@ pub fn compile_file(
 /// we have multiple binaries in one workspace
 /// A Fix would be for the driver instance to store the local crate id.
 // Granted that this is the only place which relies on the local crate being first
-pub fn create_local_crate<P: AsRef<Path>>(
+pub fn create_local_crate(
     context: &mut Context,
-    root_file: P,
+    file_name: &Path,
     crate_type: CrateType,
 ) -> CrateId {
-    let dir_path = root_file.as_ref().to_path_buf();
-    let root_file_id = context.file_manager.add_file(&dir_path).unwrap();
+    let root_file_id = context.file_manager.add_file(file_name).unwrap();
 
-    let crate_id = context.crate_graph.add_crate_root(crate_type, root_file_id);
-
-    assert!(crate_id == LOCAL_CRATE);
-
-    LOCAL_CRATE
+    context.crate_graph.add_crate_root(crate_type, root_file_id)
 }
 
 /// Creates a Non Local Crate. A Non Local Crate is any crate which is the not the crate that
 /// the compiler is compiling.
-pub fn create_non_local_crate<P: AsRef<Path>>(
+pub fn create_non_local_crate(
     context: &mut Context,
-    root_file: P,
+    file_name: &Path,
     crate_type: CrateType,
 ) -> CrateId {
-    let dir_path = root_file.as_ref().to_path_buf();
-    let root_file_id = context.file_manager.add_file(&dir_path).unwrap();
-
-    // The first crate is always the local crate
-    assert!(context.crate_graph.number_of_crates() != 0);
+    let root_file_id = context.file_manager.add_file(file_name).unwrap();
 
     // You can add any crate type to the crate graph
     // but you cannot depend on Binaries
@@ -114,8 +88,8 @@ pub fn create_non_local_crate<P: AsRef<Path>>(
 
 /// Adds a edge in the crate graph for two crates
 pub fn add_dep(context: &mut Context, this_crate: CrateId, depends_on: CrateId, crate_name: &str) {
-    let crate_name = CrateName::new(crate_name)
-        .expect("crate name contains blacklisted characters, please remove");
+    let crate_name =
+        crate_name.parse().expect("crate name contains blacklisted characters, please remove");
 
     // Cannot depend on a binary
     if context.crate_graph.crate_type(depends_on) == CrateType::Binary {
@@ -151,29 +125,31 @@ pub fn propagate_dep(
 /// On error, this returns a non-empty vector of warnings and error messages, with at least one error.
 pub fn check_crate(
     context: &mut Context,
+    crate_id: CrateId,
     deny_warnings: bool,
-    enable_slices: bool,
 ) -> Result<Warnings, ErrorsAndWarnings> {
     // Add the stdlib before we check the crate
     // TODO: This should actually be done when constructing the driver and then propagated to each dependency when added;
     // however, the `create_non_local_crate` panics if you add the stdlib as the first crate in the graph and other
     // parts of the code expect the `0` FileID to be the crate root. See also #1681
     let std_crate_name = "std";
-    let path_to_std_lib_file = PathBuf::from(std_crate_name).join("lib.nr");
-    let std_crate = create_non_local_crate(context, path_to_std_lib_file, CrateType::Library);
-    propagate_dep(context, std_crate, &CrateName::new(std_crate_name).unwrap());
+    let path_to_std_lib_file = Path::new(std_crate_name).join("lib.nr");
+    let root_file_id = context.file_manager.add_file(&path_to_std_lib_file).unwrap();
 
-    context.def_interner.enable_slices = enable_slices;
+    // You can add any crate type to the crate graph
+    // but you cannot depend on Binaries
+    let std_crate = context.crate_graph.add_stdlib(CrateType::Library, root_file_id);
+    propagate_dep(context, std_crate, &std_crate_name.parse().unwrap());
 
     let mut errors = vec![];
-    match context.crate_graph.crate_type(LOCAL_CRATE) {
+    match context.crate_graph.crate_type(crate_id) {
         CrateType::Workspace => {
             let keys: Vec<_> = context.crate_graph.iter_keys().collect(); // avoid borrow checker
             for crate_id in keys {
                 CrateDefMap::collect_defs(crate_id, context, &mut errors);
             }
         }
-        _ => CrateDefMap::collect_defs(LOCAL_CRATE, context, &mut errors),
+        _ => CrateDefMap::collect_defs(crate_id, context, &mut errors),
     }
 
     if has_errors(&errors, deny_warnings) {
@@ -183,8 +159,11 @@ pub fn check_crate(
     }
 }
 
-pub fn compute_function_signature(context: &Context) -> Option<FunctionSignature> {
-    let main_function = context.get_main_function(&LOCAL_CRATE)?;
+pub fn compute_function_signature(
+    context: &Context,
+    crate_id: &CrateId,
+) -> Option<FunctionSignature> {
+    let main_function = context.get_main_function(crate_id)?;
 
     let func_meta = context.def_interner.function_meta(&main_function);
 
@@ -197,11 +176,12 @@ pub fn compute_function_signature(context: &Context) -> Option<FunctionSignature
 /// On error this returns the non-empty list of warnings and errors.
 pub fn compile_main(
     context: &mut Context,
+    crate_id: CrateId,
     options: &CompileOptions,
 ) -> Result<(CompiledProgram, Warnings), ErrorsAndWarnings> {
-    let warnings = check_crate(context, options.deny_warnings, options.experimental_ssa)?;
+    let warnings = check_crate(context, crate_id, options.deny_warnings)?;
 
-    let main = match context.get_main_function(&LOCAL_CRATE) {
+    let main = match context.get_main_function(&crate_id) {
         Some(m) => m,
         None => {
             let err = FileDiagnostic {
@@ -212,10 +192,10 @@ pub fn compile_main(
         }
     };
 
-    let compiled_program = compile_no_check(context, options, main)?;
+    let compiled_program = compile_no_check(context, true, options, main)?;
 
     if options.print_acir {
-        println!("Compiled ACIR for main:");
+        println!("Compiled ACIR for main (unoptimized):");
         println!("{}", compiled_program.circuit);
     }
 
@@ -225,11 +205,12 @@ pub fn compile_main(
 /// Run the frontend to check the crate for errors then compile all contracts if there were none
 pub fn compile_contracts(
     context: &mut Context,
+    crate_id: CrateId,
     options: &CompileOptions,
 ) -> Result<(Vec<CompiledContract>, Warnings), ErrorsAndWarnings> {
-    let warnings = check_crate(context, options.deny_warnings, options.experimental_ssa)?;
+    let warnings = check_crate(context, crate_id, options.deny_warnings)?;
 
-    let contracts = context.get_all_contracts(&LOCAL_CRATE);
+    let contracts = context.get_all_contracts(&crate_id);
     let mut compiled_contracts = vec![];
     let mut errors = warnings;
 
@@ -247,7 +228,7 @@ pub fn compile_contracts(
             for compiled_contract in &compiled_contracts {
                 for contract_function in &compiled_contract.functions {
                     println!(
-                        "Compiled ACIR for {}::{}:",
+                        "Compiled ACIR for {}::{} (unoptimized):",
                         compiled_contract.name, contract_function.name
                     );
                     println!("{}", contract_function.bytecode);
@@ -278,7 +259,7 @@ fn compile_contract(
     let mut errs = Vec::new();
     for function_id in &contract.functions {
         let name = context.function_name(function_id).to_owned();
-        let function = match compile_no_check(context, options, *function_id) {
+        let function = match compile_no_check(context, true, options, *function_id) {
             Ok(function) => function,
             Err(err) => {
                 errs.push(err);
@@ -315,16 +296,14 @@ fn compile_contract(
 #[allow(deprecated)]
 pub fn compile_no_check(
     context: &Context,
+    show_output: bool,
     options: &CompileOptions,
     main_function: FuncId,
 ) -> Result<CompiledProgram, FileDiagnostic> {
     let program = monomorphize(main_function, &context.def_interner);
 
-    let (circuit, debug, abi) = if options.experimental_ssa {
-        experimental_create_circuit(program, options.show_ssa, options.show_output)?
-    } else {
-        create_circuit(program, options.show_ssa, options.show_output)?
-    };
+    let (circuit, debug, abi) =
+        create_circuit(program, options.show_ssa, options.show_brillig, show_output)?;
 
     Ok(CompiledProgram { circuit, debug, abi })
 }
diff --git a/crates/noirc_driver/src/main.rs b/crates/noirc_driver/src/main.rs
deleted file mode 100644
index 77b6e8a664d..00000000000
--- a/crates/noirc_driver/src/main.rs
+++ /dev/null
@@ -1,27 +0,0 @@
-use noirc_driver::{
-    add_dep, compile_main, create_local_crate, create_non_local_crate, CompileOptions,
-};
-use noirc_frontend::{
-    graph::{CrateType, LOCAL_CRATE},
-    hir::Context,
-};
-fn main() {
-    const EXTERNAL_DIR: &str = "dep_b/lib.nr";
-    const EXTERNAL_DIR2: &str = "dep_a/lib.nr";
-    const ROOT_DIR_MAIN: &str = "example_real_project/main.nr";
-
-    let mut context = Context::default();
-
-    // Add local crate to dep graph
-    create_local_crate(&mut context, ROOT_DIR_MAIN, CrateType::Binary);
-
-    // Add libraries into Driver
-    let crate_id1 = create_non_local_crate(&mut context, EXTERNAL_DIR2, CrateType::Library);
-    let crate_id2 = create_non_local_crate(&mut context, EXTERNAL_DIR, CrateType::Library);
-
-    // Add dependencies as package
-    add_dep(&mut context, LOCAL_CRATE, crate_id1, "coo4");
-    add_dep(&mut context, LOCAL_CRATE, crate_id2, "coo3");
-
-    compile_main(&mut context, &CompileOptions::default()).ok();
-}
diff --git a/crates/noirc_evaluator/Cargo.toml b/crates/noirc_evaluator/Cargo.toml
index b2a01b142d0..b838f936ee6 100644
--- a/crates/noirc_evaluator/Cargo.toml
+++ b/crates/noirc_evaluator/Cargo.toml
@@ -11,12 +11,7 @@ noirc_frontend.workspace = true
 noirc_errors.workspace = true
 noirc_abi.workspace = true
 acvm.workspace = true
-arena.workspace = true
 iter-extended.workspace = true
 thiserror.workspace = true
 num-bigint = "0.4"
-num-traits = "0.2.8"
 im = "15.1"
-
-[dev-dependencies]
-rand="0.8.5"
diff --git a/crates/noirc_evaluator/src/brillig/brillig_gen.rs b/crates/noirc_evaluator/src/brillig/brillig_gen.rs
index 32c98cb86ff..3ba04ed1afb 100644
--- a/crates/noirc_evaluator/src/brillig/brillig_gen.rs
+++ b/crates/noirc_evaluator/src/brillig/brillig_gen.rs
@@ -2,6 +2,7 @@ pub(crate) mod brillig_black_box;
 pub(crate) mod brillig_block;
 pub(crate) mod brillig_directive;
 pub(crate) mod brillig_fn;
+pub(crate) mod brillig_slice_ops;
 
 use crate::ssa_refactor::ir::{function::Function, post_order::PostOrder};
 
@@ -12,18 +13,15 @@ use self::{brillig_block::BrilligBlock, brillig_fn::FunctionContext};
 use super::brillig_ir::{artifact::BrilligArtifact, BrilligContext};
 
 /// Converting an SSA function into Brillig bytecode.
-pub(crate) fn convert_ssa_function(func: &Function) -> BrilligArtifact {
+pub(crate) fn convert_ssa_function(func: &Function, enable_debug_trace: bool) -> BrilligArtifact {
     let mut reverse_post_order = Vec::new();
     reverse_post_order.extend_from_slice(PostOrder::with_function(func).as_slice());
     reverse_post_order.reverse();
 
     let mut function_context =
-        FunctionContext { function_id: func.id(), ssa_value_to_register: HashMap::new() };
+        FunctionContext { function_id: func.id(), ssa_value_to_brillig_variable: HashMap::new() };
 
-    let mut brillig_context = BrilligContext::new(
-        FunctionContext::parameters(func),
-        FunctionContext::return_values(func),
-    );
+    let mut brillig_context = BrilligContext::new(enable_debug_trace);
 
     brillig_context.enter_context(FunctionContext::function_id_to_function_label(func.id()));
     for block in reverse_post_order {
diff --git a/crates/noirc_evaluator/src/brillig/brillig_gen/brillig_block.rs b/crates/noirc_evaluator/src/brillig/brillig_gen/brillig_block.rs
index a5193a0369a..c7779533a8a 100644
--- a/crates/noirc_evaluator/src/brillig/brillig_gen/brillig_block.rs
+++ b/crates/noirc_evaluator/src/brillig/brillig_gen/brillig_block.rs
@@ -1,9 +1,11 @@
+use crate::brillig::brillig_gen::brillig_slice_ops::{
+    convert_array_or_vector_to_vector, slice_push_back_operation,
+};
 use crate::brillig::brillig_ir::{
-    BrilligBinaryOp, BrilligContext, BRILLIG_MEMORY_ADDRESSING_BIT_SIZE,
+    BrilligBinaryOp, BrilligContext, BRILLIG_INTEGER_ARITHMETIC_BIT_SIZE,
 };
 use crate::ssa_refactor::ir::function::FunctionId;
-use crate::ssa_refactor::ir::instruction::Intrinsic;
-use crate::ssa_refactor::ir::types::CompositeType;
+use crate::ssa_refactor::ir::instruction::{Endian, Intrinsic};
 use crate::ssa_refactor::ir::{
     basic_block::{BasicBlock, BasicBlockId},
     dfg::DataFlowGraph,
@@ -18,6 +20,10 @@ use iter_extended::vecmap;
 
 use super::brillig_black_box::convert_black_box_call;
 use super::brillig_fn::FunctionContext;
+use super::brillig_slice_ops::{
+    slice_insert_operation, slice_pop_back_operation, slice_pop_front_operation,
+    slice_push_front_operation, slice_remove_operation,
+};
 
 /// Generate the compilation artifacts for compiling a function into brillig bytecode.
 pub(crate) struct BrilligBlock<'block> {
@@ -100,7 +106,7 @@ impl<'block> BrilligBlock<'block> {
     ) {
         match terminator_instruction {
             TerminatorInstruction::JmpIf { condition, then_destination, else_destination } => {
-                let condition = self.convert_ssa_value(*condition, dfg);
+                let condition = self.convert_ssa_register_value(*condition, dfg);
                 self.brillig_context.jump_if_instruction(
                     condition,
                     self.create_block_label_for_current_function(*then_destination),
@@ -112,9 +118,14 @@ impl<'block> BrilligBlock<'block> {
             TerminatorInstruction::Jmp { destination, arguments } => {
                 let target = &dfg[*destination];
                 for (src, dest) in arguments.iter().zip(target.parameters()) {
-                    let destination = self.convert_ssa_value(*dest, dfg);
+                    // Destination variable might have already been created by another block that jumps to this target
+                    let destination = self.function_context.get_or_create_variable(
+                        self.brillig_context,
+                        *dest,
+                        dfg,
+                    );
                     let source = self.convert_ssa_value(*src, dfg);
-                    self.brillig_context.mov_instruction(destination, source);
+                    self.pass_variable(source, destination);
                 }
                 self.brillig_context
                     .jump_instruction(self.create_block_label_for_current_function(*destination));
@@ -122,13 +133,50 @@ impl<'block> BrilligBlock<'block> {
             TerminatorInstruction::Return { return_values } => {
                 let return_registers: Vec<_> = return_values
                     .iter()
-                    .map(|value_id| self.convert_ssa_value(*value_id, dfg))
+                    .flat_map(|value_id| {
+                        let return_variable = self.convert_ssa_value(*value_id, dfg);
+                        self.function_context.extract_registers(return_variable)
+                    })
                     .collect();
                 self.brillig_context.return_instruction(&return_registers);
             }
         }
     }
 
+    /// Passes an arbitrary variable from the registers of the source to the registers of the destination
+    fn pass_variable(&mut self, source: RegisterOrMemory, destination: RegisterOrMemory) {
+        match (source, destination) {
+            (
+                RegisterOrMemory::RegisterIndex(source_register),
+                RegisterOrMemory::RegisterIndex(destination_register),
+            ) => {
+                self.brillig_context.mov_instruction(destination_register, source_register);
+            }
+            (
+                RegisterOrMemory::HeapArray(HeapArray { pointer: source_pointer, .. }),
+                RegisterOrMemory::HeapArray(HeapArray { pointer: destination_pointer, .. }),
+            ) => {
+                self.brillig_context.mov_instruction(destination_pointer, source_pointer);
+            }
+            (
+                RegisterOrMemory::HeapVector(HeapVector {
+                    pointer: source_pointer,
+                    size: source_size,
+                }),
+                RegisterOrMemory::HeapVector(HeapVector {
+                    pointer: destination_pointer,
+                    size: destination_size,
+                }),
+            ) => {
+                self.brillig_context.mov_instruction(destination_pointer, source_pointer);
+                self.brillig_context.mov_instruction(destination_size, source_size);
+            }
+            (_, _) => {
+                unreachable!("ICE: Cannot pass value from {:?} to {:?}", source, destination);
+            }
+        }
+    }
+
     /// Converts SSA Block parameters into Brillig Registers.
     fn convert_block_params(&mut self, block: &BasicBlock, dfg: &DataFlowGraph) {
         for param_id in block.parameters() {
@@ -141,8 +189,14 @@ impl<'block> BrilligBlock<'block> {
                 // Simple parameters and arrays are passed as already filled registers
                 // In the case of arrays, the values should already be in memory and the register should
                 // Be a valid pointer to the array.
-                Type::Numeric(_) | Type::Array(..) | Type::Reference => {
-                    self.function_context.get_or_create_register(self.brillig_context, *param_id);
+                // For slices, two registers are passed, the pointer to the data and a register holding the size of the slice.
+                Type::Numeric(_) | Type::Array(..) | Type::Slice(..) | Type::Reference => {
+                    // This parameter variable might have already been created by another block that jumps to this one.
+                    self.function_context.get_or_create_variable(
+                        self.brillig_context,
+                        *param_id,
+                        dfg,
+                    );
                 }
                 _ => {
                     todo!("ICE: Param type not supported")
@@ -157,53 +211,59 @@ impl<'block> BrilligBlock<'block> {
 
         match instruction {
             Instruction::Binary(binary) => {
-                let result_ids = dfg.instruction_results(instruction_id);
-                let result_register = self
-                    .function_context
-                    .get_or_create_register(self.brillig_context, result_ids[0]);
+                let result_register = self.function_context.create_register_variable(
+                    self.brillig_context,
+                    dfg.instruction_results(instruction_id)[0],
+                    dfg,
+                );
                 self.convert_ssa_binary(binary, dfg, result_register);
             }
             Instruction::Constrain(value) => {
-                let condition = self.convert_ssa_value(*value, dfg);
+                let condition = self.convert_ssa_register_value(*value, dfg);
                 self.brillig_context.constrain_instruction(condition);
             }
             Instruction::Allocate => {
-                let value = dfg.instruction_results(instruction_id)[0];
-                let address_register =
-                    self.function_context.get_or_create_register(self.brillig_context, value);
-                self.brillig_context.allocate_instruction(address_register);
+                let result_value = dfg.instruction_results(instruction_id)[0];
+                let address_register = self.function_context.create_register_variable(
+                    self.brillig_context,
+                    result_value,
+                    dfg,
+                );
+                self.brillig_context.allocate_variable_instruction(address_register);
             }
             Instruction::Store { address, value } => {
-                let address_register = self.convert_ssa_value(*address, dfg);
-                let source_register = self.convert_ssa_value(*value, dfg);
+                let address_register = self.convert_ssa_register_value(*address, dfg);
+                let source_variable = self.convert_ssa_value(*value, dfg);
 
-                self.brillig_context.store_instruction(address_register, source_register);
+                self.brillig_context.store_variable_instruction(address_register, source_variable);
             }
             Instruction::Load { address } => {
-                let target_register = self.function_context.get_or_create_register(
+                let target_variable = self.function_context.create_variable(
                     self.brillig_context,
                     dfg.instruction_results(instruction_id)[0],
+                    dfg,
                 );
-                let address_register = self.convert_ssa_value(*address, dfg);
 
-                self.brillig_context.load_instruction(target_register, address_register);
+                let address_register = self.convert_ssa_register_value(*address, dfg);
+
+                self.brillig_context.load_variable_instruction(target_variable, address_register);
             }
             Instruction::Not(value) => {
-                let condition = self.convert_ssa_value(*value, dfg);
-                let result_ids = dfg.instruction_results(instruction_id);
-                let result_register = self
-                    .function_context
-                    .get_or_create_register(self.brillig_context, result_ids[0]);
+                let condition_register = self.convert_ssa_register_value(*value, dfg);
+                let result_register = self.function_context.create_register_variable(
+                    self.brillig_context,
+                    dfg.instruction_results(instruction_id)[0],
+                    dfg,
+                );
                 let bit_size = Self::get_bit_size_from_ssa_type(dfg.type_of_value(*value));
-                self.brillig_context.not_instruction(condition, bit_size, result_register);
+                self.brillig_context.not_instruction(condition_register, bit_size, result_register);
             }
             Instruction::Call { func, arguments } => match &dfg[*func] {
                 Value::ForeignFunction(func_name) => {
                     let result_ids = dfg.instruction_results(instruction_id);
 
-                    let input_registers = vecmap(arguments, |value_id| {
-                        self.convert_ssa_value_to_register_value_or_array(*value_id, dfg)
-                    });
+                    let input_registers =
+                        vecmap(arguments, |value_id| self.convert_ssa_value(*value_id, dfg));
                     let output_registers = vecmap(result_ids, |value_id| {
                         self.allocate_external_call_result(*value_id, dfg)
                     });
@@ -227,36 +287,11 @@ impl<'block> BrilligBlock<'block> {
                     }
                 }
                 Value::Function(func_id) => {
-                    let function_arguments: Vec<RegisterIndex> =
-                        vecmap(arguments, |arg| self.convert_ssa_value(*arg, dfg));
-                    let result_ids = dfg.instruction_results(instruction_id);
-
-                    // Create label for the function that will be called
-                    let label_of_function_to_call =
-                        FunctionContext::function_id_to_function_label(*func_id);
-
-                    let saved_registers =
-                        self.brillig_context.pre_call_save_registers_prep_args(&function_arguments);
-
-                    // Call instruction, which will interpret above registers 0..num args
-                    self.brillig_context.add_external_call_instruction(label_of_function_to_call);
-
-                    // Important: resolve after pre_call_save_registers_prep_args
-                    // This ensures we don't save the results to registers unnecessarily.
-                    let result_registers = vecmap(result_ids, |a| {
-                        self.function_context.get_or_create_register(self.brillig_context, *a)
-                    });
-                    assert!(
-                        !saved_registers.iter().any(|x| result_registers.contains(x)),
-                        "should not save registers used as function results"
-                    );
-                    self.brillig_context
-                        .post_call_prep_returns_load_registers(&result_registers, &saved_registers);
+                    self.convert_ssa_function_call(*func_id, arguments, dfg, instruction_id);
                 }
                 Value::Intrinsic(Intrinsic::BlackBox(bb_func)) => {
-                    let function_arguments = vecmap(arguments, |arg| {
-                        self.convert_ssa_value_to_register_value_or_array(*arg, dfg)
-                    });
+                    let function_arguments =
+                        vecmap(arguments, |arg| self.convert_ssa_value(*arg, dfg));
                     let function_results = dfg.instruction_results(instruction_id);
                     let function_results = vecmap(function_results, |result| {
                         self.allocate_external_call_result(*result, dfg)
@@ -268,104 +303,394 @@ impl<'block> BrilligBlock<'block> {
                         &function_results,
                     );
                 }
+                Value::Intrinsic(Intrinsic::ArrayLen) => {
+                    let result_register = self.function_context.create_register_variable(
+                        self.brillig_context,
+                        dfg.instruction_results(instruction_id)[0],
+                        dfg,
+                    );
+                    let param = self.convert_ssa_value(arguments[0], dfg);
+                    self.brillig_context.length_of_variable_instruction(param, result_register);
+                }
+                Value::Intrinsic(
+                    Intrinsic::SlicePushBack
+                    | Intrinsic::SlicePopBack
+                    | Intrinsic::SlicePushFront
+                    | Intrinsic::SlicePopFront
+                    | Intrinsic::SliceInsert
+                    | Intrinsic::SliceRemove,
+                ) => {
+                    self.convert_ssa_slice_intrinsic_call(
+                        dfg,
+                        &dfg[*func],
+                        instruction_id,
+                        arguments,
+                    );
+                }
+                Value::Intrinsic(Intrinsic::ToRadix(endianness)) => {
+                    let source = self.convert_ssa_register_value(arguments[0], dfg);
+                    let radix = self.convert_ssa_register_value(arguments[1], dfg);
+                    let limb_count = self.convert_ssa_register_value(arguments[2], dfg);
+                    let target_slice = self.function_context.create_variable(
+                        self.brillig_context,
+                        dfg.instruction_results(instruction_id)[0],
+                        dfg,
+                    );
+
+                    self.brillig_context.radix_instruction(
+                        source,
+                        self.function_context.extract_heap_vector(target_slice),
+                        radix,
+                        limb_count,
+                        matches!(endianness, Endian::Big),
+                    );
+                }
+                Value::Intrinsic(Intrinsic::ToBits(endianness)) => {
+                    let source = self.convert_ssa_register_value(arguments[0], dfg);
+                    let limb_count = self.convert_ssa_register_value(arguments[1], dfg);
+                    let target_slice = self.function_context.create_variable(
+                        self.brillig_context,
+                        dfg.instruction_results(instruction_id)[0],
+                        dfg,
+                    );
+
+                    let radix = self.brillig_context.make_constant(2_usize.into());
+
+                    self.brillig_context.radix_instruction(
+                        source,
+                        self.function_context.extract_heap_vector(target_slice),
+                        radix,
+                        limb_count,
+                        matches!(endianness, Endian::Big),
+                    );
+
+                    self.brillig_context.deallocate_register(radix);
+                }
                 _ => {
                     unreachable!("unsupported function call type {:?}", dfg[*func])
                 }
             },
             Instruction::Truncate { value, .. } => {
                 let result_ids = dfg.instruction_results(instruction_id);
-                let destination = self
-                    .function_context
-                    .get_or_create_register(self.brillig_context, result_ids[0]);
-                let source = self.convert_ssa_value(*value, dfg);
-                self.brillig_context.truncate_instruction(destination, source);
+                let destination_register = self.function_context.create_register_variable(
+                    self.brillig_context,
+                    result_ids[0],
+                    dfg,
+                );
+                let source_register = self.convert_ssa_register_value(*value, dfg);
+                self.brillig_context.truncate_instruction(destination_register, source_register);
             }
             Instruction::Cast(value, target_type) => {
                 let result_ids = dfg.instruction_results(instruction_id);
-                let destination = self
-                    .function_context
-                    .get_or_create_register(self.brillig_context, result_ids[0]);
-                let source = self.convert_ssa_value(*value, dfg);
-                self.convert_cast(destination, source, target_type, &dfg.type_of_value(*value));
+                let destination_register = self.function_context.create_register_variable(
+                    self.brillig_context,
+                    result_ids[0],
+                    dfg,
+                );
+                let source_register = self.convert_ssa_register_value(*value, dfg);
+                self.convert_cast(
+                    destination_register,
+                    source_register,
+                    target_type,
+                    &dfg.type_of_value(*value),
+                );
             }
             Instruction::ArrayGet { array, index } => {
                 let result_ids = dfg.instruction_results(instruction_id);
-                let destination = self
-                    .function_context
-                    .get_or_create_register(self.brillig_context, result_ids[0]);
-                let array_register = self.convert_ssa_value(*array, dfg);
-                let index_register = self.convert_ssa_value(*index, dfg);
-                self.brillig_context.array_get(array_register, index_register, destination);
-            }
-            // Array set operation in SSA returns a new array that is a copy of the parameter array
-            // With a specific value changed.
+                let destination_variable =
+                    self.function_context.create_variable(self.brillig_context, result_ids[0], dfg);
+
+                let array_variable = self.convert_ssa_value(*array, dfg);
+                let array_pointer = match array_variable {
+                    RegisterOrMemory::HeapArray(HeapArray { pointer, .. }) => pointer,
+                    RegisterOrMemory::HeapVector(HeapVector { pointer, .. }) => pointer,
+                    _ => unreachable!("ICE: array get on non-array"),
+                };
+
+                let index_register = self.convert_ssa_register_value(*index, dfg);
+                self.convert_ssa_array_get(array_pointer, index_register, destination_variable);
+            }
             Instruction::ArraySet { array, index, value } => {
+                let source_variable = self.convert_ssa_value(*array, dfg);
+                let index_register = self.convert_ssa_register_value(*index, dfg);
+                let value_variable = self.convert_ssa_value(*value, dfg);
+
                 let result_ids = dfg.instruction_results(instruction_id);
-                let destination = self
-                    .function_context
-                    .get_or_create_register(self.brillig_context, result_ids[0]);
-
-                // First issue a array copy to the destination
-                let array_size = compute_size_of_type(&dfg.type_of_value(*array));
-                self.brillig_context.allocate_fixed_length_array(destination, array_size);
-                let source_array_register: RegisterIndex = self.convert_ssa_value(*array, dfg);
-                let size_register = self.brillig_context.make_constant(array_size.into());
-                self.brillig_context.copy_array_instruction(
-                    source_array_register,
-                    destination,
-                    size_register,
+                let destination_variable =
+                    self.function_context.create_variable(self.brillig_context, result_ids[0], dfg);
+
+                self.convert_ssa_array_set(
+                    source_variable,
+                    destination_variable,
+                    index_register,
+                    value_variable,
                 );
-
-                // Then set the value in the newly created array
-                let index_register = self.convert_ssa_value(*index, dfg);
-                let value_register = self.convert_ssa_value(*value, dfg);
-                self.brillig_context.array_set(destination, index_register, value_register);
             }
             _ => todo!("ICE: Instruction not supported {instruction:?}"),
         };
     }
 
-    /// This function allows storing a Value in memory starting at the address specified by the
-    /// address_register. The value can be a single value or an array. The function will recursively
-    /// store the value in memory.
-    fn store_in_memory(
+    fn convert_ssa_function_call(
         &mut self,
-        address_register: RegisterIndex,
-        value_id: ValueId,
+        func_id: FunctionId,
+        arguments: &[ValueId],
         dfg: &DataFlowGraph,
+        instruction_id: InstructionId,
     ) {
-        let value = &dfg[value_id];
-        match value {
-            Value::Param { .. } | Value::Instruction { .. } | Value::NumericConstant { .. } => {
-                let value_register = self.convert_ssa_value(value_id, dfg);
-                self.brillig_context.store_instruction(address_register, value_register);
+        // Convert the arguments to registers casting those to the types of the receiving function
+        let argument_registers: Vec<RegisterIndex> = arguments
+            .iter()
+            .flat_map(|argument_id| {
+                let variable_to_pass = self.convert_ssa_value(*argument_id, dfg);
+                self.function_context.extract_registers(variable_to_pass)
+            })
+            .collect();
+
+        let result_ids = dfg.instruction_results(instruction_id);
+
+        // Create label for the function that will be called
+        let label_of_function_to_call = FunctionContext::function_id_to_function_label(func_id);
+
+        let saved_registers =
+            self.brillig_context.pre_call_save_registers_prep_args(&argument_registers);
+
+        // Call instruction, which will interpret above registers 0..num args
+        self.brillig_context.add_external_call_instruction(label_of_function_to_call);
+
+        // Important: resolve after pre_call_save_registers_prep_args
+        // This ensures we don't save the results to registers unnecessarily.
+
+        // Allocate the registers for the variables where we are assigning the returns
+        let variables_assigned_to = vecmap(result_ids, |result_id| {
+            self.function_context.create_variable(self.brillig_context, *result_id, dfg)
+        });
+
+        // Collect the registers that should have been returned
+        let returned_registers: Vec<RegisterIndex> = variables_assigned_to
+            .iter()
+            .flat_map(|returned_variable| {
+                self.function_context.extract_registers(*returned_variable)
+            })
+            .collect();
+
+        assert!(
+            !saved_registers.iter().any(|x| returned_registers.contains(x)),
+            "should not save registers used as function results"
+        );
+
+        // puts the returns into the returned_registers and restores saved_registers
+        self.brillig_context
+            .post_call_prep_returns_load_registers(&returned_registers, &saved_registers);
+    }
+
+    fn convert_ssa_array_get(
+        &mut self,
+        array_pointer: RegisterIndex,
+        index_register: RegisterIndex,
+        destination_variable: RegisterOrMemory,
+    ) {
+        match destination_variable {
+            RegisterOrMemory::RegisterIndex(destination_register) => {
+                self.brillig_context.array_get(array_pointer, index_register, destination_register);
             }
-            Value::Array { array, element_type } => {
-                // Allocate a register for the iterator
-                let iterator_register = self.brillig_context.allocate_register();
-                // Set the iterator to the address of the array
-                self.brillig_context.mov_instruction(iterator_register, address_register);
+            RegisterOrMemory::HeapArray(HeapArray { pointer, .. }) => {
+                self.brillig_context.array_get(array_pointer, index_register, pointer);
+            }
+            RegisterOrMemory::HeapVector(_) => unimplemented!("ICE: Array get for vector"),
+        }
+    }
 
-                let size_of_item_register = self
-                    .brillig_context
-                    .make_constant(compute_size_of_composite_type(element_type).into());
+    /// Array set operation in SSA returns a new array or slice that is a copy of the parameter array or slice
+    /// With a specific value changed.
+    fn convert_ssa_array_set(
+        &mut self,
+        source_variable: RegisterOrMemory,
+        destination_variable: RegisterOrMemory,
+        index_register: RegisterIndex,
+        value_variable: RegisterOrMemory,
+    ) {
+        let destination_pointer = match destination_variable {
+            RegisterOrMemory::HeapArray(HeapArray { pointer, .. }) => pointer,
+            RegisterOrMemory::HeapVector(HeapVector { pointer, .. }) => pointer,
+            _ => unreachable!("ICE: array set returns non-array"),
+        };
 
-                for element_id in array.iter() {
-                    // Store the item in memory
-                    self.store_in_memory(iterator_register, *element_id, dfg);
-                    // Increment the iterator by the size of the items
-                    self.brillig_context.binary_instruction(
-                        iterator_register,
-                        size_of_item_register,
-                        iterator_register,
-                        BrilligBinaryOp::Integer {
-                            op: BinaryIntOp::Add,
-                            bit_size: BRILLIG_MEMORY_ADDRESSING_BIT_SIZE,
-                        },
-                    );
-                }
+        // First issue a array copy to the destination
+        let (source_pointer, source_size_as_register) = match source_variable {
+            RegisterOrMemory::HeapArray(HeapArray { size, pointer }) => {
+                let source_size_register = self.brillig_context.allocate_register();
+                self.brillig_context.const_instruction(source_size_register, size.into());
+                (pointer, source_size_register)
+            }
+            RegisterOrMemory::HeapVector(HeapVector { size, pointer }) => {
+                let source_size_register = self.brillig_context.allocate_register();
+                self.brillig_context.mov_instruction(source_size_register, size);
+                (pointer, source_size_register)
+            }
+            _ => unreachable!("ICE: array set on non-array"),
+        };
+
+        self.brillig_context
+            .allocate_array_instruction(destination_pointer, source_size_as_register);
+
+        self.brillig_context.copy_array_instruction(
+            source_pointer,
+            destination_pointer,
+            source_size_as_register,
+        );
+
+        if let RegisterOrMemory::HeapVector(HeapVector { size: target_size, .. }) =
+            destination_variable
+        {
+            self.brillig_context.mov_instruction(target_size, source_size_as_register);
+        }
+
+        // Then set the value in the newly created array
+        self.store_variable_in_array(destination_pointer, index_register, value_variable);
+
+        self.brillig_context.deallocate_register(source_size_as_register);
+    }
+
+    fn store_variable_in_array(
+        &mut self,
+        destination_pointer: RegisterIndex,
+        index_register: RegisterIndex,
+        value_variable: RegisterOrMemory,
+    ) {
+        match value_variable {
+            RegisterOrMemory::RegisterIndex(value_register) => {
+                self.brillig_context.array_set(destination_pointer, index_register, value_register);
+            }
+            RegisterOrMemory::HeapArray(HeapArray { pointer, .. }) => {
+                self.brillig_context.array_set(destination_pointer, index_register, pointer);
+            }
+            RegisterOrMemory::HeapVector(_) => {
+                unimplemented!("ICE: cannot store a vector in array")
             }
-            _ => unimplemented!("ICE: Value {:?} not storeable in memory", value),
+        }
+    }
+
+    /// Convert the SSA slice operations to brillig slice operations
+    fn convert_ssa_slice_intrinsic_call(
+        &mut self,
+        dfg: &DataFlowGraph,
+        intrinsic: &Value,
+        instruction_id: InstructionId,
+        arguments: &[ValueId],
+    ) {
+        let source_variable = self.convert_ssa_value(arguments[0], dfg);
+        let source_vector =
+            convert_array_or_vector_to_vector(self.brillig_context, source_variable);
+
+        match intrinsic {
+            Value::Intrinsic(Intrinsic::SlicePushBack) => {
+                let target_variable = self.function_context.create_variable(
+                    self.brillig_context,
+                    dfg.instruction_results(instruction_id)[0],
+                    dfg,
+                );
+                let target_vector = self.function_context.extract_heap_vector(target_variable);
+                let item_value = self.convert_ssa_register_value(arguments[1], dfg);
+                slice_push_back_operation(
+                    self.brillig_context,
+                    target_vector,
+                    source_vector,
+                    item_value,
+                );
+            }
+            Value::Intrinsic(Intrinsic::SlicePushFront) => {
+                let target_variable = self.function_context.create_variable(
+                    self.brillig_context,
+                    dfg.instruction_results(instruction_id)[0],
+                    dfg,
+                );
+                let target_vector = self.function_context.extract_heap_vector(target_variable);
+                let item_value = self.convert_ssa_register_value(arguments[1], dfg);
+                slice_push_front_operation(
+                    self.brillig_context,
+                    target_vector,
+                    source_vector,
+                    item_value,
+                );
+            }
+            Value::Intrinsic(Intrinsic::SlicePopBack) => {
+                let results = dfg.instruction_results(instruction_id);
+
+                let target_variable =
+                    self.function_context.create_variable(self.brillig_context, results[0], dfg);
+                let target_vector = self.function_context.extract_heap_vector(target_variable);
+
+                let pop_item = self.function_context.create_register_variable(
+                    self.brillig_context,
+                    results[1],
+                    dfg,
+                );
+
+                slice_pop_back_operation(
+                    self.brillig_context,
+                    target_vector,
+                    source_vector,
+                    pop_item,
+                );
+            }
+            Value::Intrinsic(Intrinsic::SlicePopFront) => {
+                let results = dfg.instruction_results(instruction_id);
+
+                let pop_item = self.function_context.create_register_variable(
+                    self.brillig_context,
+                    results[0],
+                    dfg,
+                );
+                let target_variable =
+                    self.function_context.create_variable(self.brillig_context, results[1], dfg);
+                let target_vector = self.function_context.extract_heap_vector(target_variable);
+
+                slice_pop_front_operation(
+                    self.brillig_context,
+                    target_vector,
+                    source_vector,
+                    pop_item,
+                );
+            }
+            Value::Intrinsic(Intrinsic::SliceInsert) => {
+                let results = dfg.instruction_results(instruction_id);
+                let index = self.convert_ssa_register_value(arguments[1], dfg);
+                let item = self.convert_ssa_register_value(arguments[2], dfg);
+                let target_variable =
+                    self.function_context.create_variable(self.brillig_context, results[0], dfg);
+
+                let target_vector = self.function_context.extract_heap_vector(target_variable);
+                slice_insert_operation(
+                    self.brillig_context,
+                    target_vector,
+                    source_vector,
+                    index,
+                    item,
+                );
+            }
+            Value::Intrinsic(Intrinsic::SliceRemove) => {
+                let results = dfg.instruction_results(instruction_id);
+                let index = self.convert_ssa_register_value(arguments[1], dfg);
+
+                let target_variable =
+                    self.function_context.create_variable(self.brillig_context, results[0], dfg);
+                let target_vector = self.function_context.extract_heap_vector(target_variable);
+
+                let removed_item_register = self.function_context.create_register_variable(
+                    self.brillig_context,
+                    results[1],
+                    dfg,
+                );
+
+                slice_remove_operation(
+                    self.brillig_context,
+                    target_vector,
+                    source_vector,
+                    index,
+                    removed_item_register,
+                );
+            }
+            _ => unreachable!("ICE: Slice operation not supported"),
         }
     }
 
@@ -420,65 +745,115 @@ impl<'block> BrilligBlock<'block> {
         let binary_type =
             type_of_binary_operation(dfg[binary.lhs].get_type(), dfg[binary.rhs].get_type());
 
-        let left = self.convert_ssa_value(binary.lhs, dfg);
-        let right = self.convert_ssa_value(binary.rhs, dfg);
+        let mut left = self.convert_ssa_register_value(binary.lhs, dfg);
+        let mut right = self.convert_ssa_register_value(binary.rhs, dfg);
 
         let brillig_binary_op =
-            convert_ssa_binary_op_to_brillig_binary_op(binary.operator, binary_type);
+            convert_ssa_binary_op_to_brillig_binary_op(binary.operator, &binary_type);
+
+        // Some binary operations with fields are issued by the compiler, such as loop comparisons, cast those to the bit size here
+        // TODO Remove after fixing https://github.com/noir-lang/noir/issues/1979
+        if let (
+            BrilligBinaryOp::Integer { bit_size, .. },
+            Type::Numeric(NumericType::NativeField),
+        ) = (&brillig_binary_op, &binary_type)
+        {
+            let new_lhs = self.brillig_context.allocate_register();
+            let new_rhs = self.brillig_context.allocate_register();
+
+            self.brillig_context.cast_instruction(new_lhs, left, *bit_size);
+            self.brillig_context.cast_instruction(new_rhs, right, *bit_size);
+
+            left = new_lhs;
+            right = new_rhs;
+        }
 
         self.brillig_context.binary_instruction(left, right, result_register, brillig_binary_op);
     }
 
-    /// Converts an SSA `ValueId` into a `RegisterIndex`.
-    fn convert_ssa_value(&mut self, value_id: ValueId, dfg: &DataFlowGraph) -> RegisterIndex {
+    /// Converts an SSA `ValueId` into a `RegisterOrMemory`. Initializes if necessary.
+    fn convert_ssa_value(&mut self, value_id: ValueId, dfg: &DataFlowGraph) -> RegisterOrMemory {
         let value = &dfg[value_id];
 
-        let register = match value {
+        let variable = match value {
             Value::Param { .. } | Value::Instruction { .. } => {
                 // All block parameters and instruction results should have already been
                 // converted to registers so we fetch from the cache.
-                self.function_context.get_or_create_register(self.brillig_context, value_id)
+                self.function_context.get_variable(value_id)
             }
             Value::NumericConstant { constant, .. } => {
-                let register_index =
-                    self.function_context.get_or_create_register(self.brillig_context, value_id);
+                // Constants might have been converted previously or not, so we get or create and
+                // (re)initialize the value inside.
+                let new_variable = self.function_context.get_or_create_variable(
+                    self.brillig_context,
+                    value_id,
+                    dfg,
+                );
+                let register_index = self.function_context.extract_register(new_variable);
 
                 self.brillig_context.const_instruction(register_index, (*constant).into());
-                register_index
+                new_variable
             }
-            Value::Array { .. } => {
-                let address_register = self.brillig_context.allocate_register();
-                self.brillig_context.allocate_fixed_length_array(
-                    address_register,
-                    compute_size_of_type(&dfg.type_of_value(value_id)),
+            Value::Array { array, .. } => {
+                let new_variable = self.function_context.get_or_create_variable(
+                    self.brillig_context,
+                    value_id,
+                    dfg,
                 );
-                self.store_in_memory(address_register, value_id, dfg);
-                address_register
+
+                // Initialize the variable
+                let pointer = match new_variable {
+                    RegisterOrMemory::HeapArray(heap_array) => {
+                        self.brillig_context
+                            .allocate_fixed_length_array(heap_array.pointer, array.len());
+
+                        heap_array.pointer
+                    }
+                    RegisterOrMemory::HeapVector(heap_vector) => {
+                        self.brillig_context
+                            .const_instruction(heap_vector.size, array.len().into());
+                        self.brillig_context
+                            .allocate_array_instruction(heap_vector.pointer, heap_vector.size);
+
+                        heap_vector.pointer
+                    }
+                    _ => unreachable!(
+                        "ICE: Cannot initialize array value created as {new_variable:?}"
+                    ),
+                };
+
+                // Write the items
+
+                // Allocate a register for the iterator
+                let iterator_register = self.brillig_context.make_constant(0_usize.into());
+
+                for element_id in array.iter() {
+                    let element_variable = self.convert_ssa_value(*element_id, dfg);
+                    // Store the item in memory
+                    self.store_variable_in_array(pointer, iterator_register, element_variable);
+                    // Increment the iterator
+                    self.brillig_context.usize_op_in_place(iterator_register, BinaryIntOp::Add, 1);
+                }
+
+                self.brillig_context.deallocate_register(iterator_register);
+
+                new_variable
             }
             _ => {
-                todo!("ICE: Should have been in cache {value:?}")
+                todo!("ICE: Cannot convert value {value:?}")
             }
         };
-        register
+        variable
     }
 
-    fn convert_ssa_value_to_register_value_or_array(
+    /// Converts an SSA `ValueId` into a `RegisterIndex`. Initializes if necessary.
+    fn convert_ssa_register_value(
         &mut self,
         value_id: ValueId,
         dfg: &DataFlowGraph,
-    ) -> RegisterOrMemory {
-        let register_index = self.convert_ssa_value(value_id, dfg);
-        let typ = dfg[value_id].get_type();
-        match typ {
-            Type::Numeric(_) => RegisterOrMemory::RegisterIndex(register_index),
-            Type::Array(..) => RegisterOrMemory::HeapArray(HeapArray {
-                pointer: register_index,
-                size: compute_size_of_type(&typ),
-            }),
-            _ => {
-                unreachable!("type not supported for conversion into brillig register")
-            }
-        }
+    ) -> RegisterIndex {
+        let variable = self.convert_ssa_value(value_id, dfg);
+        self.function_context.extract_register(variable)
     }
 
     fn allocate_external_call_result(
@@ -488,25 +863,27 @@ impl<'block> BrilligBlock<'block> {
     ) -> RegisterOrMemory {
         let typ = dfg[result].get_type();
         match typ {
-            Type::Numeric(_) => RegisterOrMemory::RegisterIndex(
-                self.function_context.get_or_create_register(self.brillig_context, result),
-            ),
+            Type::Numeric(_) => {
+                self.function_context.create_variable(self.brillig_context, result, dfg)
+            }
+
             Type::Array(..) => {
-                let pointer =
-                    self.function_context.get_or_create_register(self.brillig_context, result);
-                let array_size_in_memory = compute_size_of_type(&typ);
-                self.brillig_context.allocate_fixed_length_array(pointer, array_size_in_memory);
-                RegisterOrMemory::HeapArray(HeapArray { pointer, size: array_size_in_memory })
+                let variable =
+                    self.function_context.create_variable(self.brillig_context, result, dfg);
+                let array = self.function_context.extract_heap_array(variable);
+                self.brillig_context.allocate_fixed_length_array(array.pointer, array.size);
+                variable
             }
             Type::Slice(_) => {
-                let pointer =
-                    self.function_context.get_or_create_register(self.brillig_context, result);
-                let array_size_register = self.brillig_context.allocate_register();
+                let variable =
+                    self.function_context.create_variable(self.brillig_context, result, dfg);
+                let vector = self.function_context.extract_heap_vector(variable);
+
                 // Set the pointer to the current stack frame
                 // The stack pointer will then be update by the caller of this method
                 // once the external call is resolved and the array size is known
-                self.brillig_context.set_array_pointer(pointer);
-                RegisterOrMemory::HeapVector(HeapVector { pointer, size: array_size_register })
+                self.brillig_context.set_array_pointer(vector.pointer);
+                variable
             }
             _ => {
                 unreachable!("ICE: unsupported return type for black box call {typ:?}")
@@ -553,7 +930,7 @@ pub(crate) fn type_of_binary_operation(lhs_type: Type, rhs_type: Type) -> Type {
 /// - Brillig Binary Field Op, if it is a field type
 pub(crate) fn convert_ssa_binary_op_to_brillig_binary_op(
     ssa_op: BinaryOp,
-    typ: Type,
+    typ: &Type,
 ) -> BrilligBinaryOp {
     // First get the bit size and whether its a signed integer, if it is a numeric type
     // if it is not,then we return None, indicating that
@@ -568,18 +945,20 @@ pub(crate) fn convert_ssa_binary_op_to_brillig_binary_op(
       };
 
     fn binary_op_to_field_op(op: BinaryOp) -> BrilligBinaryOp {
-        let operation = match op {
-            BinaryOp::Add => BinaryFieldOp::Add,
-            BinaryOp::Sub => BinaryFieldOp::Sub,
-            BinaryOp::Mul => BinaryFieldOp::Mul,
-            BinaryOp::Div => BinaryFieldOp::Div,
-            BinaryOp::Eq => BinaryFieldOp::Equals,
+        match op {
+            BinaryOp::Add => BrilligBinaryOp::Field { op: BinaryFieldOp::Add },
+            BinaryOp::Sub => BrilligBinaryOp::Field { op: BinaryFieldOp::Sub },
+            BinaryOp::Mul => BrilligBinaryOp::Field { op: BinaryFieldOp::Mul },
+            BinaryOp::Div => BrilligBinaryOp::Field { op: BinaryFieldOp::Div },
+            BinaryOp::Eq => BrilligBinaryOp::Field { op: BinaryFieldOp::Equals },
+            BinaryOp::Lt => BrilligBinaryOp::Integer {
+                op: BinaryIntOp::LessThan,
+                bit_size: BRILLIG_INTEGER_ARITHMETIC_BIT_SIZE,
+            },
             _ => unreachable!(
                 "Field type cannot be used with {op}. This should have been caught by the frontend"
             ),
-        };
-
-        BrilligBinaryOp::Field { op: operation }
+        }
     }
 
     fn binary_op_to_int_op(op: BinaryOp, bit_size: u32, is_signed: bool) -> BrilligBinaryOp {
@@ -611,22 +990,7 @@ pub(crate) fn convert_ssa_binary_op_to_brillig_binary_op(
 
     // If bit size is available then it is a binary integer operation
     match bit_size_signedness {
-        Some((bit_size, is_signed)) => binary_op_to_int_op(ssa_op, bit_size, is_signed),
+        Some((bit_size, is_signed)) => binary_op_to_int_op(ssa_op, *bit_size, is_signed),
         None => binary_op_to_field_op(ssa_op),
     }
 }
-
-/// Computes the size of an SSA composite type
-fn compute_size_of_composite_type(typ: &CompositeType) -> usize {
-    typ.iter().map(compute_size_of_type).sum()
-}
-
-/// Finds out the size of a given SSA type
-/// This is needed to store values in memory
-pub(crate) fn compute_size_of_type(typ: &Type) -> usize {
-    match typ {
-        Type::Numeric(_) => 1,
-        Type::Array(types, item_count) => compute_size_of_composite_type(types) * item_count,
-        _ => todo!("ICE: Type not supported {typ:?}"),
-    }
-}
diff --git a/crates/noirc_evaluator/src/brillig/brillig_gen/brillig_fn.rs b/crates/noirc_evaluator/src/brillig/brillig_gen/brillig_fn.rs
index 4a5ae6f3f09..1a751d28b23 100644
--- a/crates/noirc_evaluator/src/brillig/brillig_gen/brillig_fn.rs
+++ b/crates/noirc_evaluator/src/brillig/brillig_gen/brillig_fn.rs
@@ -1,6 +1,7 @@
 use std::collections::HashMap;
 
-use acvm::acir::brillig::RegisterIndex;
+use acvm::brillig_vm::brillig::{HeapArray, HeapVector, RegisterIndex, RegisterOrMemory};
+use iter_extended::vecmap;
 
 use crate::{
     brillig::brillig_ir::{
@@ -8,44 +9,130 @@ use crate::{
         BrilligContext,
     },
     ssa_refactor::ir::{
+        dfg::DataFlowGraph,
         function::{Function, FunctionId},
-        types::Type,
+        types::{CompositeType, Type},
         value::ValueId,
     },
 };
 
-use super::brillig_block::compute_size_of_type;
-
 pub(crate) struct FunctionContext {
     pub(crate) function_id: FunctionId,
-    /// Map from SSA values to Register Indices.
-    pub(crate) ssa_value_to_register: HashMap<ValueId, RegisterIndex>,
+    /// Map from SSA values to register or memory.
+    pub(crate) ssa_value_to_brillig_variable: HashMap<ValueId, RegisterOrMemory>,
 }
 
 impl FunctionContext {
-    /// Gets a `RegisterIndex` for a `ValueId`, if one already exists
-    /// or creates a new `RegisterIndex` using the latest available
-    /// free register.
-    pub(crate) fn get_or_create_register(
+    /// For a given SSA value id, create and cache the a corresponding variable.
+    /// This will allocate the needed registers for the variable.
+    pub(crate) fn create_variable(
+        &mut self,
+        brillig_context: &mut BrilligContext,
+        value: ValueId,
+        dfg: &DataFlowGraph,
+    ) -> RegisterOrMemory {
+        let typ = dfg.type_of_value(value);
+
+        let variable = match typ {
+            Type::Numeric(_) | Type::Reference => {
+                let register = brillig_context.allocate_register();
+                RegisterOrMemory::RegisterIndex(register)
+            }
+            Type::Array(item_typ, elem_count) => {
+                let pointer_register = brillig_context.allocate_register();
+                let size = compute_array_length(&item_typ, elem_count);
+                RegisterOrMemory::HeapArray(HeapArray { pointer: pointer_register, size })
+            }
+            Type::Slice(_) => {
+                let pointer_register = brillig_context.allocate_register();
+                let size_register = brillig_context.allocate_register();
+                RegisterOrMemory::HeapVector(HeapVector {
+                    pointer: pointer_register,
+                    size: size_register,
+                })
+            }
+            Type::Function => {
+                unreachable!("ICE: Function values should have been removed from the SSA")
+            }
+        };
+
+        // Cache the `ValueId` so that if we call get_variable, it will
+        // return the registers that have just been created.
+        //
+        // WARNING: This assumes that a registers won't be reused for a different value.
+        // If you overwrite the registers, then the cache will be invalid.
+
+        if self.ssa_value_to_brillig_variable.insert(value, variable).is_some() {
+            unreachable!("ICE: ValueId {value:?} was already in cache");
+        }
+
+        variable
+    }
+
+    /// For a given SSA value id, return the corresponding cached variable.
+    pub(crate) fn get_variable(&mut self, value: ValueId) -> RegisterOrMemory {
+        *self
+            .ssa_value_to_brillig_variable
+            .get(&value)
+            .unwrap_or_else(|| panic!("ICE: Value not found in cache {value}"))
+    }
+
+    pub(crate) fn get_or_create_variable(
         &mut self,
         brillig_context: &mut BrilligContext,
         value: ValueId,
+        dfg: &DataFlowGraph,
+    ) -> RegisterOrMemory {
+        if let Some(variable) = self.ssa_value_to_brillig_variable.get(&value) {
+            return *variable;
+        }
+
+        self.create_variable(brillig_context, value, dfg)
+    }
+
+    /// Creates a variable that fits in a single register and returns the register.
+    pub(crate) fn create_register_variable(
+        &mut self,
+        brillig_context: &mut BrilligContext,
+        value: ValueId,
+        dfg: &DataFlowGraph,
     ) -> RegisterIndex {
-        if let Some(register_index) = self.ssa_value_to_register.get(&value) {
-            return *register_index;
+        let variable = self.create_variable(brillig_context, value, dfg);
+        self.extract_register(variable)
+    }
+
+    pub(crate) fn extract_register(&self, variable: RegisterOrMemory) -> RegisterIndex {
+        match variable {
+            RegisterOrMemory::RegisterIndex(register_index) => register_index,
+            _ => unreachable!("ICE: Expected register, got {variable:?}"),
         }
+    }
 
-        let register = brillig_context.allocate_register();
+    pub(crate) fn extract_heap_array(&self, variable: RegisterOrMemory) -> HeapArray {
+        match variable {
+            RegisterOrMemory::HeapArray(array) => array,
+            _ => unreachable!("ICE: Expected array, got {variable:?}"),
+        }
+    }
 
-        // Cache the `ValueId` so that if we call it again, it will
-        // return the register that has just been created.
-        //
-        // WARNING: This assumes that a register has not been
-        // modified. If a MOV instruction has overwritten the value
-        // at a register, then this cache will be invalid.
-        self.ssa_value_to_register.insert(value, register);
+    pub(crate) fn extract_heap_vector(&self, variable: RegisterOrMemory) -> HeapVector {
+        match variable {
+            RegisterOrMemory::HeapVector(vector) => vector,
+            _ => unreachable!("ICE: Expected vector, got {variable:?}"),
+        }
+    }
 
-        register
+    /// Collects the registers that a given variable is stored in.
+    pub(crate) fn extract_registers(&self, variable: RegisterOrMemory) -> Vec<RegisterIndex> {
+        match variable {
+            RegisterOrMemory::RegisterIndex(register_index) => vec![register_index],
+            RegisterOrMemory::HeapArray(array) => {
+                vec![array.pointer]
+            }
+            RegisterOrMemory::HeapVector(vector) => {
+                vec![vector.pointer, vector.size]
+            }
+        }
     }
 
     /// Creates a function label from a given SSA function id.
@@ -53,17 +140,31 @@ impl FunctionContext {
         function_id.to_string()
     }
 
+    fn ssa_type_to_parameter(typ: &Type) -> BrilligParameter {
+        match typ {
+            Type::Numeric(_) | Type::Reference => BrilligParameter::Simple,
+            Type::Array(item_type, size) => BrilligParameter::Array(
+                vecmap(item_type.iter(), |item_typ| {
+                    FunctionContext::ssa_type_to_parameter(item_typ)
+                }),
+                *size,
+            ),
+            Type::Slice(item_type) => {
+                BrilligParameter::Slice(vecmap(item_type.iter(), |item_typ| {
+                    FunctionContext::ssa_type_to_parameter(item_typ)
+                }))
+            }
+            _ => unimplemented!("Unsupported function parameter/return type {typ:?}"),
+        }
+    }
+
     /// Collects the parameters of a given function
     pub(crate) fn parameters(func: &Function) -> Vec<BrilligParameter> {
         func.parameters()
             .iter()
             .map(|&value_id| {
                 let typ = func.dfg.type_of_value(value_id);
-                match typ {
-                    Type::Numeric(_) | Type::Reference => BrilligParameter::Register,
-                    Type::Array(..) => BrilligParameter::HeapArray(compute_size_of_type(&typ)),
-                    _ => unimplemented!("Unsupported function parameter type {typ:?}"),
-                }
+                FunctionContext::ssa_type_to_parameter(&typ)
             })
             .collect()
     }
@@ -74,12 +175,13 @@ impl FunctionContext {
             .iter()
             .map(|&value_id| {
                 let typ = func.dfg.type_of_value(value_id);
-                match typ {
-                    Type::Numeric(_) | Type::Reference => BrilligParameter::Register,
-                    Type::Array(..) => BrilligParameter::HeapArray(compute_size_of_type(&typ)),
-                    _ => unimplemented!("Unsupported return value type {typ:?}"),
-                }
+                FunctionContext::ssa_type_to_parameter(&typ)
             })
             .collect()
     }
 }
+
+/// Computes the length of an array. This will match with the indexes that SSA will issue
+pub(crate) fn compute_array_length(item_typ: &CompositeType, elem_count: usize) -> usize {
+    item_typ.len() * elem_count
+}
diff --git a/crates/noirc_evaluator/src/brillig/brillig_gen/brillig_slice_ops.rs b/crates/noirc_evaluator/src/brillig/brillig_gen/brillig_slice_ops.rs
new file mode 100644
index 00000000000..99af5c2b13b
--- /dev/null
+++ b/crates/noirc_evaluator/src/brillig/brillig_gen/brillig_slice_ops.rs
@@ -0,0 +1,644 @@
+use acvm::brillig_vm::brillig::{BinaryIntOp, HeapVector, RegisterIndex, RegisterOrMemory};
+
+use crate::brillig::brillig_ir::BrilligContext;
+
+pub(crate) fn slice_push_back_operation(
+    brillig_context: &mut BrilligContext,
+    target_vector: HeapVector,
+    source_vector: HeapVector,
+    item_to_insert: RegisterIndex,
+) {
+    // First we need to allocate the target vector incrementing the size by 1
+    brillig_context.usize_op(source_vector.size, target_vector.size, BinaryIntOp::Add, 1);
+    brillig_context.allocate_array_instruction(target_vector.pointer, target_vector.size);
+
+    // Now we copy the source vector into the target vector
+    brillig_context.copy_array_instruction(
+        source_vector.pointer,
+        target_vector.pointer,
+        source_vector.size,
+    );
+
+    brillig_context.array_set(target_vector.pointer, source_vector.size, item_to_insert);
+}
+
+pub(crate) fn slice_push_front_operation(
+    brillig_context: &mut BrilligContext,
+    target_vector: HeapVector,
+    source_vector: HeapVector,
+    item_to_insert: RegisterIndex,
+) {
+    // First we need to allocate the target vector incrementing the size by 1
+    brillig_context.usize_op(source_vector.size, target_vector.size, BinaryIntOp::Add, 1);
+    brillig_context.allocate_array_instruction(target_vector.pointer, target_vector.size);
+
+    // Now we offset the target pointer by one
+    let destination_copy_pointer = brillig_context.allocate_register();
+    brillig_context.usize_op(target_vector.pointer, destination_copy_pointer, BinaryIntOp::Add, 1);
+
+    // Now we copy the source vector into the target vector starting at index 1
+    brillig_context.copy_array_instruction(
+        source_vector.pointer,
+        destination_copy_pointer,
+        source_vector.size,
+    );
+    brillig_context.deallocate_register(destination_copy_pointer);
+
+    // Then we write the item to insert at index 0
+    let zero = brillig_context.make_constant(0_u128.into());
+    brillig_context.array_set(target_vector.pointer, zero, item_to_insert);
+    brillig_context.deallocate_register(zero);
+}
+
+pub(crate) fn slice_pop_front_operation(
+    brillig_context: &mut BrilligContext,
+    target_vector: HeapVector,
+    source_vector: HeapVector,
+    removed_item: RegisterIndex,
+) {
+    // First we need to allocate the target vector decrementing the size by 1
+    brillig_context.usize_op(source_vector.size, target_vector.size, BinaryIntOp::Sub, 1);
+    brillig_context.allocate_array_instruction(target_vector.pointer, target_vector.size);
+
+    // Now we offset the source pointer by one
+    let source_copy_pointer = brillig_context.allocate_register();
+    brillig_context.usize_op(source_vector.pointer, source_copy_pointer, BinaryIntOp::Add, 1);
+
+    // Now we copy the source vector starting at index 1 into the target vector
+    brillig_context.copy_array_instruction(
+        source_copy_pointer,
+        target_vector.pointer,
+        target_vector.size,
+    );
+    brillig_context.deallocate_register(source_copy_pointer);
+
+    let zero = brillig_context.make_constant(0_u128.into());
+    brillig_context.array_get(source_vector.pointer, zero, removed_item);
+    brillig_context.deallocate_register(zero);
+}
+
+pub(crate) fn slice_pop_back_operation(
+    brillig_context: &mut BrilligContext,
+    target_vector: HeapVector,
+    source_vector: HeapVector,
+    removed_item: RegisterIndex,
+) {
+    // First we need to allocate the target vector decrementing the size by 1
+    brillig_context.usize_op(source_vector.size, target_vector.size, BinaryIntOp::Sub, 1);
+    brillig_context.allocate_array_instruction(target_vector.pointer, target_vector.size);
+
+    // Now we copy all elements but the last into the target vector
+    brillig_context.copy_array_instruction(
+        source_vector.pointer,
+        target_vector.pointer,
+        target_vector.size,
+    );
+
+    brillig_context.array_get(source_vector.pointer, target_vector.size, removed_item);
+}
+
+pub(crate) fn slice_insert_operation(
+    brillig_context: &mut BrilligContext,
+    target_vector: HeapVector,
+    source_vector: HeapVector,
+    index: RegisterIndex,
+    item: RegisterIndex,
+) {
+    // First we need to allocate the target vector incrementing the size by 1
+    brillig_context.usize_op(source_vector.size, target_vector.size, BinaryIntOp::Add, 1);
+    brillig_context.allocate_array_instruction(target_vector.pointer, target_vector.size);
+
+    // Copy the elements to the left of the index
+    brillig_context.copy_array_instruction(source_vector.pointer, target_vector.pointer, index);
+
+    // Compute the source pointer just at the index
+    let source_pointer_at_index = brillig_context.allocate_register();
+    brillig_context.memory_op(
+        source_vector.pointer,
+        index,
+        source_pointer_at_index,
+        BinaryIntOp::Add,
+    );
+
+    // Compute the target pointer after the index
+    let target_pointer_after_index = brillig_context.allocate_register();
+    brillig_context.memory_op(
+        target_vector.pointer,
+        index,
+        target_pointer_after_index,
+        BinaryIntOp::Add,
+    );
+    brillig_context.usize_op_in_place(target_pointer_after_index, BinaryIntOp::Add, 1);
+
+    // Compute the number of elements to the right of the index
+    let item_count = brillig_context.allocate_register();
+    brillig_context.memory_op(source_vector.size, index, item_count, BinaryIntOp::Sub);
+
+    // Copy the elements to the right of the index
+    brillig_context.copy_array_instruction(
+        source_pointer_at_index,
+        target_pointer_after_index,
+        item_count,
+    );
+
+    brillig_context.deallocate_register(source_pointer_at_index);
+    brillig_context.deallocate_register(target_pointer_after_index);
+    brillig_context.deallocate_register(item_count);
+
+    // Write the item to insert at the index
+    brillig_context.array_set(target_vector.pointer, index, item);
+}
+
+pub(crate) fn slice_remove_operation(
+    brillig_context: &mut BrilligContext,
+    target_vector: HeapVector,
+    source_vector: HeapVector,
+    index: RegisterIndex,
+    removed_item: RegisterIndex,
+) {
+    // First we need to allocate the target vector decrementing the size by 1
+    brillig_context.usize_op(source_vector.size, target_vector.size, BinaryIntOp::Sub, 1);
+    brillig_context.allocate_array_instruction(target_vector.pointer, target_vector.size);
+
+    // Copy the elements to the left of the index
+    brillig_context.copy_array_instruction(source_vector.pointer, target_vector.pointer, index);
+
+    // Compute the source pointer after the index
+    let source_pointer_after_index = brillig_context.allocate_register();
+    brillig_context.memory_op(
+        source_vector.pointer,
+        index,
+        source_pointer_after_index,
+        BinaryIntOp::Add,
+    );
+    brillig_context.usize_op_in_place(source_pointer_after_index, BinaryIntOp::Add, 1);
+
+    // Compute the target pointer at the index
+    let target_pointer_at_index = brillig_context.allocate_register();
+    brillig_context.memory_op(
+        target_vector.pointer,
+        index,
+        target_pointer_at_index,
+        BinaryIntOp::Add,
+    );
+
+    // Compute the number of elements to the right of the index
+    let item_count = brillig_context.allocate_register();
+    brillig_context.memory_op(source_vector.size, index, item_count, BinaryIntOp::Sub);
+    brillig_context.usize_op_in_place(item_count, BinaryIntOp::Sub, 1);
+
+    // Copy the elements to the right of the index
+    brillig_context.copy_array_instruction(
+        source_pointer_after_index,
+        target_pointer_at_index,
+        item_count,
+    );
+
+    brillig_context.deallocate_register(source_pointer_after_index);
+    brillig_context.deallocate_register(target_pointer_at_index);
+    brillig_context.deallocate_register(item_count);
+
+    // Get the item at the index
+    brillig_context.array_get(source_vector.pointer, index, removed_item);
+}
+
+pub(crate) fn convert_array_or_vector_to_vector(
+    brillig_context: &mut BrilligContext,
+    source_variable: RegisterOrMemory,
+) -> HeapVector {
+    match source_variable {
+        RegisterOrMemory::HeapVector(source_vector) => source_vector,
+        RegisterOrMemory::HeapArray(source_array) => brillig_context.array_to_vector(&source_array),
+        _ => unreachable!("ICE: unsupported slice push back source {:?}", source_variable),
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use std::vec;
+
+    use acvm::acir::brillig::{HeapVector, Value};
+    use acvm::brillig_vm::brillig::RegisterIndex;
+
+    use crate::brillig::brillig_gen::brillig_slice_ops::{
+        slice_insert_operation, slice_pop_back_operation, slice_pop_front_operation,
+        slice_push_back_operation, slice_push_front_operation, slice_remove_operation,
+    };
+    use crate::brillig::brillig_ir::artifact::BrilligParameter;
+    use crate::brillig::brillig_ir::tests::{create_and_run_vm, create_context};
+
+    #[test]
+    fn test_slice_push_operation() {
+        fn test_case_push(
+            push_back: bool,
+            array: Vec<Value>,
+            expected_mem: Vec<Value>,
+            item_to_push: Value,
+        ) {
+            let arguments = vec![
+                BrilligParameter::Array(vec![BrilligParameter::Simple], array.len()),
+                BrilligParameter::Simple,
+            ];
+            let returns = vec![
+                BrilligParameter::Array(vec![BrilligParameter::Simple], array.len() + 1),
+                BrilligParameter::Simple,
+            ];
+
+            let mut context = create_context();
+
+            // Allocate the parameters
+            let array_pointer = context.allocate_register();
+            let item_to_insert = context.allocate_register();
+
+            // Cast the source array to a vector
+            let array_size = context.make_constant(array.len().into());
+
+            // Allocate the results
+            let copied_array_pointer = context.allocate_register();
+            let copied_array_size = context.allocate_register();
+
+            if push_back {
+                slice_push_back_operation(
+                    &mut context,
+                    HeapVector { pointer: copied_array_pointer, size: copied_array_size },
+                    HeapVector { pointer: array_pointer, size: array_size },
+                    item_to_insert,
+                );
+            } else {
+                slice_push_front_operation(
+                    &mut context,
+                    HeapVector { pointer: copied_array_pointer, size: copied_array_size },
+                    HeapVector { pointer: array_pointer, size: array_size },
+                    item_to_insert,
+                );
+            }
+
+            context.return_instruction(&[copied_array_pointer, copied_array_size]);
+
+            let vm = create_and_run_vm(
+                array.clone(),
+                vec![Value::from(0_usize), item_to_push],
+                context,
+                arguments,
+                returns,
+            );
+
+            assert_eq!(vm.get_memory(), &expected_mem);
+
+            assert_eq!(vm.get_registers().get(RegisterIndex(0)), Value::from(array.len()));
+            assert_eq!(vm.get_registers().get(RegisterIndex(1)), Value::from(array.len() + 1));
+        }
+
+        test_case_push(
+            true,
+            vec![Value::from(1_usize), Value::from(2_usize), Value::from(3_usize)],
+            vec![
+                Value::from(1_usize),
+                Value::from(2_usize),
+                Value::from(3_usize),
+                Value::from(1_usize),
+                Value::from(2_usize),
+                Value::from(3_usize),
+                Value::from(27_usize),
+            ],
+            Value::from(27_usize),
+        );
+        test_case_push(true, vec![], vec![Value::from(27_usize)], Value::from(27_usize));
+        test_case_push(
+            false,
+            vec![Value::from(1_usize), Value::from(2_usize), Value::from(3_usize)],
+            vec![
+                Value::from(1_usize),
+                Value::from(2_usize),
+                Value::from(3_usize),
+                Value::from(27_usize),
+                Value::from(1_usize),
+                Value::from(2_usize),
+                Value::from(3_usize),
+            ],
+            Value::from(27_usize),
+        );
+        test_case_push(false, vec![], vec![Value::from(27_usize)], Value::from(27_usize));
+    }
+
+    #[test]
+    fn test_slice_pop_back_operation() {
+        fn test_case_pop(
+            pop_back: bool,
+            array: Vec<Value>,
+            expected_mem: Vec<Value>,
+            expected_removed_item: Value,
+        ) {
+            let arguments =
+                vec![BrilligParameter::Array(vec![BrilligParameter::Simple], array.len())];
+            let returns = vec![
+                BrilligParameter::Array(vec![BrilligParameter::Simple], array.len() - 1),
+                BrilligParameter::Simple,
+                BrilligParameter::Simple,
+            ];
+
+            let mut context = create_context();
+
+            // Allocate the parameters
+            let array_pointer = context.allocate_register();
+
+            // Cast the source array to a vector
+            let array_size = context.make_constant(array.len().into());
+
+            // Allocate the results
+            let copied_array_pointer = context.allocate_register();
+            let removed_item = context.allocate_register();
+
+            let copied_array_size = context.allocate_register();
+
+            if pop_back {
+                slice_pop_back_operation(
+                    &mut context,
+                    HeapVector { pointer: copied_array_pointer, size: copied_array_size },
+                    HeapVector { pointer: array_pointer, size: array_size },
+                    removed_item,
+                );
+            } else {
+                slice_pop_front_operation(
+                    &mut context,
+                    HeapVector { pointer: copied_array_pointer, size: copied_array_size },
+                    HeapVector { pointer: array_pointer, size: array_size },
+                    removed_item,
+                );
+            }
+
+            context.return_instruction(&[copied_array_pointer, copied_array_size, removed_item]);
+
+            let vm = create_and_run_vm(
+                array.clone(),
+                vec![Value::from(0_usize)],
+                context,
+                arguments,
+                returns,
+            );
+
+            assert_eq!(vm.get_memory(), &expected_mem);
+
+            assert_eq!(vm.get_registers().get(RegisterIndex(0)), Value::from(array.len()));
+            assert_eq!(vm.get_registers().get(RegisterIndex(1)), Value::from(array.len() - 1));
+            assert_eq!(vm.get_registers().get(RegisterIndex(2)), expected_removed_item);
+        }
+
+        test_case_pop(
+            true,
+            vec![Value::from(1_usize), Value::from(2_usize), Value::from(3_usize)],
+            vec![
+                Value::from(1_usize),
+                Value::from(2_usize),
+                Value::from(3_usize),
+                Value::from(1_usize),
+                Value::from(2_usize),
+            ],
+            Value::from(3_usize),
+        );
+        test_case_pop(
+            true,
+            vec![Value::from(1_usize)],
+            vec![Value::from(1_usize)],
+            Value::from(1_usize),
+        );
+        test_case_pop(
+            false,
+            vec![Value::from(1_usize), Value::from(2_usize), Value::from(3_usize)],
+            vec![
+                Value::from(1_usize),
+                Value::from(2_usize),
+                Value::from(3_usize),
+                Value::from(2_usize),
+                Value::from(3_usize),
+            ],
+            Value::from(1_usize),
+        );
+    }
+
+    #[test]
+    fn test_slice_insert_operation() {
+        fn test_case_insert(
+            array: Vec<Value>,
+            expected_mem: Vec<Value>,
+            item: Value,
+            index: Value,
+        ) {
+            let arguments = vec![
+                BrilligParameter::Array(vec![BrilligParameter::Simple], array.len()),
+                BrilligParameter::Simple,
+                BrilligParameter::Simple,
+            ];
+            let returns = vec![
+                BrilligParameter::Array(vec![BrilligParameter::Simple], array.len() + 1),
+                BrilligParameter::Simple,
+            ];
+
+            let mut context = create_context();
+
+            // Allocate the parameters
+            let array_pointer = context.allocate_register();
+            let item_to_insert = context.allocate_register();
+            let index_to_insert = context.allocate_register();
+
+            // Cast the source array to a vector
+            let array_size = context.make_constant(array.len().into());
+
+            // Allocate the results
+            let copied_array_pointer = context.allocate_register();
+
+            let copied_array_size = context.allocate_register();
+
+            slice_insert_operation(
+                &mut context,
+                HeapVector { pointer: copied_array_pointer, size: copied_array_size },
+                HeapVector { pointer: array_pointer, size: array_size },
+                index_to_insert,
+                item_to_insert,
+            );
+
+            context.return_instruction(&[copied_array_pointer, copied_array_size]);
+
+            let vm = create_and_run_vm(
+                array.clone(),
+                vec![Value::from(0_usize), item, index],
+                context,
+                arguments,
+                returns,
+            );
+
+            assert_eq!(vm.get_memory(), &expected_mem);
+
+            assert_eq!(vm.get_registers().get(RegisterIndex(0)), Value::from(array.len()));
+            assert_eq!(vm.get_registers().get(RegisterIndex(1)), Value::from(array.len() + 1));
+        }
+
+        test_case_insert(
+            vec![Value::from(1_usize), Value::from(2_usize), Value::from(3_usize)],
+            vec![
+                Value::from(1_usize),
+                Value::from(2_usize),
+                Value::from(3_usize),
+                Value::from(1_usize),
+                Value::from(27_usize),
+                Value::from(2_usize),
+                Value::from(3_usize),
+            ],
+            Value::from(27_usize),
+            Value::from(1_usize),
+        );
+
+        test_case_insert(
+            vec![Value::from(1_usize), Value::from(2_usize), Value::from(3_usize)],
+            vec![
+                Value::from(1_usize),
+                Value::from(2_usize),
+                Value::from(3_usize),
+                Value::from(27_usize),
+                Value::from(1_usize),
+                Value::from(2_usize),
+                Value::from(3_usize),
+            ],
+            Value::from(27_usize),
+            Value::from(0_usize),
+        );
+        test_case_insert(
+            vec![Value::from(1_usize), Value::from(2_usize), Value::from(3_usize)],
+            vec![
+                Value::from(1_usize),
+                Value::from(2_usize),
+                Value::from(3_usize),
+                Value::from(1_usize),
+                Value::from(2_usize),
+                Value::from(27_usize),
+                Value::from(3_usize),
+            ],
+            Value::from(27_usize),
+            Value::from(2_usize),
+        );
+        test_case_insert(
+            vec![Value::from(1_usize), Value::from(2_usize), Value::from(3_usize)],
+            vec![
+                Value::from(1_usize),
+                Value::from(2_usize),
+                Value::from(3_usize),
+                Value::from(1_usize),
+                Value::from(2_usize),
+                Value::from(3_usize),
+                Value::from(27_usize),
+            ],
+            Value::from(27_usize),
+            Value::from(3_usize),
+        );
+        test_case_insert(
+            vec![],
+            vec![Value::from(27_usize)],
+            Value::from(27_usize),
+            Value::from(0_usize),
+        );
+    }
+
+    #[test]
+    fn test_slice_remove_operation() {
+        fn test_case_remove(
+            array: Vec<Value>,
+            expected_mem: Vec<Value>,
+            index: Value,
+            expected_removed_item: Value,
+        ) {
+            let arguments = vec![
+                BrilligParameter::Array(vec![BrilligParameter::Simple], array.len()),
+                BrilligParameter::Simple,
+            ];
+            let returns = vec![
+                BrilligParameter::Array(vec![BrilligParameter::Simple], array.len() - 1),
+                BrilligParameter::Simple,
+                BrilligParameter::Simple,
+            ];
+
+            let mut context = create_context();
+
+            // Allocate the parameters
+            let array_pointer = context.allocate_register();
+            let index_to_insert = context.allocate_register();
+
+            // Cast the source array to a vector
+            let array_size = context.make_constant(array.len().into());
+
+            // Allocate the results
+            let copied_array_pointer = context.allocate_register();
+            let removed_item = context.allocate_register();
+
+            let copied_array_size = context.allocate_register();
+
+            slice_remove_operation(
+                &mut context,
+                HeapVector { pointer: copied_array_pointer, size: copied_array_size },
+                HeapVector { pointer: array_pointer, size: array_size },
+                index_to_insert,
+                removed_item,
+            );
+
+            context.return_instruction(&[copied_array_pointer, copied_array_size, removed_item]);
+
+            let vm = create_and_run_vm(
+                array.clone(),
+                vec![Value::from(0_usize), index],
+                context,
+                arguments,
+                returns,
+            );
+
+            assert_eq!(vm.get_memory(), &expected_mem);
+
+            assert_eq!(vm.get_registers().get(RegisterIndex(0)), Value::from(array.len()));
+            assert_eq!(vm.get_registers().get(RegisterIndex(1)), Value::from(array.len() - 1));
+            assert_eq!(vm.get_registers().get(RegisterIndex(2)), expected_removed_item);
+        }
+
+        test_case_remove(
+            vec![Value::from(1_usize), Value::from(2_usize), Value::from(3_usize)],
+            vec![
+                Value::from(1_usize),
+                Value::from(2_usize),
+                Value::from(3_usize),
+                Value::from(2_usize),
+                Value::from(3_usize),
+            ],
+            Value::from(0_usize),
+            Value::from(1_usize),
+        );
+
+        test_case_remove(
+            vec![Value::from(1_usize), Value::from(2_usize), Value::from(3_usize)],
+            vec![
+                Value::from(1_usize),
+                Value::from(2_usize),
+                Value::from(3_usize),
+                Value::from(1_usize),
+                Value::from(3_usize),
+            ],
+            Value::from(1_usize),
+            Value::from(2_usize),
+        );
+
+        test_case_remove(
+            vec![Value::from(1_usize), Value::from(2_usize), Value::from(3_usize)],
+            vec![
+                Value::from(1_usize),
+                Value::from(2_usize),
+                Value::from(3_usize),
+                Value::from(1_usize),
+                Value::from(2_usize),
+            ],
+            Value::from(2_usize),
+            Value::from(3_usize),
+        );
+        test_case_remove(
+            vec![Value::from(1_usize)],
+            vec![Value::from(1_usize)],
+            Value::from(0_usize),
+            Value::from(1_usize),
+        );
+    }
+}
diff --git a/crates/noirc_evaluator/src/brillig/brillig_ir.rs b/crates/noirc_evaluator/src/brillig/brillig_ir.rs
index 1d1a4534ec3..ac0103dd9ed 100644
--- a/crates/noirc_evaluator/src/brillig/brillig_ir.rs
+++ b/crates/noirc_evaluator/src/brillig/brillig_ir.rs
@@ -8,8 +8,10 @@ pub(crate) mod artifact;
 pub(crate) mod debug_show;
 pub(crate) mod registers;
 
+mod entry_point;
+
 use self::{
-    artifact::{BrilligArtifact, BrilligParameter, UnresolvedJumpLocation},
+    artifact::{BrilligArtifact, UnresolvedJumpLocation},
     registers::BrilligRegistersContext,
 };
 use acvm::{
@@ -19,6 +21,7 @@ use acvm::{
     },
     FieldElement,
 };
+use debug_show::DebugShow;
 
 /// Integer arithmetic in Brillig is limited to 127 bit
 /// integers.
@@ -83,19 +86,19 @@ pub(crate) struct BrilligContext {
     context_label: String,
     /// Section label, used to separate sections of code
     section_label: usize,
+    /// IR printer
+    debug_show: DebugShow,
 }
 
 impl BrilligContext {
     /// Initial context state
-    pub(crate) fn new(
-        arguments: Vec<BrilligParameter>,
-        return_parameters: Vec<BrilligParameter>,
-    ) -> BrilligContext {
+    pub(crate) fn new(enable_debug_trace: bool) -> BrilligContext {
         BrilligContext {
-            obj: BrilligArtifact::new(arguments, return_parameters),
+            obj: BrilligArtifact::default(),
             registers: BrilligRegistersContext::new(),
             context_label: String::default(),
             section_label: 0,
+            debug_show: DebugShow::new(enable_debug_trace),
         }
     }
 
@@ -128,13 +131,13 @@ impl BrilligContext {
         pointer_register: RegisterIndex,
         size_register: RegisterIndex,
     ) {
-        debug_show::allocate_array_instruction(pointer_register, size_register);
+        self.debug_show.allocate_array_instruction(pointer_register, size_register);
         self.set_array_pointer(pointer_register);
         self.update_stack_pointer(size_register);
     }
 
     pub(crate) fn set_array_pointer(&mut self, pointer_register: RegisterIndex) {
-        debug_show::mov_instruction(pointer_register, ReservedRegisters::stack_pointer());
+        self.debug_show.mov_instruction(pointer_register, ReservedRegisters::stack_pointer());
         self.push_opcode(BrilligOpcode::Mov {
             destination: pointer_register,
             source: ReservedRegisters::stack_pointer(),
@@ -142,40 +145,30 @@ impl BrilligContext {
     }
 
     pub(crate) fn update_stack_pointer(&mut self, size_register: RegisterIndex) {
-        debug_show::binary_instruction(
+        self.memory_op(
             ReservedRegisters::stack_pointer(),
             size_register,
             ReservedRegisters::stack_pointer(),
-            BrilligBinaryOp::Integer {
-                op: BinaryIntOp::Add,
-                bit_size: BRILLIG_MEMORY_ADDRESSING_BIT_SIZE,
-            },
+            BinaryIntOp::Add,
         );
-        self.push_opcode(BrilligOpcode::BinaryIntOp {
-            destination: ReservedRegisters::stack_pointer(),
-            op: BinaryIntOp::Add,
-            bit_size: BRILLIG_MEMORY_ADDRESSING_BIT_SIZE,
-            lhs: ReservedRegisters::stack_pointer(),
-            rhs: size_register,
-        });
     }
 
-    /// Allocates a single value and stores the
+    /// Allocates a variable in memory and stores the
     /// pointer to the array in `pointer_register`
-    pub(crate) fn allocate_instruction(&mut self, pointer_register: RegisterIndex) {
-        debug_show::allocate_instruction(pointer_register);
-        let size_register = self.make_constant(1_u128.into());
+    pub(crate) fn allocate_variable_instruction(&mut self, pointer_register: RegisterIndex) {
+        self.debug_show.allocate_instruction(pointer_register);
+        // A variable can be stored in up to two values, so we reserve two values for that.
+        let size_register = self.make_constant(2_u128.into());
         self.push_opcode(BrilligOpcode::Mov {
             destination: pointer_register,
             source: ReservedRegisters::stack_pointer(),
         });
-        self.push_opcode(BrilligOpcode::BinaryIntOp {
-            destination: ReservedRegisters::stack_pointer(),
-            op: BinaryIntOp::Add,
-            bit_size: BRILLIG_MEMORY_ADDRESSING_BIT_SIZE,
-            lhs: ReservedRegisters::stack_pointer(),
-            rhs: size_register,
-        });
+        self.memory_op(
+            ReservedRegisters::stack_pointer(),
+            size_register,
+            ReservedRegisters::stack_pointer(),
+            BinaryIntOp::Add,
+        );
     }
 
     /// Gets the value in the array at index `index` and stores it in `result`
@@ -185,7 +178,7 @@ impl BrilligContext {
         index: RegisterIndex,
         result: RegisterIndex,
     ) {
-        debug_show::array_get(array_ptr, index, result);
+        self.debug_show.array_get(array_ptr, index, result);
         // Computes array_ptr + index, ie array[index]
         let index_of_element_in_memory = self.allocate_register();
         self.binary_instruction(
@@ -207,7 +200,7 @@ impl BrilligContext {
         index: RegisterIndex,
         value: RegisterIndex,
     ) {
-        debug_show::array_set(array_ptr, index, value);
+        self.debug_show.array_set(array_ptr, index, value);
         // Computes array_ptr + index, ie array[index]
         let index_of_element_in_memory = self.allocate_register();
         self.binary_instruction(
@@ -226,66 +219,71 @@ impl BrilligContext {
     /// Into the array pointed by destination
     pub(crate) fn copy_array_instruction(
         &mut self,
-        source: RegisterIndex,
-        destination: RegisterIndex,
+        source_pointer: RegisterIndex,
+        destination_pointer: RegisterIndex,
         num_elements_register: RegisterIndex,
     ) {
-        debug_show::copy_array_instruction(source, destination, num_elements_register);
-        let index_register = self.make_constant(0_u128.into());
+        self.debug_show.copy_array_instruction(
+            source_pointer,
+            destination_pointer,
+            num_elements_register,
+        );
+
+        let value_register = self.allocate_register();
+
+        self.loop_instruction(num_elements_register, |ctx, iterator| {
+            ctx.array_get(source_pointer, iterator, value_register);
+            ctx.array_set(destination_pointer, iterator, value_register);
+        });
+
+        self.deallocate_register(value_register);
+    }
+
+    /// This instruction will issue a loop that will iterate iteration_count times
+    /// The body of the loop should be issued by the caller in the on_iteration closure.
+    fn loop_instruction<F>(&mut self, iteration_count: RegisterIndex, on_iteration: F)
+    where
+        F: FnOnce(&mut BrilligContext, RegisterIndex),
+    {
+        let iterator_register = self.make_constant(0_u128.into());
 
         let loop_label = self.next_section_label();
         self.enter_next_section();
 
         // Loop body
 
-        // Check if index < num_elements
-        let index_less_than_array_len = self.allocate_register();
-        self.binary_instruction(
-            index_register,
-            num_elements_register,
-            index_less_than_array_len,
-            BrilligBinaryOp::Integer {
-                op: BinaryIntOp::LessThan,
-                bit_size: BRILLIG_MEMORY_ADDRESSING_BIT_SIZE,
-            },
+        // Check if iterator < iteration_count
+        let iterator_less_than_iterations = self.allocate_register();
+        self.memory_op(
+            iterator_register,
+            iteration_count,
+            iterator_less_than_iterations,
+            BinaryIntOp::LessThan,
         );
 
         let exit_loop_label = self.next_section_label();
 
-        self.not_instruction(index_less_than_array_len, 1, index_less_than_array_len);
-        self.jump_if_instruction(index_less_than_array_len, exit_loop_label);
+        self.not_instruction(iterator_less_than_iterations, 1, iterator_less_than_iterations);
+        self.jump_if_instruction(iterator_less_than_iterations, exit_loop_label);
 
-        // Copy the element from source to destination
-        let value_register = self.allocate_register();
-        self.array_get(source, index_register, value_register);
-        self.array_set(destination, index_register, value_register);
+        // Call the on iteration function
+        on_iteration(self, iterator_register);
 
-        // Increment the index register
-        let one_register = self.make_constant(1u128.into());
-        self.binary_instruction(
-            index_register,
-            one_register,
-            index_register,
-            BrilligBinaryOp::Integer {
-                op: BinaryIntOp::Add,
-                bit_size: BRILLIG_MEMORY_ADDRESSING_BIT_SIZE,
-            },
-        );
+        // Increment the iterator register
+        self.usize_op_in_place(iterator_register, BinaryIntOp::Add, 1);
 
         self.jump_instruction(loop_label);
 
         // Exit the loop
         self.enter_next_section();
         // Deallocate our temporary registers
-        self.deallocate_register(index_less_than_array_len);
-        self.deallocate_register(value_register);
-        self.deallocate_register(one_register);
-        self.deallocate_register(index_register);
+        self.deallocate_register(iterator_less_than_iterations);
+        self.deallocate_register(iterator_register);
     }
 
     /// Adds a label to the next opcode
     pub(crate) fn enter_context<T: ToString>(&mut self, label: T) {
-        debug_show::enter_context(label.to_string());
+        self.debug_show.enter_context(label.to_string());
         self.context_label = label.to_string();
         self.section_label = 0;
         // Add a context label to the next opcode
@@ -319,7 +317,7 @@ impl BrilligContext {
 
     /// Adds a unresolved `Jump` instruction to the bytecode.
     pub(crate) fn jump_instruction<T: ToString>(&mut self, target_label: T) {
-        debug_show::jump_instruction(target_label.to_string());
+        self.debug_show.jump_instruction(target_label.to_string());
         self.add_unresolved_jump(BrilligOpcode::Jump { location: 0 }, target_label.to_string());
     }
 
@@ -329,7 +327,7 @@ impl BrilligContext {
         condition: RegisterIndex,
         target_label: T,
     ) {
-        debug_show::jump_if_instruction(condition, target_label.to_string());
+        self.debug_show.jump_if_instruction(condition, target_label.to_string());
         self.add_unresolved_jump(
             BrilligOpcode::JumpIf { condition, location: 0 },
             target_label.to_string(),
@@ -362,7 +360,7 @@ impl BrilligContext {
     /// Emits brillig bytecode to jump to a trap condition if `condition`
     /// is false.
     pub(crate) fn constrain_instruction(&mut self, condition: RegisterIndex) {
-        debug_show::constrain_instruction(condition);
+        self.debug_show.constrain_instruction(condition);
         self.add_unresolved_jump(
             BrilligOpcode::JumpIf { condition, location: 0 },
             self.next_section_label(),
@@ -381,7 +379,7 @@ impl BrilligContext {
     /// method will move all register values to the first `N` values in
     /// the VM.
     pub(crate) fn return_instruction(&mut self, return_registers: &[RegisterIndex]) {
-        debug_show::return_instruction(return_registers);
+        self.debug_show.return_instruction(return_registers);
         let mut sources = Vec::with_capacity(return_registers.len());
         let mut destinations = Vec::with_capacity(return_registers.len());
 
@@ -413,6 +411,7 @@ impl BrilligContext {
             .collect();
         for (new_source, destination) in new_sources.iter().zip(destinations.iter()) {
             self.mov_instruction(*destination, *new_source);
+            self.deallocate_register(*new_source);
         }
     }
 
@@ -420,7 +419,7 @@ impl BrilligContext {
     ///
     /// Copies the value at `source` into `destination`
     pub(crate) fn mov_instruction(&mut self, destination: RegisterIndex, source: RegisterIndex) {
-        debug_show::mov_instruction(destination, source);
+        self.debug_show.mov_instruction(destination, source);
         self.push_opcode(BrilligOpcode::Mov { destination, source });
     }
 
@@ -435,7 +434,7 @@ impl BrilligContext {
         result: RegisterIndex,
         operation: BrilligBinaryOp,
     ) {
-        debug_show::binary_instruction(lhs, rhs, result, operation.clone());
+        self.debug_show.binary_instruction(lhs, rhs, result, operation.clone());
         match operation {
             BrilligBinaryOp::Field { op } => {
                 let opcode = BrilligOpcode::BinaryFieldOp { op, destination: result, lhs, rhs };
@@ -454,7 +453,7 @@ impl BrilligContext {
 
     /// Stores the value of `constant` in the `result` register
     pub(crate) fn const_instruction(&mut self, result: RegisterIndex, constant: Value) {
-        debug_show::const_instruction(result, constant);
+        self.debug_show.const_instruction(result, constant);
         self.push_opcode(BrilligOpcode::Const { destination: result, value: constant });
     }
 
@@ -468,7 +467,7 @@ impl BrilligContext {
         bit_size: u32,
         result: RegisterIndex,
     ) {
-        debug_show::not_instruction(input, bit_size, result);
+        self.debug_show.not_instruction(input, bit_size, result);
         // Compile !x as ((-1) - x)
         let u_max = FieldElement::from(2_i128).pow(&FieldElement::from(bit_size as i128))
             - FieldElement::one();
@@ -494,7 +493,7 @@ impl BrilligContext {
         inputs: &[RegisterOrMemory],
         outputs: &[RegisterOrMemory],
     ) {
-        debug_show::foreign_call_instruction(func_name.clone(), inputs, outputs);
+        self.debug_show.foreign_call_instruction(func_name.clone(), inputs, outputs);
         let opcode = BrilligOpcode::ForeignCall {
             function: func_name,
             destinations: outputs.to_vec(),
@@ -509,20 +508,96 @@ impl BrilligContext {
         destination: RegisterIndex,
         source_pointer: RegisterIndex,
     ) {
-        debug_show::load_instruction(destination, source_pointer);
+        self.debug_show.load_instruction(destination, source_pointer);
         self.push_opcode(BrilligOpcode::Load { destination, source_pointer });
     }
 
+    /// Loads a variable stored previously
+    pub(crate) fn load_variable_instruction(
+        &mut self,
+        destination: RegisterOrMemory,
+        variable_pointer: RegisterIndex,
+    ) {
+        match destination {
+            RegisterOrMemory::RegisterIndex(register_index) => {
+                self.load_instruction(register_index, variable_pointer);
+            }
+            RegisterOrMemory::HeapArray(HeapArray { pointer, .. }) => {
+                self.load_instruction(pointer, variable_pointer);
+            }
+            RegisterOrMemory::HeapVector(HeapVector { pointer, size }) => {
+                self.load_instruction(pointer, variable_pointer);
+
+                let size_pointer = self.allocate_register();
+                self.mov_instruction(size_pointer, variable_pointer);
+                self.usize_op_in_place(size_pointer, BinaryIntOp::Add, 1_usize);
+
+                self.load_instruction(size, size_pointer);
+                self.deallocate_register(size_pointer);
+            }
+        }
+    }
+
     /// Emits a store instruction
     pub(crate) fn store_instruction(
         &mut self,
         destination_pointer: RegisterIndex,
         source: RegisterIndex,
     ) {
-        debug_show::store_instruction(destination_pointer, source);
+        self.debug_show.store_instruction(destination_pointer, source);
         self.push_opcode(BrilligOpcode::Store { destination_pointer, source });
     }
 
+    pub(crate) fn length_of_variable_instruction(
+        &mut self,
+        variable: RegisterOrMemory,
+        result: RegisterIndex,
+    ) {
+        match variable {
+            RegisterOrMemory::RegisterIndex(_) => {
+                self.const_instruction(result, 1_u128.into());
+            }
+            RegisterOrMemory::HeapArray(HeapArray { size, .. }) => {
+                self.const_instruction(result, size.into());
+            }
+            RegisterOrMemory::HeapVector(HeapVector { size, .. }) => {
+                self.mov_instruction(result, size);
+            }
+        }
+    }
+
+    /// Stores a variable by saving its registers to memory
+    pub(crate) fn store_variable_instruction(
+        &mut self,
+        variable_pointer: RegisterIndex,
+        source: RegisterOrMemory,
+    ) {
+        let size_pointer = self.allocate_register();
+        self.mov_instruction(size_pointer, variable_pointer);
+        self.usize_op_in_place(size_pointer, BinaryIntOp::Add, 1_usize);
+
+        match source {
+            RegisterOrMemory::RegisterIndex(register_index) => {
+                self.store_instruction(variable_pointer, register_index);
+                let size_constant = self.make_constant(Value::from(1_usize));
+                self.store_instruction(size_pointer, size_constant);
+                self.deallocate_register(size_constant);
+            }
+            RegisterOrMemory::HeapArray(HeapArray { pointer, size }) => {
+                self.store_instruction(variable_pointer, pointer);
+                let size_constant = self.make_constant(Value::from(size));
+                self.store_instruction(size_pointer, size_constant);
+                self.deallocate_register(size_constant);
+            }
+            RegisterOrMemory::HeapVector(HeapVector { pointer, size }) => {
+                self.store_instruction(variable_pointer, pointer);
+                self.store_instruction(size_pointer, size);
+            }
+        }
+
+        self.deallocate_register(size_pointer);
+    }
+
     /// Emits a truncate instruction.
     ///
     /// Note: Truncation is used as an optimization in the SSA IR
@@ -543,7 +618,7 @@ impl BrilligContext {
 
     /// Emits a stop instruction
     pub(crate) fn stop_instruction(&mut self) {
-        debug_show::stop_instruction();
+        self.debug_show.stop_instruction();
         self.push_opcode(BrilligOpcode::Stop);
     }
 
@@ -620,7 +695,7 @@ impl BrilligContext {
         source: RegisterIndex,
         target_bit_size: u32,
     ) {
-        debug_show::cast_instruction(destination, source, target_bit_size);
+        self.debug_show.cast_instruction(destination, source, target_bit_size);
         assert!(
             target_bit_size <= BRILLIG_INTEGER_ARITHMETIC_BIT_SIZE,
             "tried to cast to a bit size greater than allowed {target_bit_size}"
@@ -642,7 +717,7 @@ impl BrilligContext {
     /// Adds a unresolved external `Call` instruction to the bytecode.
     /// This calls into another function compiled into this brillig artifact.
     pub(crate) fn add_external_call_instruction<T: ToString>(&mut self, func_label: T) {
-        debug_show::add_external_call_instruction(func_label.to_string());
+        self.debug_show.add_external_call_instruction(func_label.to_string());
         self.obj.add_unresolved_external_call(
             BrilligOpcode::Call { location: 0 },
             func_label.to_string(),
@@ -668,7 +743,7 @@ impl BrilligContext {
         for register in used_registers.iter() {
             self.store_instruction(ReservedRegisters::stack_pointer(), *register);
             // Add one to our stack pointer
-            self.usize_op(ReservedRegisters::stack_pointer(), BinaryIntOp::Add, 1);
+            self.usize_op_in_place(ReservedRegisters::stack_pointer(), BinaryIntOp::Add, 1);
         }
 
         // Store the location of our registers in the previous stack pointer
@@ -689,27 +764,49 @@ impl BrilligContext {
 
         for register in used_registers.iter().rev() {
             // Subtract one from our stack pointer
-            self.usize_op(iterator_register, BinaryIntOp::Sub, 1);
+            self.usize_op_in_place(iterator_register, BinaryIntOp::Sub, 1);
             self.load_instruction(*register, iterator_register);
         }
     }
 
+    /// Utility method to perform a binary instruction with a constant value in place
+    pub(crate) fn usize_op_in_place(
+        &mut self,
+        destination: RegisterIndex,
+        op: BinaryIntOp,
+        constant: usize,
+    ) {
+        self.usize_op(destination, destination, op, constant);
+    }
+
     /// Utility method to perform a binary instruction with a constant value
     pub(crate) fn usize_op(
         &mut self,
+        operand: RegisterIndex,
         destination: RegisterIndex,
         op: BinaryIntOp,
         constant: usize,
     ) {
         let const_register = self.make_constant(Value::from(constant));
+        self.memory_op(operand, const_register, destination, op);
+        // Mark as no longer used for this purpose, frees for reuse
+        self.deallocate_register(const_register);
+    }
+
+    /// Utility method to perform a binary instruction with a memory address
+    pub(crate) fn memory_op(
+        &mut self,
+        lhs: RegisterIndex,
+        rhs: RegisterIndex,
+        destination: RegisterIndex,
+        op: BinaryIntOp,
+    ) {
         self.binary_instruction(
-            destination,
-            const_register,
+            lhs,
+            rhs,
             destination,
             BrilligBinaryOp::Integer { op, bit_size: BRILLIG_MEMORY_ADDRESSING_BIT_SIZE },
         );
-        // Mark as no longer used for this purpose, frees for reuse
-        self.deallocate_register(const_register);
     }
 
     // Used before a call instruction.
@@ -742,9 +839,12 @@ impl BrilligContext {
     ) {
         // Allocate our result registers and write into them
         // We assume the return values of our call are held in 0..num results register indices
-        for (i, result_register) in result_registers.iter().enumerate() {
-            self.mov_instruction(*result_register, self.register(i));
-        }
+        let (sources, destinations) = result_registers
+            .iter()
+            .enumerate()
+            .map(|(i, result_register)| (self.register(i), *result_register))
+            .unzip();
+        self.mov_registers_to_registers_instruction(sources, destinations);
 
         // Restore all the same registers we have, in exact reverse order.
         // Note that we have allocated some registers above, which we will not be handling here,
@@ -762,9 +862,95 @@ impl BrilligContext {
 
     /// Issues a blackbox operation.
     pub(crate) fn black_box_op_instruction(&mut self, op: BlackBoxOp) {
-        debug_show::black_box_op_instruction(op);
+        self.debug_show.black_box_op_instruction(op);
         self.push_opcode(BrilligOpcode::BlackBox(op));
     }
+
+    /// Issues a to_radix instruction. This instruction will write the modulus of the source register
+    /// And the radix register limb_count times to the target vector.
+    pub(crate) fn radix_instruction(
+        &mut self,
+        source: RegisterIndex,
+        target_vector: HeapVector,
+        radix: RegisterIndex,
+        limb_count: RegisterIndex,
+        big_endian: bool,
+    ) {
+        self.mov_instruction(target_vector.size, limb_count);
+        self.allocate_array_instruction(target_vector.pointer, target_vector.size);
+
+        let shifted_register = self.allocate_register();
+        self.mov_instruction(shifted_register, source);
+
+        let modulus_register: RegisterIndex = self.allocate_register();
+
+        self.loop_instruction(target_vector.size, |ctx, iterator_register| {
+            // Compute the modulus
+            ctx.modulo_instruction(
+                modulus_register,
+                shifted_register,
+                radix,
+                FieldElement::max_num_bits(),
+                false,
+            );
+            // Write it
+            ctx.array_set(target_vector.pointer, iterator_register, modulus_register);
+            // Integer div the field
+            ctx.binary_instruction(
+                shifted_register,
+                radix,
+                shifted_register,
+                BrilligBinaryOp::Integer {
+                    op: BinaryIntOp::UnsignedDiv,
+                    bit_size: FieldElement::max_num_bits(),
+                },
+            );
+        });
+
+        // Deallocate our temporary registers
+        self.deallocate_register(shifted_register);
+        self.deallocate_register(modulus_register);
+
+        if big_endian {
+            self.reverse_vector_in_place_instruction(target_vector);
+        }
+    }
+
+    /// This instruction will reverse the order of the elements in a vector.
+    pub(crate) fn reverse_vector_in_place_instruction(&mut self, vector: HeapVector) {
+        let iteration_count = self.allocate_register();
+        self.usize_op(vector.size, iteration_count, BinaryIntOp::UnsignedDiv, 2);
+
+        let start_value_register = self.allocate_register();
+        let index_at_end_of_array = self.allocate_register();
+        let end_value_register = self.allocate_register();
+
+        self.loop_instruction(iteration_count, |ctx, iterator_register| {
+            // Load both values
+            ctx.array_get(vector.pointer, iterator_register, start_value_register);
+
+            // The index at the end of array is size - 1 - iterator
+            ctx.mov_instruction(index_at_end_of_array, vector.size);
+            ctx.usize_op_in_place(index_at_end_of_array, BinaryIntOp::Sub, 1);
+            ctx.memory_op(
+                index_at_end_of_array,
+                iterator_register,
+                index_at_end_of_array,
+                BinaryIntOp::Sub,
+            );
+
+            ctx.array_get(vector.pointer, index_at_end_of_array, end_value_register);
+
+            // Write both values
+            ctx.array_set(vector.pointer, iterator_register, end_value_register);
+            ctx.array_set(vector.pointer, index_at_end_of_array, start_value_register);
+        });
+
+        self.deallocate_register(iteration_count);
+        self.deallocate_register(start_value_register);
+        self.deallocate_register(end_value_register);
+        self.deallocate_register(index_at_end_of_array);
+    }
 }
 
 /// Type to encapsulate the binary operation types in Brillig
@@ -778,7 +964,7 @@ pub(crate) enum BrilligBinaryOp {
 }
 
 #[cfg(test)]
-mod tests {
+pub(crate) mod tests {
     use std::vec;
 
     use acvm::acir::brillig::{
@@ -788,11 +974,12 @@ mod tests {
     use acvm::brillig_vm::{Registers, VMStatus, VM};
     use acvm::{BlackBoxFunctionSolver, BlackBoxResolutionError, FieldElement};
 
-    use crate::brillig::brillig_ir::{BrilligContext, BRILLIG_MEMORY_ADDRESSING_BIT_SIZE};
+    use crate::brillig::brillig_ir::BrilligContext;
 
-    use super::{BrilligBinaryOp, BrilligOpcode, ReservedRegisters};
+    use super::artifact::BrilligParameter;
+    use super::{BrilligOpcode, ReservedRegisters};
 
-    struct DummyBlackBoxSolver;
+    pub(crate) struct DummyBlackBoxSolver;
 
     impl BlackBoxFunctionSolver for DummyBlackBoxSolver {
         fn schnorr_verify(
@@ -819,6 +1006,44 @@ mod tests {
         }
     }
 
+    pub(crate) fn create_context() -> BrilligContext {
+        let mut context = BrilligContext::new(true);
+        context.enter_context("test");
+        context
+    }
+
+    pub(crate) fn create_entry_point_bytecode(
+        context: BrilligContext,
+        arguments: Vec<BrilligParameter>,
+        returns: Vec<BrilligParameter>,
+    ) -> Vec<BrilligOpcode> {
+        let artifact = context.artifact();
+        let mut entry_point_artifact =
+            BrilligContext::new_entry_point_artifact(arguments, returns, "test".to_string());
+        entry_point_artifact.link_with(&artifact);
+        entry_point_artifact.finish()
+    }
+
+    pub(crate) fn create_and_run_vm(
+        memory: Vec<Value>,
+        param_registers: Vec<Value>,
+        context: BrilligContext,
+        arguments: Vec<BrilligParameter>,
+        returns: Vec<BrilligParameter>,
+    ) -> VM<'static, DummyBlackBoxSolver> {
+        let mut vm = VM::new(
+            Registers { inner: param_registers },
+            memory,
+            create_entry_point_bytecode(context, arguments, returns),
+            vec![],
+            &DummyBlackBoxSolver,
+        );
+
+        let status = vm.process_opcodes();
+        assert_eq!(status, VMStatus::Finished);
+        vm
+    }
+
     /// Test a Brillig foreign call returning a vector
     #[test]
     fn test_brillig_ir_foreign_call_return_vector() {
@@ -832,7 +1057,7 @@ mod tests {
         //   let the_sequence = get_number_sequence(12);
         //   assert(the_sequence.len() == 12);
         // }
-        let mut context = BrilligContext::new(vec![], vec![]);
+        let mut context = BrilligContext::new(true);
         let r_stack = ReservedRegisters::stack_pointer();
         // Start stack pointer at 0
         context.const_instruction(r_stack, Value::from(0_usize));
@@ -849,25 +1074,9 @@ mod tests {
             &[RegisterOrMemory::HeapVector(HeapVector { pointer: r_stack, size: r_output_size })],
         );
         // push stack frame by r_returned_size
-        context.binary_instruction(
-            r_stack,
-            r_output_size,
-            r_stack,
-            BrilligBinaryOp::Integer {
-                op: BinaryIntOp::Add,
-                bit_size: BRILLIG_MEMORY_ADDRESSING_BIT_SIZE,
-            },
-        );
+        context.memory_op(r_stack, r_output_size, r_stack, BinaryIntOp::Add);
         // check r_input_size == r_output_size
-        context.binary_instruction(
-            r_input_size,
-            r_output_size,
-            r_equality,
-            BrilligBinaryOp::Integer {
-                op: BinaryIntOp::Equals,
-                bit_size: BRILLIG_MEMORY_ADDRESSING_BIT_SIZE,
-            },
-        );
+        context.memory_op(r_input_size, r_output_size, r_equality, BinaryIntOp::Equals);
         // We push a JumpIf and Trap opcode directly as the constrain instruction
         // uses unresolved jumps which requires a block to be constructed in SSA and
         // we don't need this for Brillig IR tests
diff --git a/crates/noirc_evaluator/src/brillig/brillig_ir/artifact.rs b/crates/noirc_evaluator/src/brillig/brillig_ir/artifact.rs
index 53e4702213e..46e3df2e465 100644
--- a/crates/noirc_evaluator/src/brillig/brillig_ir/artifact.rs
+++ b/crates/noirc_evaluator/src/brillig/brillig_ir/artifact.rs
@@ -1,14 +1,12 @@
-use acvm::acir::brillig::{Opcode as BrilligOpcode, RegisterIndex};
+use acvm::acir::brillig::Opcode as BrilligOpcode;
 use std::collections::HashMap;
 
-use crate::brillig::brillig_ir::ReservedRegisters;
-
 /// Represents a parameter or a return value of a function.
 #[derive(Debug, Clone)]
 pub(crate) enum BrilligParameter {
-    Register,
-    // A heap array is filled in memory and a pointer to the first element is passed in the register.
-    HeapArray(usize),
+    Simple,
+    Array(Vec<BrilligParameter>, usize),
+    Slice(Vec<BrilligParameter>),
 }
 
 #[derive(Default, Debug, Clone)]
@@ -28,11 +26,6 @@ pub(crate) struct BrilligArtifact {
     /// TODO: perhaps we should combine this with the `unresolved_jumps` field
     /// TODO: and have an enum which indicates whether the jump is internal or external
     unresolved_external_call_labels: Vec<(JumpInstructionPosition, UnresolvedJumpLocation)>,
-    /// The return values that this function will return.
-    return_parameters: Vec<BrilligParameter>,
-
-    /// The arguments that this function will take.
-    arguments: Vec<BrilligParameter>,
 }
 
 /// A pointer to a location in the opcode.
@@ -58,90 +51,12 @@ pub(crate) type JumpInstructionPosition = OpcodeLocation;
 pub(crate) type UnresolvedJumpLocation = Label;
 
 impl BrilligArtifact {
-    /// Initialize an artifact with the number of arguments and return parameters
-    pub(crate) fn new(
-        arguments: Vec<BrilligParameter>,
-        return_parameters: Vec<BrilligParameter>,
-    ) -> BrilligArtifact {
-        BrilligArtifact {
-            byte_code: Vec::new(),
-            unresolved_jumps: Vec::new(),
-            labels: HashMap::new(),
-            unresolved_external_call_labels: Vec::new(),
-            arguments,
-            return_parameters,
-        }
-    }
-
-    /// Creates an entry point artifact that will jump to the function label provided.
-    pub(crate) fn new_entry_point_artifact(
-        arguments: Vec<BrilligParameter>,
-        return_parameters: Vec<BrilligParameter>,
-        target_function: Label,
-    ) -> BrilligArtifact {
-        let mut entry_point_artifact = BrilligArtifact::new(arguments, return_parameters);
-        entry_point_artifact.entry_point_instruction();
-
-        entry_point_artifact
-            .add_unresolved_external_call(BrilligOpcode::Call { location: 0 }, target_function);
-
-        entry_point_artifact.exit_point_instruction();
-        entry_point_artifact
-    }
-
     /// Resolves all jumps and generates the final bytecode
     pub(crate) fn finish(mut self) -> Vec<BrilligOpcode> {
         self.resolve_jumps();
         self.byte_code
     }
 
-    /// Adds the instructions needed to handle entry point parameters
-    ///
-    /// And sets the starting value of the reserved registers
-    fn entry_point_instruction(&mut self) {
-        // Translate the inputs by the reserved registers offset
-        for i in (0..self.arguments.len()).rev() {
-            self.byte_code.push(BrilligOpcode::Mov {
-                destination: ReservedRegisters::user_register_index(i),
-                source: RegisterIndex::from(i),
-            });
-        }
-
-        // Calculate the initial value for the stack pointer register
-        let size_arguments_memory = self
-            .arguments
-            .iter()
-            .map(|arg| match arg {
-                BrilligParameter::Register => 0,
-                BrilligParameter::HeapArray(size) => *size,
-            })
-            .sum::<usize>();
-
-        // Set the initial value of the stack pointer register
-        self.byte_code.push(BrilligOpcode::Const {
-            destination: ReservedRegisters::stack_pointer(),
-            value: size_arguments_memory.into(),
-        });
-    }
-
-    /// Adds the instructions needed to handle return parameters
-    fn exit_point_instruction(&mut self) {
-        // We want all functions to follow the calling convention of returning
-        // their results in the first `n` registers. So we modify the bytecode of the
-        // function to move the return values to the first `n` registers once completed.
-
-        // TODO: this _seems_ like an abstraction leak, we need to know about the reserved
-        // TODO: registers in order to do this.
-        // Move the results to registers 0..n
-        for i in 0..self.return_parameters.len() {
-            self.push_opcode(BrilligOpcode::Mov {
-                destination: i.into(),
-                source: ReservedRegisters::user_register_index(i),
-            });
-        }
-        self.push_opcode(BrilligOpcode::Stop);
-    }
-
     /// Gets the first unresolved function call of this artifact.
     pub(crate) fn first_unresolved_function_call(&self) -> Option<Label> {
         self.unresolved_external_call_labels.first().map(|(_, label)| label.clone())
diff --git a/crates/noirc_evaluator/src/brillig/brillig_ir/debug_show.rs b/crates/noirc_evaluator/src/brillig/brillig_ir/debug_show.rs
index 977792ee07b..75716e49177 100644
--- a/crates/noirc_evaluator/src/brillig/brillig_ir/debug_show.rs
+++ b/crates/noirc_evaluator/src/brillig/brillig_ir/debug_show.rs
@@ -6,9 +6,6 @@ use acvm::acir::brillig::{
     Value,
 };
 
-/// Controls whether debug traces are enabled
-const ENABLE_DEBUG_TRACE: bool = true;
-
 /// Trait for converting values into debug-friendly strings.
 trait DebugToString {
     fn debug_to_string(&self) -> String;
@@ -130,215 +127,311 @@ impl<T: DebugToString> DebugToString for [T] {
 }
 
 macro_rules! debug_println {
-    ( $literal:expr ) => {
-        if ENABLE_DEBUG_TRACE {
-            println!("{}", $literal);
+    ( $enable_debug:expr, $literal:expr ) => {
+        if $enable_debug {
+            println!("{}", $literal)
         }
     };
-    ( $format_message:expr, $( $x:expr ),* ) => {
-        if ENABLE_DEBUG_TRACE {
+    ( $enable_debug:expr, $format_message:expr, $( $x:expr ),* ) => {
+        if $enable_debug {
             println!($format_message, $( $x.debug_to_string(), )*)
         }
     };
 }
 
-/// Emits brillig bytecode to jump to a trap condition if `condition`
-/// is false.
-pub(crate) fn constrain_instruction(condition: RegisterIndex) {
-    debug_println!("  ASSERT {} != 0", condition);
+pub(crate) struct DebugShow {
+    enable_debug_trace: bool,
 }
 
-/// Processes a return instruction.
-pub(crate) fn return_instruction(return_registers: &[RegisterIndex]) {
-    let registers_string = return_registers
-        .iter()
-        .map(RegisterIndex::debug_to_string)
-        .collect::<Vec<String>>()
-        .join(", ");
+impl DebugShow {
+    pub(crate) fn new(enable_debug_trace: bool) -> DebugShow {
+        DebugShow { enable_debug_trace }
+    }
 
-    debug_println!("  // return {};", registers_string);
-}
+    /// Emits brillig bytecode to jump to a trap condition if `condition`
+    /// is false.
+    pub(crate) fn constrain_instruction(&self, condition: RegisterIndex) {
+        debug_println!(self.enable_debug_trace, "  ASSERT {} != 0", condition);
+    }
 
-/// Emits a `mov` instruction.
-pub(crate) fn mov_instruction(destination: RegisterIndex, source: RegisterIndex) {
-    debug_println!("  MOV {}, {}", destination, source);
-}
+    /// Processes a return instruction.
+    pub(crate) fn return_instruction(&self, return_registers: &[RegisterIndex]) {
+        let registers_string = return_registers
+            .iter()
+            .map(RegisterIndex::debug_to_string)
+            .collect::<Vec<String>>()
+            .join(", ");
 
-/// Processes a binary instruction according `operation`.
-pub(crate) fn binary_instruction(
-    lhs: RegisterIndex,
-    rhs: RegisterIndex,
-    result: RegisterIndex,
-    operation: BrilligBinaryOp,
-) {
-    debug_println!("  {} = {} {} {}", result, lhs, operation, rhs);
-}
+        debug_println!(self.enable_debug_trace, "  // return {};", registers_string);
+    }
 
-/// Stores the value of `constant` in the `result` register
-pub(crate) fn const_instruction(result: RegisterIndex, constant: Value) {
-    debug_println!("  CONST {} = {}", result, constant);
-}
+    /// Emits a `mov` instruction.
+    pub(crate) fn mov_instruction(&self, destination: RegisterIndex, source: RegisterIndex) {
+        debug_println!(self.enable_debug_trace, "  MOV {}, {}", destination, source);
+    }
 
-/// Processes a not instruction. Append with "_" as this is a high-level instruction.
-pub(crate) fn not_instruction(condition: RegisterIndex, bit_size: u32, result: RegisterIndex) {
-    debug_println!("  i{}_NOT {} = !{}", bit_size, result, condition);
-}
+    /// Processes a binary instruction according `operation`.
+    pub(crate) fn binary_instruction(
+        &self,
+        lhs: RegisterIndex,
+        rhs: RegisterIndex,
+        result: RegisterIndex,
+        operation: BrilligBinaryOp,
+    ) {
+        debug_println!(self.enable_debug_trace, "  {} = {} {} {}", result, lhs, operation, rhs);
+    }
 
-/// Processes a foreign call instruction.
-pub(crate) fn foreign_call_instruction(
-    func_name: String,
-    inputs: &[RegisterOrMemory],
-    outputs: &[RegisterOrMemory],
-) {
-    debug_println!("  FOREIGN_CALL {} ({}) => {}", func_name, inputs, outputs);
-}
+    /// Stores the value of `constant` in the `result` register
+    pub(crate) fn const_instruction(&self, result: RegisterIndex, constant: Value) {
+        debug_println!(self.enable_debug_trace, "  CONST {} = {}", result, constant);
+    }
 
-/// Emits a load instruction
-pub(crate) fn load_instruction(destination: RegisterIndex, source_pointer: RegisterIndex) {
-    debug_println!("  LOAD {} = *{}", destination, source_pointer);
-}
+    /// Processes a not instruction. Append with "_" as this is a high-level instruction.
+    pub(crate) fn not_instruction(
+        &self,
+        condition: RegisterIndex,
+        bit_size: u32,
+        result: RegisterIndex,
+    ) {
+        debug_println!(self.enable_debug_trace, "  i{}_NOT {} = !{}", bit_size, result, condition);
+    }
 
-/// Emits a store instruction
-pub(crate) fn store_instruction(destination_pointer: RegisterIndex, source: RegisterIndex) {
-    debug_println!("  STORE *{} = {}", destination_pointer, source);
-}
+    /// Processes a foreign call instruction.
+    pub(crate) fn foreign_call_instruction(
+        &self,
+        func_name: String,
+        inputs: &[RegisterOrMemory],
+        outputs: &[RegisterOrMemory],
+    ) {
+        debug_println!(
+            self.enable_debug_trace,
+            "  FOREIGN_CALL {} ({}) => {}",
+            func_name,
+            inputs,
+            outputs
+        );
+    }
 
-/// Emits a stop instruction
-pub(crate) fn stop_instruction() {
-    debug_println!("  STOP");
-}
+    /// Emits a load instruction
+    pub(crate) fn load_instruction(
+        &self,
+        destination: RegisterIndex,
+        source_pointer: RegisterIndex,
+    ) {
+        debug_println!(self.enable_debug_trace, "  LOAD {} = *{}", destination, source_pointer);
+    }
 
-/// Debug function for allocate_array_instruction
-pub(crate) fn allocate_array_instruction(
-    pointer_register: RegisterIndex,
-    size_register: RegisterIndex,
-) {
-    debug_println!("  ALLOCATE_ARRAY {} SIZE {}", pointer_register, size_register);
-}
+    /// Emits a store instruction
+    pub(crate) fn store_instruction(
+        &self,
+        destination_pointer: RegisterIndex,
+        source: RegisterIndex,
+    ) {
+        debug_println!(self.enable_debug_trace, "  STORE *{} = {}", destination_pointer, source);
+    }
 
-/// Debug function for allocate_instruction
-pub(crate) fn allocate_instruction(pointer_register: RegisterIndex) {
-    debug_println!("  ALLOCATE {} ", pointer_register);
-}
+    /// Emits a stop instruction
+    pub(crate) fn stop_instruction(&self) {
+        debug_println!(self.enable_debug_trace, "  STOP");
+    }
 
-/// Debug function for array_get
-pub(crate) fn array_get(array_ptr: RegisterIndex, index: RegisterIndex, result: RegisterIndex) {
-    debug_println!("  ARRAY_GET {}[{}] -> {}", array_ptr, index, result);
-}
+    /// Debug function for allocate_array_instruction
+    pub(crate) fn allocate_array_instruction(
+        &self,
+        pointer_register: RegisterIndex,
+        size_register: RegisterIndex,
+    ) {
+        debug_println!(
+            self.enable_debug_trace,
+            "  ALLOCATE_ARRAY {} SIZE {}",
+            pointer_register,
+            size_register
+        );
+    }
 
-/// Debug function for array_set
-pub(crate) fn array_set(array_ptr: RegisterIndex, index: RegisterIndex, value: RegisterIndex) {
-    debug_println!("  ARRAY_SET {}[{}] = {}", array_ptr, index, value);
-}
+    /// Debug function for allocate_instruction
+    pub(crate) fn allocate_instruction(&self, pointer_register: RegisterIndex) {
+        debug_println!(self.enable_debug_trace, "  ALLOCATE {} ", pointer_register);
+    }
 
-/// Debug function for copy_array_instruction
-pub(crate) fn copy_array_instruction(
-    source: RegisterIndex,
-    destination: RegisterIndex,
-    num_elements_register: RegisterIndex,
-) {
-    debug_println!(
-        "  COPY_ARRAY {} -> {} ({} ELEMENTS)",
-        source,
-        destination,
-        num_elements_register
-    );
-}
+    /// Debug function for array_get
+    pub(crate) fn array_get(
+        &self,
+        array_ptr: RegisterIndex,
+        index: RegisterIndex,
+        result: RegisterIndex,
+    ) {
+        debug_println!(
+            self.enable_debug_trace,
+            "  ARRAY_GET {}[{}] -> {}",
+            array_ptr,
+            index,
+            result
+        );
+    }
 
-/// Debug function for enter_context
-pub(crate) fn enter_context(label: String) {
-    if !label.ends_with("-b0") {
-        // Hacky readability fix: don't print labels e.g. f1 then f1-b0 one after another, they mean the same thing
-        debug_println!("{}:", label);
+    /// Debug function for array_set
+    pub(crate) fn array_set(
+        &self,
+        array_ptr: RegisterIndex,
+        index: RegisterIndex,
+        value: RegisterIndex,
+    ) {
+        debug_println!(self.enable_debug_trace, "  ARRAY_SET {}[{}] = {}", array_ptr, index, value);
     }
-}
 
-/// Debug function for jump_instruction
-pub(crate) fn jump_instruction(target_label: String) {
-    debug_println!("  JUMP_TO {}", target_label);
-}
+    /// Debug function for copy_array_instruction
+    pub(crate) fn copy_array_instruction(
+        &self,
+        source: RegisterIndex,
+        destination: RegisterIndex,
+        num_elements_register: RegisterIndex,
+    ) {
+        debug_println!(
+            self.enable_debug_trace,
+            "  COPY_ARRAY {} -> {} ({} ELEMENTS)",
+            source,
+            destination,
+            num_elements_register
+        );
+    }
 
-/// Debug function for jump_if_instruction
-pub(crate) fn jump_if_instruction<T: ToString>(condition: RegisterIndex, target_label: T) {
-    debug_println!("  JUMP_IF {} TO {}", condition, target_label.to_string());
-}
+    /// Debug function for enter_context
+    pub(crate) fn enter_context(&self, label: String) {
+        if !label.ends_with("-b0") {
+            // Hacky readability fix: don't print labels e.g. f1 then f1-b0 one after another, they mean the same thing
+            debug_println!(self.enable_debug_trace, "{}:", label);
+        }
+    }
 
-/// Debug function for cast_instruction
-pub(crate) fn cast_instruction(
-    destination: RegisterIndex,
-    source: RegisterIndex,
-    target_bit_size: u32,
-) {
-    debug_println!("  CAST {} FROM {} TO {} BITS", destination, source, target_bit_size);
-}
+    /// Debug function for jump_instruction
+    pub(crate) fn jump_instruction(&self, target_label: String) {
+        debug_println!(self.enable_debug_trace, "  JUMP_TO {}", target_label);
+    }
 
-/// Debug function for black_box_op
-pub(crate) fn black_box_op_instruction(op: BlackBoxOp) {
-    match op {
-        BlackBoxOp::Sha256 { message, output } => {
-            debug_println!("  SHA256 {} -> {}", message, output);
-        }
-        BlackBoxOp::Keccak256 { message, output } => {
-            debug_println!("  KECCAK256 {} -> {}", message, output);
-        }
-        BlackBoxOp::Blake2s { message, output } => {
-            debug_println!("  BLAKE2S {} -> {}", message, output);
-        }
-        BlackBoxOp::HashToField128Security { message, output } => {
-            debug_println!("  HASH_TO_FIELD_128_SECURITY {} -> {}", message, output);
-        }
-        BlackBoxOp::EcdsaSecp256k1 {
-            hashed_msg,
-            public_key_x,
-            public_key_y,
-            signature,
-            result,
-        } => {
-            debug_println!(
-                "  ECDSA_SECP256K1 {} {} {} {} -> {}",
+    /// Debug function for jump_if_instruction
+    pub(crate) fn jump_if_instruction<T: ToString>(
+        &self,
+        condition: RegisterIndex,
+        target_label: T,
+    ) {
+        debug_println!(
+            self.enable_debug_trace,
+            "  JUMP_IF {} TO {}",
+            condition,
+            target_label.to_string()
+        );
+    }
+
+    /// Debug function for cast_instruction
+    pub(crate) fn cast_instruction(
+        &self,
+        destination: RegisterIndex,
+        source: RegisterIndex,
+        target_bit_size: u32,
+    ) {
+        debug_println!(
+            self.enable_debug_trace,
+            "  CAST {} FROM {} TO {} BITS",
+            destination,
+            source,
+            target_bit_size
+        );
+    }
+
+    /// Debug function for black_box_op
+    pub(crate) fn black_box_op_instruction(&self, op: BlackBoxOp) {
+        match op {
+            BlackBoxOp::Sha256 { message, output } => {
+                debug_println!(self.enable_debug_trace, "  SHA256 {} -> {}", message, output);
+            }
+            BlackBoxOp::Keccak256 { message, output } => {
+                debug_println!(self.enable_debug_trace, "  KECCAK256 {} -> {}", message, output);
+            }
+            BlackBoxOp::Blake2s { message, output } => {
+                debug_println!(self.enable_debug_trace, "  BLAKE2S {} -> {}", message, output);
+            }
+            BlackBoxOp::HashToField128Security { message, output } => {
+                debug_println!(
+                    self.enable_debug_trace,
+                    "  HASH_TO_FIELD_128_SECURITY {} -> {}",
+                    message,
+                    output
+                );
+            }
+            BlackBoxOp::EcdsaSecp256k1 {
                 hashed_msg,
                 public_key_x,
                 public_key_y,
                 signature,
-                result
-            );
-        }
-        BlackBoxOp::EcdsaSecp256r1 {
-            hashed_msg,
-            public_key_x,
-            public_key_y,
-            signature,
-            result,
-        } => {
-            debug_println!(
-                "  ECDSA_SECP256R1 {} {} {} {} -> {}",
+                result,
+            } => {
+                debug_println!(
+                    self.enable_debug_trace,
+                    "  ECDSA_SECP256K1 {} {} {} {} -> {}",
+                    hashed_msg,
+                    public_key_x,
+                    public_key_y,
+                    signature,
+                    result
+                );
+            }
+            BlackBoxOp::EcdsaSecp256r1 {
                 hashed_msg,
                 public_key_x,
                 public_key_y,
                 signature,
-                result
-            );
-        }
-        BlackBoxOp::FixedBaseScalarMul { input, result } => {
-            debug_println!("  FIXED_BASE_SCALAR_MUL {} -> {}", input, result);
-        }
-        BlackBoxOp::Pedersen { inputs, domain_separator, output } => {
-            debug_println!("  PEDERSEN {} {} -> {}", inputs, domain_separator, output);
-        }
-        BlackBoxOp::SchnorrVerify { public_key_x, public_key_y, message, signature, result } => {
-            debug_println!(
-                "  SCHNORR_VERIFY {} {} {} {} -> {}",
+                result,
+            } => {
+                debug_println!(
+                    self.enable_debug_trace,
+                    "  ECDSA_SECP256R1 {} {} {} {} -> {}",
+                    hashed_msg,
+                    public_key_x,
+                    public_key_y,
+                    signature,
+                    result
+                );
+            }
+            BlackBoxOp::FixedBaseScalarMul { input, result } => {
+                debug_println!(
+                    self.enable_debug_trace,
+                    "  FIXED_BASE_SCALAR_MUL {} -> {}",
+                    input,
+                    result
+                );
+            }
+            BlackBoxOp::Pedersen { inputs, domain_separator, output } => {
+                debug_println!(
+                    self.enable_debug_trace,
+                    "  PEDERSEN {} {} -> {}",
+                    inputs,
+                    domain_separator,
+                    output
+                );
+            }
+            BlackBoxOp::SchnorrVerify {
                 public_key_x,
                 public_key_y,
                 message,
                 signature,
-                result
-            );
+                result,
+            } => {
+                debug_println!(
+                    self.enable_debug_trace,
+                    "  SCHNORR_VERIFY {} {} {} {} -> {}",
+                    public_key_x,
+                    public_key_y,
+                    message,
+                    signature,
+                    result
+                );
+            }
         }
     }
-}
 
-/// Debug function for cast_instruction
-pub(crate) fn add_external_call_instruction(func_label: String) {
-    debug_println!("  CALL {}", func_label);
+    /// Debug function for cast_instruction
+    pub(crate) fn add_external_call_instruction(&self, func_label: String) {
+        debug_println!(self.enable_debug_trace, "  CALL {}", func_label);
+    }
 }
diff --git a/crates/noirc_evaluator/src/brillig/brillig_ir/entry_point.rs b/crates/noirc_evaluator/src/brillig/brillig_ir/entry_point.rs
new file mode 100644
index 00000000000..23c7b8a2c5b
--- /dev/null
+++ b/crates/noirc_evaluator/src/brillig/brillig_ir/entry_point.rs
@@ -0,0 +1,432 @@
+use crate::brillig::brillig_ir::ReservedRegisters;
+
+use super::{
+    artifact::{BrilligArtifact, BrilligParameter},
+    debug_show::DebugShow,
+    registers::BrilligRegistersContext,
+    BrilligContext,
+};
+use acvm::acir::brillig::{Opcode as BrilligOpcode, RegisterIndex};
+
+impl BrilligContext {
+    /// Creates an entry point artifact that will jump to the function label provided.
+    pub(crate) fn new_entry_point_artifact<T: ToString>(
+        arguments: Vec<BrilligParameter>,
+        return_parameters: Vec<BrilligParameter>,
+        target_function: T,
+    ) -> BrilligArtifact {
+        let mut context = BrilligContext {
+            obj: BrilligArtifact::default(),
+            registers: BrilligRegistersContext::new(),
+            context_label: String::default(),
+            section_label: 0,
+            debug_show: DebugShow::new(false),
+        };
+
+        context.entry_point_instruction(arguments);
+
+        context.add_external_call_instruction(target_function);
+
+        context.exit_point_instruction(return_parameters);
+        context.artifact()
+    }
+
+    /// Adds the instructions needed to handle entry point parameters
+    ///
+    /// And sets the starting value of the reserved registers
+    fn entry_point_instruction(&mut self, arguments: Vec<BrilligParameter>) {
+        // Translate the inputs by the reserved registers offset
+        for i in (0..arguments.len()).rev() {
+            self.push_opcode(BrilligOpcode::Mov {
+                destination: ReservedRegisters::user_register_index(i),
+                source: RegisterIndex::from(i),
+            });
+            // Make sure we don't overwrite the arguments
+            self.allocate_register();
+        }
+
+        // Calculate the initial value for the stack pointer register
+        let size_arguments_memory: usize = arguments
+            .iter()
+            .map(|arg| match arg {
+                BrilligParameter::Simple => 0,
+                _ => BrilligContext::flattened_size(arg),
+            })
+            .sum();
+
+        // Set the initial value of the stack pointer register
+        self.push_opcode(BrilligOpcode::Const {
+            destination: ReservedRegisters::stack_pointer(),
+            value: size_arguments_memory.into(),
+        });
+        // Set the initial value of the previous stack pointer register
+        self.push_opcode(BrilligOpcode::Const {
+            destination: ReservedRegisters::previous_stack_pointer(),
+            value: 0_usize.into(),
+        });
+
+        for (index, parameter) in arguments.iter().enumerate() {
+            if let BrilligParameter::Array(item_type, item_count) = parameter {
+                if item_type.iter().any(|param| !matches!(param, BrilligParameter::Simple)) {
+                    let pointer_register = ReservedRegisters::user_register_index(index);
+                    let deflattened_register =
+                        self.deflatten_array(item_type, *item_count, pointer_register);
+                    self.mov_instruction(pointer_register, deflattened_register);
+                }
+            }
+        }
+    }
+
+    /// Computes the size of a parameter if it was flattened
+    fn flattened_size(param: &BrilligParameter) -> usize {
+        match param {
+            BrilligParameter::Simple => 1,
+            BrilligParameter::Array(item_types, item_count) => {
+                let item_size: usize = item_types.iter().map(BrilligContext::flattened_size).sum();
+                item_count * item_size
+            }
+            BrilligParameter::Slice(_) => {
+                unreachable!("ICE: Slices cannot be passed as entry point arguments")
+            }
+        }
+    }
+
+    /// Deflatten an array by recursively allocating nested arrays and copying the plain values.
+    fn deflatten_array(
+        &mut self,
+        item_type: &[BrilligParameter],
+        item_count: usize,
+        flattened_array_pointer: RegisterIndex,
+    ) -> RegisterIndex {
+        let movement_register = self.allocate_register();
+        let deflattened_array_pointer = self.allocate_register();
+
+        let target_item_size = item_type.len();
+        let source_item_size: usize = item_type.iter().map(BrilligContext::flattened_size).sum();
+
+        self.allocate_fixed_length_array(deflattened_array_pointer, item_count * target_item_size);
+
+        for item_index in 0..item_count {
+            let source_item_base_index = item_index * source_item_size;
+            let target_item_base_index = item_index * target_item_size;
+
+            let mut source_offset = 0;
+
+            for (subitem_index, subitem) in item_type.iter().enumerate() {
+                let source_index =
+                    self.make_constant((source_item_base_index + source_offset).into());
+
+                let target_index =
+                    self.make_constant((target_item_base_index + subitem_index).into());
+
+                match subitem {
+                    BrilligParameter::Simple => {
+                        self.array_get(flattened_array_pointer, source_index, movement_register);
+                        self.array_set(deflattened_array_pointer, target_index, movement_register);
+                        source_offset += 1;
+                    }
+                    BrilligParameter::Array(nested_array_item_type, nested_array_item_count) => {
+                        let nested_array_pointer = self.allocate_register();
+                        self.mov_instruction(nested_array_pointer, flattened_array_pointer);
+                        self.memory_op(
+                            nested_array_pointer,
+                            source_index,
+                            nested_array_pointer,
+                            acvm::brillig_vm::brillig::BinaryIntOp::Add,
+                        );
+                        let deflattened_nested_array_pointer = self.deflatten_array(
+                            nested_array_item_type,
+                            *nested_array_item_count,
+                            nested_array_pointer,
+                        );
+                        self.array_set(
+                            deflattened_array_pointer,
+                            target_index,
+                            deflattened_nested_array_pointer,
+                        );
+
+                        self.deallocate_register(nested_array_pointer);
+
+                        source_offset += BrilligContext::flattened_size(subitem);
+                    }
+                    BrilligParameter::Slice(..) => unreachable!("ICE: Cannot deflatten slices"),
+                }
+
+                self.deallocate_register(source_index);
+                self.deallocate_register(target_index);
+            }
+        }
+
+        self.deallocate_register(movement_register);
+
+        deflattened_array_pointer
+    }
+
+    /// Adds the instructions needed to handle return parameters
+    fn exit_point_instruction(&mut self, return_parameters: Vec<BrilligParameter>) {
+        // Make sure we don't overwrite the return parameters
+        return_parameters.iter().for_each(|_| {
+            self.allocate_register();
+        });
+
+        for (index, ret) in return_parameters.iter().enumerate() {
+            if let BrilligParameter::Array(item_type, item_count) = ret {
+                if item_type.iter().any(|item| !matches!(item, BrilligParameter::Simple)) {
+                    let returned_pointer = ReservedRegisters::user_register_index(index);
+                    let flattened_array_pointer = self.allocate_register();
+
+                    self.allocate_fixed_length_array(
+                        flattened_array_pointer,
+                        BrilligContext::flattened_size(ret),
+                    );
+
+                    self.flatten_array(
+                        item_type,
+                        *item_count,
+                        flattened_array_pointer,
+                        returned_pointer,
+                    );
+
+                    self.mov_instruction(returned_pointer, flattened_array_pointer);
+                }
+            }
+        }
+        // We want all functions to follow the calling convention of returning
+        // their results in the first `n` registers. So we to move the return values
+        // to the first `n` registers once completed.
+
+        // Move the results to registers 0..n
+        for i in 0..return_parameters.len() {
+            self.push_opcode(BrilligOpcode::Mov {
+                destination: i.into(),
+                source: ReservedRegisters::user_register_index(i),
+            });
+        }
+        self.push_opcode(BrilligOpcode::Stop);
+    }
+
+    // Flattens an array by recursively copying nested arrays and regular items.
+    fn flatten_array(
+        &mut self,
+        item_type: &[BrilligParameter],
+        item_count: usize,
+        flattened_array_pointer: RegisterIndex,
+        deflattened_array_pointer: RegisterIndex,
+    ) {
+        let movement_register = self.allocate_register();
+
+        let source_item_size = item_type.len();
+        let target_item_size: usize = item_type.iter().map(BrilligContext::flattened_size).sum();
+
+        for item_index in 0..item_count {
+            let source_item_base_index = item_index * source_item_size;
+            let target_item_base_index = item_index * target_item_size;
+
+            let mut target_offset = 0;
+
+            for (subitem_index, subitem) in item_type.iter().enumerate() {
+                let source_index =
+                    self.make_constant((source_item_base_index + subitem_index).into());
+                let target_index =
+                    self.make_constant((target_item_base_index + target_offset).into());
+
+                match subitem {
+                    BrilligParameter::Simple => {
+                        self.array_get(deflattened_array_pointer, source_index, movement_register);
+                        self.array_set(flattened_array_pointer, target_index, movement_register);
+                        target_offset += 1;
+                    }
+                    BrilligParameter::Array(nested_array_item_type, nested_array_item_count) => {
+                        let nested_array_pointer = self.allocate_register();
+                        self.array_get(
+                            deflattened_array_pointer,
+                            source_index,
+                            nested_array_pointer,
+                        );
+
+                        let flattened_nested_array_pointer = self.allocate_register();
+
+                        self.mov_instruction(
+                            flattened_nested_array_pointer,
+                            flattened_array_pointer,
+                        );
+
+                        self.memory_op(
+                            flattened_nested_array_pointer,
+                            target_index,
+                            flattened_nested_array_pointer,
+                            acvm::brillig_vm::brillig::BinaryIntOp::Add,
+                        );
+
+                        self.flatten_array(
+                            nested_array_item_type,
+                            *nested_array_item_count,
+                            flattened_nested_array_pointer,
+                            nested_array_pointer,
+                        );
+
+                        self.deallocate_register(nested_array_pointer);
+                        self.deallocate_register(flattened_nested_array_pointer);
+
+                        target_offset += BrilligContext::flattened_size(subitem);
+                    }
+                    BrilligParameter::Slice(..) => unreachable!("ICE: Cannot flatten slices"),
+                }
+
+                self.deallocate_register(source_index);
+                self.deallocate_register(target_index);
+            }
+        }
+
+        self.deallocate_register(movement_register);
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use acvm::brillig_vm::brillig::{RegisterIndex, Value};
+
+    use crate::brillig::brillig_ir::{
+        artifact::BrilligParameter,
+        tests::{create_and_run_vm, create_context},
+    };
+
+    #[test]
+    fn entry_point_with_nested_array_parameter() {
+        let flattened_array = vec![
+            Value::from(1_usize),
+            Value::from(2_usize),
+            Value::from(3_usize),
+            Value::from(4_usize),
+            Value::from(5_usize),
+            Value::from(6_usize),
+        ];
+        let arguments = vec![BrilligParameter::Array(
+            vec![
+                BrilligParameter::Array(vec![BrilligParameter::Simple], 2),
+                BrilligParameter::Simple,
+            ],
+            2,
+        )];
+        let returns = vec![BrilligParameter::Simple];
+
+        let mut context = create_context();
+
+        // Allocate the parameter
+        let array_pointer = context.allocate_register();
+
+        context.return_instruction(&[array_pointer]);
+
+        let vm = create_and_run_vm(
+            flattened_array.clone(),
+            vec![Value::from(0_usize)],
+            context,
+            arguments,
+            returns,
+        );
+        let memory = vm.get_memory();
+
+        assert_eq!(vm.get_registers().get(RegisterIndex(0)), Value::from(flattened_array.len()));
+        assert_eq!(
+            memory,
+            &vec![
+                // The original flattened values
+                Value::from(1_usize),
+                Value::from(2_usize),
+                Value::from(3_usize),
+                Value::from(4_usize),
+                Value::from(5_usize),
+                Value::from(6_usize),
+                // The pointer to the nested array of the first item
+                Value::from(10_usize),
+                Value::from(3_usize),
+                // The pointer to the nested array of the second item
+                Value::from(12_usize),
+                Value::from(6_usize),
+                // The nested array of the first item
+                Value::from(1_usize),
+                Value::from(2_usize),
+                // The nested array of the second item
+                Value::from(4_usize),
+                Value::from(5_usize),
+            ]
+        );
+    }
+
+    #[test]
+    fn entry_point_with_nested_array_return() {
+        let flattened_array = vec![
+            Value::from(1_usize),
+            Value::from(2_usize),
+            Value::from(3_usize),
+            Value::from(4_usize),
+            Value::from(5_usize),
+            Value::from(6_usize),
+        ];
+
+        let array_param = BrilligParameter::Array(
+            vec![
+                BrilligParameter::Simple,
+                BrilligParameter::Array(vec![BrilligParameter::Simple], 2),
+            ],
+            2,
+        );
+
+        let arguments = vec![array_param.clone()];
+        let returns = vec![array_param];
+
+        let mut context = create_context();
+
+        // Allocate the parameter
+        let array_pointer = context.allocate_register();
+
+        context.return_instruction(&[array_pointer]);
+
+        let vm = create_and_run_vm(
+            flattened_array.clone(),
+            vec![Value::from(0_usize)],
+            context,
+            arguments,
+            returns,
+        );
+        let memory = vm.get_memory();
+
+        assert_eq!(
+            vm.get_registers().get(RegisterIndex(0)),
+            // The returned value will be past the original array and the deflattened array
+            Value::from(flattened_array.len() + (flattened_array.len() + 2)),
+        );
+
+        assert_eq!(
+            memory,
+            &vec![
+                // The original flattened values
+                Value::from(1_usize),
+                Value::from(2_usize),
+                Value::from(3_usize),
+                Value::from(4_usize),
+                Value::from(5_usize),
+                Value::from(6_usize),
+                // The pointer to the nested array of the first item
+                Value::from(1_usize),
+                Value::from(10_usize),
+                // The pointer to the nested array of the second item
+                Value::from(4_usize),
+                Value::from(12_usize),
+                // The nested array of the first item
+                Value::from(2_usize),
+                Value::from(3_usize),
+                // The nested array of the second item
+                Value::from(5_usize),
+                Value::from(6_usize),
+                // The values flattened again
+                Value::from(1_usize),
+                Value::from(2_usize),
+                Value::from(3_usize),
+                Value::from(4_usize),
+                Value::from(5_usize),
+                Value::from(6_usize),
+            ]
+        );
+    }
+}
diff --git a/crates/noirc_evaluator/src/brillig/mod.rs b/crates/noirc_evaluator/src/brillig/mod.rs
index c5ae0a514ed..105475323a7 100644
--- a/crates/noirc_evaluator/src/brillig/mod.rs
+++ b/crates/noirc_evaluator/src/brillig/mod.rs
@@ -24,8 +24,8 @@ pub struct Brillig {
 
 impl Brillig {
     /// Compiles a function into brillig and store the compilation artifacts
-    pub(crate) fn compile(&mut self, func: &Function) {
-        let obj = convert_ssa_function(func);
+    pub(crate) fn compile(&mut self, func: &Function, enable_debug_trace: bool) {
+        let obj = convert_ssa_function(func, enable_debug_trace);
         self.ssa_function_to_brillig.insert(func.id(), obj);
     }
 
@@ -50,7 +50,7 @@ impl std::ops::Index<FunctionId> for Brillig {
 
 impl Ssa {
     /// Compile to brillig brillig functions and ACIR functions reachable from them
-    pub(crate) fn to_brillig(&self) -> Brillig {
+    pub(crate) fn to_brillig(&self, enable_debug_trace: bool) -> Brillig {
         // Collect all the function ids that are reachable from brillig
         // That means all the functions marked as brillig and ACIR functions called by them
         let mut brillig_reachable_function_ids: HashSet<FunctionId> = HashSet::new();
@@ -96,7 +96,7 @@ impl Ssa {
         let mut brillig = Brillig::default();
         for brillig_function_id in brillig_reachable_function_ids {
             let func = &self.functions[&brillig_function_id];
-            brillig.compile(func);
+            brillig.compile(func, enable_debug_trace);
         }
 
         brillig
diff --git a/crates/noirc_evaluator/src/errors.rs b/crates/noirc_evaluator/src/errors.rs
index 638f1a93fba..6d53668d7cb 100644
--- a/crates/noirc_evaluator/src/errors.rs
+++ b/crates/noirc_evaluator/src/errors.rs
@@ -1,117 +1,104 @@
+//! Noir Evaluator has two types of errors
+//!
+//! [RuntimeError]s that should be displayed to the user
+//!
+//! [InternalError]s that are used for checking internal logics of the SSA
+//!
+//! An Error of the former is a user Error
+//!
+//! An Error of the latter is an error in the implementation of the compiler
+use acvm::FieldElement;
 use noirc_errors::{CustomDiagnostic as Diagnostic, FileDiagnostic, Location};
 use thiserror::Error;
 
-#[derive(Debug)]
-pub struct RuntimeError {
-    pub location: Option<Location>,
-    pub kind: RuntimeErrorKind,
+#[derive(Debug, PartialEq, Eq, Clone, Error)]
+pub enum RuntimeError {
+    // We avoid showing the actual lhs and rhs since most of the time they are just 0
+    // and 1 respectively. This would confuse users if a constraint such as
+    // assert(foo < bar) fails with "failed constraint: 0 = 1."
+    #[error("Failed constraint")]
+    FailedConstraint { lhs: FieldElement, rhs: FieldElement, location: Option<Location> },
+    #[error(transparent)]
+    InternalError(#[from] InternalError),
+    #[error("Index out of bounds, array has size {index:?}, but index was {array_size:?}")]
+    IndexOutOfBounds { index: usize, array_size: usize, location: Option<Location> },
+    #[error("All Witnesses are by default u{num_bits:?} Applying this type does not apply any constraints.\n We also currently do not allow integers of size more than {num_bits:?}, this will be handled by BigIntegers.")]
+    InvalidRangeConstraint { num_bits: u32, location: Option<Location> },
+    #[error("Expected array index to fit into a u64")]
+    TypeConversion { from: String, into: String, location: Option<Location> },
+    #[error("{name:?} is not initialized")]
+    UnInitialized { name: String, location: Option<Location> },
+    #[error("Integer sized {num_bits:?} is over the max supported size of {max_num_bits:?}")]
+    UnsupportedIntegerSize { num_bits: u32, max_num_bits: u32, location: Option<Location> },
 }
 
-impl RuntimeError {
-    // XXX: In some places, we strip the span because we do not want span to
-    // be introduced into the binary op or low level function code, for simplicity.
-    //
-    // It's possible to have it there, but it means we will need to proliferate the code with span
-    //
-    // This does make error reporting, less specific!
-    pub fn remove_span(self) -> RuntimeErrorKind {
-        self.kind
-    }
-
-    pub fn new(kind: RuntimeErrorKind, location: Option<Location>) -> RuntimeError {
-        RuntimeError { location, kind }
-    }
-
-    // Keep one of the two location which is Some, if possible
-    // This is used when we optimize instructions so that we do not lose track of location
-    pub fn merge_location(a: Option<Location>, b: Option<Location>) -> Option<Location> {
-        match (a, b) {
-            (Some(loc), _) | (_, Some(loc)) => Some(loc),
-            (None, None) => None,
-        }
-    }
-}
-
-impl From<RuntimeErrorKind> for RuntimeError {
-    fn from(kind: RuntimeErrorKind) -> RuntimeError {
-        RuntimeError { location: None, kind }
-    }
+#[derive(Debug, PartialEq, Eq, Clone, Error)]
+pub enum InternalError {
+    #[error("ICE: Both expressions should have degree<=1")]
+    DegreeNotReduced { location: Option<Location> },
+    #[error("Try to get element from empty array")]
+    EmptyArray { location: Option<Location> },
+    #[error("ICE: {message:?}")]
+    General { message: String, location: Option<Location> },
+    #[error("ICE: {name:?} missing {arg:?} arg")]
+    MissingArg { name: String, arg: String, location: Option<Location> },
+    #[error("ICE: {name:?} should be a constant")]
+    NotAConstant { name: String, location: Option<Location> },
+    #[error("{name:?} is not implemented yet")]
+    NotImplemented { name: String, location: Option<Location> },
+    #[error("ICE: Undeclared AcirVar")]
+    UndeclaredAcirVar { location: Option<Location> },
+    #[error("ICE: Expected {expected:?}, found {found:?}")]
+    UnExpected { expected: String, found: String, location: Option<Location> },
 }
 
 impl From<RuntimeError> for FileDiagnostic {
-    fn from(err: RuntimeError) -> Self {
-        let file_id = err.location.map(|loc| loc.file).unwrap();
-        FileDiagnostic { file_id, diagnostic: err.into() }
-    }
-}
-
-#[derive(Error, Debug)]
-pub enum RuntimeErrorKind {
-    // Array errors
-    #[error("Out of bounds")]
-    ArrayOutOfBounds { index: u128, bound: u128 },
-
-    #[error("cannot call {func_name} function in non main function")]
-    FunctionNonMainContext { func_name: String },
-
-    // Environment errors
-    #[error("Cannot find Array")]
-    ArrayNotFound { found_type: String, name: String },
-
-    #[error("Unstructured Error")]
-    UnstructuredError { message: String },
-
-    #[error("Spanless")]
-    // This is here due to the fact we don't have full coverage for span
-    Spanless(String),
-
-    #[error("unimplemented")]
-    Unimplemented(String),
-
-    #[error("Unsupported operation error")]
-    UnsupportedOp { op: String, first_type: String, second_type: String },
-}
-
-impl RuntimeErrorKind {
-    pub fn expected_type(expected_type: &'static str, found_type: &str) -> RuntimeErrorKind {
-        RuntimeErrorKind::UnstructuredError {
-            message: format!("Expected a {expected_type}, but found {found_type}"),
+    fn from(error: RuntimeError) -> Self {
+        match error {
+            RuntimeError::InternalError(ref ice_error) => match ice_error {
+                InternalError::DegreeNotReduced { location }
+                | InternalError::EmptyArray { location }
+                | InternalError::General { location, .. }
+                | InternalError::MissingArg { location, .. }
+                | InternalError::NotAConstant { location, .. }
+                | InternalError::NotImplemented { location, .. }
+                | InternalError::UndeclaredAcirVar { location }
+                | InternalError::UnExpected { location, .. } => {
+                    let file_id = location.map(|loc| loc.file).unwrap();
+                    FileDiagnostic { file_id, diagnostic: error.into() }
+                }
+            },
+            RuntimeError::FailedConstraint { location, .. }
+            | RuntimeError::IndexOutOfBounds { location, .. }
+            | RuntimeError::InvalidRangeConstraint { location, .. }
+            | RuntimeError::TypeConversion { location, .. }
+            | RuntimeError::UnInitialized { location, .. }
+            | RuntimeError::UnsupportedIntegerSize { location, .. } => {
+                let file_id = location.map(|loc| loc.file).unwrap();
+                FileDiagnostic { file_id, diagnostic: error.into() }
+            }
         }
     }
 }
 
 impl From<RuntimeError> for Diagnostic {
     fn from(error: RuntimeError) -> Diagnostic {
-        let span =
-            if let Some(loc) = error.location { loc.span } else { noirc_errors::Span::new(0..0) };
-        match &error.kind {
-            RuntimeErrorKind::ArrayOutOfBounds { index, bound } => Diagnostic::simple_error(
-                "index out of bounds".to_string(),
-                format!("out of bounds error, index is {index} but length is {bound}"),
-                span,
+        match error {
+            RuntimeError::InternalError(_) => Diagnostic::simple_error(
+                "Internal Consistency Evaluators Errors: \n 
+                This is likely a bug. Consider Opening an issue at https://github.com/noir-lang/noir/issues".to_owned(),
+                "".to_string(),
+                noirc_errors::Span::new(0..0)
             ),
-            RuntimeErrorKind::ArrayNotFound { found_type, name } => Diagnostic::simple_error(
-                format!("cannot find an array with name {name}"),
-                format!("{found_type} has type"),
-                span,
-            ),
-            RuntimeErrorKind::UnstructuredError { message } => {
-                Diagnostic::simple_error("".to_owned(), message.to_string(), span)
-            }
-            RuntimeErrorKind::UnsupportedOp { op, first_type, second_type } => {
-                Diagnostic::simple_error(
-                    "unsupported operation".to_owned(),
-                    format!("no support for {op} with types {first_type} and {second_type}"),
-                    span,
-                )
+            RuntimeError::FailedConstraint { location, .. }
+            | RuntimeError::IndexOutOfBounds { location, .. }
+            | RuntimeError::InvalidRangeConstraint { location, .. }
+            | RuntimeError::TypeConversion { location, .. }
+            | RuntimeError::UnInitialized { location, .. }
+            | RuntimeError::UnsupportedIntegerSize { location, .. }  => {
+                let span = if let Some(loc) = location { loc.span } else { noirc_errors::Span::new(0..0) };
+                Diagnostic::simple_error("".to_owned(), error.to_string(), span)
             }
-            RuntimeErrorKind::Spanless(message) => Diagnostic::from_message(message),
-            RuntimeErrorKind::Unimplemented(message) => Diagnostic::from_message(message),
-            RuntimeErrorKind::FunctionNonMainContext { func_name } => Diagnostic::simple_error(
-                "cannot call function outside of main".to_owned(),
-                format!("function {func_name} can only be called in main"),
-                span,
-            ),
         }
     }
 }
diff --git a/crates/noirc_evaluator/src/lib.rs b/crates/noirc_evaluator/src/lib.rs
index 420bfc1500e..c7d4f5baed6 100644
--- a/crates/noirc_evaluator/src/lib.rs
+++ b/crates/noirc_evaluator/src/lib.rs
@@ -4,7 +4,6 @@
 #![warn(clippy::semicolon_if_nothing_returned)]
 
 mod errors;
-mod ssa;
 
 // SSA code to create the SSA based IR
 // for functions and execute different optimizations.
@@ -12,354 +11,4 @@ pub mod ssa_refactor;
 
 pub mod brillig;
 
-use acvm::{
-    acir::circuit::{opcodes::Opcode as AcirOpcode, Circuit, PublicInputs},
-    acir::native_types::{Expression, Witness},
-};
-
-use errors::{RuntimeError, RuntimeErrorKind};
-use iter_extended::vecmap;
-use noirc_abi::{Abi, AbiType, AbiVisibility};
-use noirc_errors::debug_info::DebugInfo;
-use noirc_frontend::monomorphization::ast::*;
-use ssa::{node::ObjectType, ssa_gen::IrGenerator};
-use std::collections::{BTreeMap, BTreeSet};
-
-#[derive(Default)]
-pub struct Evaluator {
-    // Why is this not u64?
-    //
-    // At the moment, wasm32 is being used in the default backend
-    // so it is safer to use a u32, at least until clang is changed
-    // to compile wasm64.
-    //
-    // XXX: Barretenberg, reserves the first index to have value 0.
-    // When we increment, we do not use this index at all.
-    // This means that every constraint system at the moment, will either need
-    // to decrease each index by 1, or create a dummy witness.
-    //
-    // We ideally want to not have this and have Barretenberg apply the
-    // following transformation to the witness index : f(i) = i + 1
-    current_witness_index: u32,
-    // This is the number of witnesses indices used when
-    // creating the private/public inputs of the ABI.
-    num_witnesses_abi_len: usize,
-    param_witnesses: BTreeMap<String, Vec<Witness>>,
-    // This is the list of witness indices which are linked to public parameters.
-    // Witnesses below `num_witnesses_abi_len` and not included in this set
-    // correspond to private parameters and must not be made public.
-    public_parameters: BTreeSet<Witness>,
-    // The witness indices for return values are not guaranteed to be contiguous
-    // and increasing as for `public_parameters`. We then use a `Vec` rather
-    // than a `BTreeSet` to preserve this order for the ABI.
-    return_values: Vec<Witness>,
-    // If true, indicates that the resulting ACIR should enforce that all inputs and outputs are
-    // comprised of unique witness indices by having extra constraints if necessary.
-    return_is_distinct: bool,
-
-    opcodes: Vec<AcirOpcode>,
-}
-
-/// Compiles the Program into ACIR and applies optimizations to the arithmetic gates
-// XXX: We return the num_witnesses, but this is the max number of witnesses
-// Some of these could have been removed due to optimizations. We need this number because the
-// Standard format requires the number of witnesses. The max number is also fine.
-// If we had a composer object, we would not need it
-pub fn create_circuit(
-    program: Program,
-    enable_logging: bool,
-    show_output: bool,
-) -> Result<(Circuit, DebugInfo, Abi), RuntimeError> {
-    let mut evaluator = Evaluator::default();
-
-    // First evaluate the main function
-    evaluator.evaluate_main_alt(program.clone(), enable_logging, show_output)?;
-
-    let Evaluator {
-        current_witness_index,
-        param_witnesses,
-        public_parameters,
-        return_values,
-        opcodes,
-        ..
-    } = evaluator;
-    let circuit = Circuit {
-        current_witness_index,
-        opcodes,
-        public_parameters: PublicInputs(public_parameters),
-        return_values: PublicInputs(return_values.iter().copied().collect()),
-    };
-
-    let (parameters, return_type) = program.main_function_signature;
-    let abi = Abi { parameters, param_witnesses, return_type, return_witnesses: return_values };
-
-    Ok((circuit, DebugInfo::default(), abi))
-}
-
-impl Evaluator {
-    // Returns true if the `witness_index` appears in the program's input parameters.
-    fn is_abi_input(&self, witness_index: Witness) -> bool {
-        witness_index.as_usize() <= self.num_witnesses_abi_len
-    }
-
-    // Returns true if the `witness_index`
-    // was created in the ABI as a private input.
-    //
-    // Note: This method is used so that we don't convert private
-    // ABI inputs into public outputs.
-    fn is_private_abi_input(&self, witness_index: Witness) -> bool {
-        // If the `witness_index` is more than the `num_witnesses_abi_len`
-        // then it was created after the ABI was processed and is therefore
-        // an intermediate variable.
-
-        let is_public_input = self.public_parameters.contains(&witness_index);
-
-        self.is_abi_input(witness_index) && !is_public_input
-    }
-
-    // True if the main function return has the `distinct` keyword and this particular witness
-    // index has already occurred elsewhere in the abi's inputs and outputs.
-    fn should_proxy_witness_for_abi_output(&self, witness_index: Witness) -> bool {
-        self.return_is_distinct
-            && (self.is_abi_input(witness_index) || self.return_values.contains(&witness_index))
-    }
-
-    // Creates a new Witness index
-    fn add_witness_to_cs(&mut self) -> Witness {
-        self.current_witness_index += 1;
-        Witness(self.current_witness_index)
-    }
-
-    pub fn current_witness_index(&self) -> u32 {
-        self.current_witness_index
-    }
-
-    pub fn push_opcode(&mut self, gate: AcirOpcode) {
-        self.opcodes.push(gate);
-    }
-
-    /// Compiles the AST into the intermediate format by evaluating the main function
-    pub fn evaluate_main_alt(
-        &mut self,
-        program: Program,
-        enable_logging: bool,
-        show_output: bool,
-    ) -> Result<(), RuntimeError> {
-        self.return_is_distinct =
-            program.return_distinctness == noirc_abi::AbiDistinctness::Distinct;
-
-        let mut ir_gen = IrGenerator::new(program);
-        self.parse_abi_alt(&mut ir_gen);
-
-        // Now call the main function
-        ir_gen.ssa_gen_main()?;
-
-        //Generates ACIR representation:
-        ir_gen.context.ir_to_acir(self, enable_logging, show_output)?;
-        Ok(())
-    }
-
-    // When we are multiplying arithmetic gates by each other, if one gate has too many terms
-    // It is better to create an intermediate variable which links to the gate and then multiply by that intermediate variable
-    // instead
-    pub fn create_intermediate_variable(&mut self, arithmetic_gate: Expression) -> Witness {
-        // Create a unique witness name and add witness to the constraint system
-        let inter_var_witness = self.add_witness_to_cs();
-
-        // Link that witness to the arithmetic gate
-        let constraint = &arithmetic_gate - inter_var_witness;
-        self.opcodes.push(AcirOpcode::Arithmetic(constraint));
-        inter_var_witness
-    }
-
-    fn param_to_var(
-        &mut self,
-        name: &str,
-        def: Definition,
-        param_type: &AbiType,
-        param_visibility: &AbiVisibility,
-        ir_gen: &mut IrGenerator,
-    ) -> Result<(), RuntimeErrorKind> {
-        let witnesses = match param_type {
-            AbiType::Field => {
-                let witness = self.add_witness_to_cs();
-                ir_gen.create_new_variable(
-                    name.to_owned(),
-                    Some(def),
-                    ObjectType::native_field(),
-                    Some(witness),
-                );
-                vec![witness]
-            }
-            AbiType::Array { length, typ } => {
-                let witnesses = self.generate_array_witnesses(length, typ)?;
-
-                ir_gen.abi_array(name, Some(def), typ.as_ref(), *length, &witnesses);
-                witnesses
-            }
-            AbiType::Integer { sign: _, width } => {
-                let witness = self.add_witness_to_cs();
-                ssa::acir_gen::range_constraint(witness, *width, self)?;
-                let obj_type = ir_gen.get_object_type_from_abi(param_type); // Fetch signedness of the integer
-                ir_gen.create_new_variable(name.to_owned(), Some(def), obj_type, Some(witness));
-
-                vec![witness]
-            }
-            AbiType::Boolean => {
-                let witness = self.add_witness_to_cs();
-                ssa::acir_gen::range_constraint(witness, 1, self)?;
-                let obj_type = ObjectType::boolean();
-                ir_gen.create_new_variable(name.to_owned(), Some(def), obj_type, Some(witness));
-
-                vec![witness]
-            }
-            AbiType::Struct { fields } => {
-                let new_fields = vecmap(fields, |(inner_name, value)| {
-                    let new_name = format!("{name}.{inner_name}");
-                    (new_name, value.clone())
-                });
-
-                let mut struct_witnesses: BTreeMap<String, Vec<Witness>> = BTreeMap::new();
-                self.generate_struct_witnesses(&mut struct_witnesses, &new_fields)?;
-
-                ir_gen.abi_struct(name, Some(def), fields, &struct_witnesses);
-
-                // This is a dirty hack and should be removed in future.
-                //
-                // `struct_witnesses` is a flat map where structs are represented by multiple entries
-                // i.e. a struct `foo` with fields `bar` and `baz` is stored under the keys
-                // `foo.bar` and `foo.baz` each holding the witnesses for fields `bar` and `baz` respectively.
-                //
-                // We've then lost the information on ordering of these fields. To reconstruct this we iterate
-                // over `fields` recursively to calculate the proper ordering of this `BTreeMap`s keys.
-                //
-                // Ideally we wouldn't lose this information in the first place.
-                fn get_field_ordering(prefix: String, fields: &[(String, AbiType)]) -> Vec<String> {
-                    fields
-                        .iter()
-                        .flat_map(|(field_name, field_type)| {
-                            let flattened_name = format!("{prefix}.{field_name}");
-                            if let AbiType::Struct { fields } = field_type {
-                                get_field_ordering(flattened_name, fields)
-                            } else {
-                                vec![flattened_name]
-                            }
-                        })
-                        .collect()
-                }
-                let field_ordering = get_field_ordering(name.to_owned(), fields);
-
-                // We concatenate the witness vectors in the order of the struct's fields.
-                // This ensures that struct fields are mapped to the correct witness indices during ABI encoding.
-                field_ordering
-                    .iter()
-                    .flat_map(|field_name| {
-                        struct_witnesses.remove(field_name).unwrap_or_else(|| {
-                            unreachable!(
-                                "Expected a field named '{field_name}' in the struct pattern"
-                            )
-                        })
-                    })
-                    .collect()
-            }
-            AbiType::String { length } => {
-                let typ = AbiType::Integer { sign: noirc_abi::Sign::Unsigned, width: 8 };
-                let witnesses = self.generate_array_witnesses(length, &typ)?;
-                ir_gen.abi_array(name, Some(def), &typ, *length, &witnesses);
-                witnesses
-            }
-        };
-
-        if param_visibility == &AbiVisibility::Public {
-            self.public_parameters.extend(witnesses.clone());
-        }
-        self.param_witnesses.insert(name.to_owned(), witnesses);
-
-        Ok(())
-    }
-
-    fn generate_struct_witnesses(
-        &mut self,
-        struct_witnesses: &mut BTreeMap<String, Vec<Witness>>,
-        fields: &[(String, AbiType)],
-    ) -> Result<(), RuntimeErrorKind> {
-        for (name, typ) in fields {
-            match typ {
-                AbiType::Integer { width, .. } => {
-                    let witness = self.add_witness_to_cs();
-                    struct_witnesses.insert(name.clone(), vec![witness]);
-                    ssa::acir_gen::range_constraint(witness, *width, self)?;
-                }
-                AbiType::Boolean => {
-                    let witness = self.add_witness_to_cs();
-                    struct_witnesses.insert(name.clone(), vec![witness]);
-                    ssa::acir_gen::range_constraint(witness, 1, self)?;
-                }
-                AbiType::Field => {
-                    let witness = self.add_witness_to_cs();
-                    struct_witnesses.insert(name.clone(), vec![witness]);
-                }
-                AbiType::Array { length, typ } => {
-                    let internal_arr_witnesses = self.generate_array_witnesses(length, typ)?;
-                    struct_witnesses.insert(name.clone(), internal_arr_witnesses);
-                }
-                AbiType::Struct { fields, .. } => {
-                    let new_fields = vecmap(fields, |(field_name, typ)| {
-                        let new_name = format!("{name}.{field_name}");
-                        (new_name, typ.clone())
-                    });
-                    self.generate_struct_witnesses(struct_witnesses, &new_fields)?;
-                }
-                AbiType::String { length } => {
-                    let typ = AbiType::Integer { sign: noirc_abi::Sign::Unsigned, width: 8 };
-                    let internal_str_witnesses = self.generate_array_witnesses(length, &typ)?;
-                    struct_witnesses.insert(name.clone(), internal_str_witnesses);
-                }
-            }
-        }
-        Ok(())
-    }
-
-    fn generate_array_witnesses(
-        &mut self,
-        length: &u64,
-        typ: &AbiType,
-    ) -> Result<Vec<Witness>, RuntimeErrorKind> {
-        let mut witnesses = Vec::new();
-        let element_width = match typ {
-            AbiType::Integer { width, .. } => Some(*width),
-            _ => None,
-        };
-        for _ in 0..*length {
-            let witness = self.add_witness_to_cs();
-            witnesses.push(witness);
-            if let Some(ww) = element_width {
-                ssa::acir_gen::range_constraint(witness, ww, self)?;
-            }
-        }
-        Ok(witnesses)
-    }
-
-    /// The ABI is the intermediate representation between Noir and types like Toml
-    /// Noted in the noirc_abi, it is possible to convert Toml -> NoirTypes
-    /// However, this intermediate representation is useful as it allows us to have
-    /// intermediate Types which the core type system does not know about like Strings.
-    fn parse_abi_alt(&mut self, ir_gen: &mut IrGenerator) {
-        let main = ir_gen.program.main_mut();
-        let main_params = std::mem::take(&mut main.parameters);
-        let abi_params = std::mem::take(&mut ir_gen.program.main_function_signature.0);
-
-        assert_eq!(main_params.len(), abi_params.len());
-
-        for ((param_id, _, param_name, _), abi_param) in main_params.iter().zip(abi_params) {
-            assert_eq!(param_name, &abi_param.name);
-            let def = Definition::Local(*param_id);
-            self.param_to_var(param_name, def, &abi_param.typ, &abi_param.visibility, ir_gen)
-                .unwrap();
-        }
-
-        // Store the number of witnesses used to represent the types
-        // in the ABI
-        self.num_witnesses_abi_len = self.current_witness_index as usize;
-    }
-}
+pub use ssa_refactor::create_circuit;
diff --git a/crates/noirc_evaluator/src/ssa/acir_gen.rs b/crates/noirc_evaluator/src/ssa/acir_gen.rs
deleted file mode 100644
index 22b5390e2fa..00000000000
--- a/crates/noirc_evaluator/src/ssa/acir_gen.rs
+++ /dev/null
@@ -1,135 +0,0 @@
-use crate::Evaluator;
-use crate::{
-    errors::RuntimeError,
-    ssa::{
-        block::BasicBlock,
-        builtin,
-        context::SsaContext,
-        node::{Instruction, Operation},
-    },
-};
-use acvm::acir::native_types::{Expression, Witness};
-
-mod operations;
-
-mod internal_var;
-pub(crate) use internal_var::InternalVar;
-mod constraints;
-mod internal_var_cache;
-use internal_var_cache::InternalVarCache;
-// Expose this to the crate as we need to apply range constraints when
-// converting the ABI(main parameters) to Noir types
-pub(crate) use constraints::range_constraint;
-mod acir_mem;
-use acir_mem::AcirMem;
-
-#[derive(Default)]
-pub(crate) struct Acir {
-    memory: AcirMem,
-    var_cache: InternalVarCache,
-}
-
-impl Acir {
-    pub(crate) fn acir_gen(
-        &mut self,
-        evaluator: &mut Evaluator,
-        ctx: &SsaContext,
-        root: &BasicBlock,
-        show_output: bool,
-    ) -> Result<(), RuntimeError> {
-        let mut current_block = Some(root);
-        while let Some(block) = current_block {
-            for iter in &block.instructions {
-                let ins = ctx.instruction(*iter);
-                self.acir_gen_instruction(ins, evaluator, ctx, show_output)?;
-            }
-            //TODO we should rather follow the jumps
-            current_block = block.left.map(|block_id| &ctx[block_id]);
-        }
-        self.memory.acir_gen(evaluator, ctx);
-        Ok(())
-    }
-
-    /// Generate ACIR opcodes based on the given instruction
-    pub(crate) fn acir_gen_instruction(
-        &mut self,
-        ins: &Instruction,
-        evaluator: &mut Evaluator,
-        ctx: &SsaContext,
-        show_output: bool,
-    ) -> Result<(), RuntimeError> {
-        use operations::{
-            binary, condition, constrain, intrinsics, load, not, r#return, store, truncate,
-        };
-
-        let acir_mem = &mut self.memory;
-        let var_cache = &mut self.var_cache;
-
-        let output = match &ins.operation {
-            Operation::Binary(binary) => {
-                binary::evaluate(binary, ins.res_type, self, evaluator, ctx)
-            }
-            Operation::Constrain(value, ..) => {
-                constrain::evaluate(value, var_cache, evaluator, ctx)
-            }
-            Operation::Not(value) => not::evaluate(value, ins.res_type, var_cache, evaluator, ctx),
-            Operation::Cast(value) => {
-                self.var_cache.get_or_compute_internal_var(*value, evaluator, ctx)
-            }
-            Operation::Truncate { value, bit_size, max_bit_size } => {
-                truncate::evaluate(value, *bit_size, *max_bit_size, var_cache, evaluator, ctx)
-            }
-            Operation::Intrinsic(opcode, args) => {
-                let opcode = match opcode {
-                    builtin::Opcode::Println(print_info) => {
-                        builtin::Opcode::Println(builtin::PrintlnInfo {
-                            is_string_output: print_info.is_string_output,
-                            show_output,
-                        })
-                    }
-                    _ => *opcode,
-                };
-                intrinsics::evaluate(args, ins, opcode, self, ctx, evaluator)
-            }
-            Operation::Return(node_ids) => {
-                r#return::evaluate(node_ids, acir_mem, var_cache, evaluator, ctx)?
-            }
-            Operation::Cond { condition, val_true: lhs, val_false: rhs } => {
-                condition::evaluate(*condition, *lhs, *rhs, var_cache, evaluator, ctx)
-            }
-            Operation::Load { array_id, index, location } => Some(load::evaluate(
-                *array_id, *index, acir_mem, var_cache, *location, evaluator, ctx,
-            )?),
-            Operation::Store { .. } => {
-                store::evaluate(&ins.operation, acir_mem, var_cache, evaluator, ctx)?
-            }
-            Operation::Nop => None,
-            i @ Operation::Jne(..)
-            | i @ Operation::Jeq(..)
-            | i @ Operation::Jmp(_)
-            | i @ Operation::Phi { .. }
-            | i @ Operation::Call { .. }
-            | i @ Operation::Result { .. } => {
-                unreachable!("Invalid instruction: {:?}", i);
-            }
-        };
-
-        // If the operation returned an `InternalVar`
-        // then we add it to the `InternalVar` cache
-        if let Some(mut output) = output {
-            output.set_id(ins.id);
-            self.var_cache.update(output);
-        }
-
-        Ok(())
-    }
-}
-
-/// Converts an `Expression` into a `Witness`
-/// - If the `Expression` is a degree-1 univariate polynomial
-/// then this conversion is a simple coercion.
-/// - Otherwise, we create a new `Witness` and set it to be equal to the
-/// `Expression`.
-pub(crate) fn expression_to_witness(expr: Expression, evaluator: &mut Evaluator) -> Witness {
-    expr.to_witness().unwrap_or_else(|| evaluator.create_intermediate_variable(expr))
-}
diff --git a/crates/noirc_evaluator/src/ssa/acir_gen/acir_mem.rs b/crates/noirc_evaluator/src/ssa/acir_gen/acir_mem.rs
deleted file mode 100644
index 3ab030d1fa9..00000000000
--- a/crates/noirc_evaluator/src/ssa/acir_gen/acir_mem.rs
+++ /dev/null
@@ -1,445 +0,0 @@
-use crate::{
-    ssa::{
-        acir_gen::InternalVar,
-        context::SsaContext,
-        mem::{ArrayId, MemArray},
-    },
-    Evaluator,
-};
-use acvm::{
-    acir::{
-        circuit::{
-            directives::Directive,
-            opcodes::{BlockId as AcirBlockId, MemOp, MemoryBlock, Opcode as AcirOpcode},
-        },
-        native_types::{Expression, Witness},
-    },
-    FieldElement,
-};
-
-use iter_extended::vecmap;
-use std::collections::{BTreeMap, HashSet};
-
-use super::{
-    constraints::{self, mul_with_witness, subtract},
-    operations::{self},
-};
-
-type MemAddress = u32;
-
-enum ArrayType {
-    /// Initialization phase: initializing the array with writes on the 0..array.len range
-    /// It contains the HashSet of the initialized indexes and the maximum of these indexes
-    Init(HashSet<MemAddress>, MemAddress),
-    /// Array is only written on, never read
-    WriteOnly,
-    /// Initialization phase and then only read, and optionally a bunch of writes at the end
-    /// The optional usize indicates the position of the ending writes if any: after this position, there are only writes
-    ReadOnly(Option<usize>),
-    /// Reads and writes outside the initialization phase
-    /// The optional usize indicates the position of the ending writes if any: after this position, there are only writes
-    ReadWrite(Option<usize>),
-}
-
-impl Default for ArrayType {
-    fn default() -> Self {
-        ArrayType::Init(HashSet::default(), 0)
-    }
-}
-
-#[derive(Default)]
-struct ArrayHeap {
-    // maps memory address to InternalVar
-    memory_map: BTreeMap<MemAddress, InternalVar>,
-    trace: Vec<MemOp>,
-    // maps memory address to (values,operation) that must be committed to the trace
-    staged: BTreeMap<MemAddress, (Expression, Expression)>,
-    typ: ArrayType,
-}
-
-impl ArrayHeap {
-    fn commit_staged(&mut self) {
-        // generates the memory operations to be added to the trace
-        let trace = vecmap(&self.staged, |(idx, (value, op))| MemOp {
-            operation: op.clone(),
-            value: value.clone(),
-            index: Expression::from_field(FieldElement::from(*idx as i128)),
-        });
-        // Add to trace
-        for item in trace {
-            self.push(item);
-        }
-        self.staged.clear();
-    }
-
-    fn push(&mut self, item: MemOp) {
-        let is_load = item.operation == Expression::zero();
-        let index_const = item.index.to_const();
-        self.typ = match &self.typ {
-            ArrayType::Init(init_idx, len) => match (is_load, index_const) {
-                (false, Some(idx)) => {
-                    let idx: MemAddress = idx.to_u128().try_into().unwrap();
-                    let mut init_idx2 = init_idx.clone();
-                    init_idx2.insert(idx);
-                    let len2 = std::cmp::max(idx + 1, *len);
-                    ArrayType::Init(init_idx2, len2)
-                }
-                (false, None) => ArrayType::WriteOnly,
-                (true, _) => {
-                    if *len as usize == init_idx.len() {
-                        ArrayType::ReadOnly(None)
-                    } else {
-                        ArrayType::ReadWrite(None)
-                    }
-                }
-            },
-            ArrayType::WriteOnly => {
-                if is_load {
-                    ArrayType::ReadWrite(None)
-                } else {
-                    ArrayType::WriteOnly
-                }
-            }
-            ArrayType::ReadOnly(last) => match (is_load, last) {
-                (true, Some(_)) => ArrayType::ReadWrite(None),
-                (true, None) => ArrayType::ReadOnly(None),
-                (false, None) => ArrayType::ReadOnly(Some(self.trace.len())),
-                (false, Some(_)) => ArrayType::ReadOnly(*last),
-            },
-            ArrayType::ReadWrite(last) => match (is_load, last) {
-                (true, _) => ArrayType::ReadWrite(None),
-                (false, None) => ArrayType::ReadWrite(Some(self.trace.len())),
-                (false, Some(_)) => ArrayType::ReadWrite(*last),
-            },
-        };
-        self.trace.push(item);
-    }
-
-    fn stage(&mut self, index: MemAddress, value: Expression, op: Expression) {
-        self.staged.insert(index, (value, op));
-    }
-
-    /// This helper function transforms an expression into a single witness representing the expression
-    fn normalize_expression(expr: &Expression, evaluator: &mut Evaluator) -> Expression {
-        expr.to_witness()
-            .unwrap_or_else(|| evaluator.create_intermediate_variable(expr.clone()))
-            .into()
-    }
-
-    /// Decide which opcode to use, depending on the backend support
-    fn acir_gen(
-        &self,
-        evaluator: &mut Evaluator,
-        array_id: ArrayId,
-        array_len: u32,
-        is_opcode_supported: OpcodeSupported,
-    ) {
-        //sanity check
-        if array_len == 0 || self.trace.is_empty() {
-            return;
-        }
-        let dummy = MemoryBlock { id: AcirBlockId(0), len: 0, trace: Vec::new() };
-        let trace_len = match self.typ {
-            ArrayType::ReadOnly(Some(len)) | ArrayType::ReadWrite(Some(len)) => len,
-            _ => self.trace.len(),
-        };
-
-        if is_opcode_supported(&AcirOpcode::ROM(dummy.clone())) {
-            // If the backend support ROM and the array is read-only, we generate the ROM opcode
-            if matches!(self.typ, ArrayType::ReadOnly(_)) {
-                self.add_rom_opcode(evaluator, array_id, array_len, trace_len);
-                return;
-            }
-        }
-        if is_opcode_supported(&AcirOpcode::Block(dummy.clone())) {
-            self.add_block_opcode(evaluator, array_id, array_len);
-        } else if is_opcode_supported(&AcirOpcode::RAM(dummy)) {
-            self.add_ram_opcode(evaluator, array_id, array_len, trace_len);
-        } else {
-            self.generate_permutation_constraints(evaluator, array_id, array_len);
-        }
-    }
-
-    fn add_block_opcode(&self, evaluator: &mut Evaluator, array_id: ArrayId, array_len: u32) {
-        evaluator.opcodes.push(AcirOpcode::Block(MemoryBlock {
-            id: AcirBlockId(array_id.as_u32()),
-            len: array_len,
-            trace: self.trace.clone(),
-        }));
-    }
-
-    fn add_rom_opcode(
-        &self,
-        evaluator: &mut Evaluator,
-        array_id: ArrayId,
-        array_len: u32,
-        trace_len: usize,
-    ) {
-        let mut trace = Vec::with_capacity(trace_len);
-        for op in self.trace.iter().take(trace_len) {
-            let index = Self::normalize_expression(&op.index, evaluator);
-            let value = Self::normalize_expression(&op.value, evaluator);
-            trace.push(MemOp { operation: op.operation.clone(), index, value });
-        }
-        evaluator.opcodes.push(AcirOpcode::ROM(MemoryBlock {
-            id: AcirBlockId(array_id.as_u32()),
-            len: array_len,
-            trace,
-        }));
-    }
-
-    fn add_ram_opcode(
-        &self,
-        evaluator: &mut Evaluator,
-        array_id: ArrayId,
-        array_len: u32,
-        trace_len: usize,
-    ) {
-        let mut trace = Vec::with_capacity(trace_len);
-        for op in self.trace.iter().take(trace_len) {
-            let index = Self::normalize_expression(&op.index, evaluator);
-            let value = Self::normalize_expression(&op.value, evaluator);
-            trace.push(MemOp { operation: op.operation.clone(), index, value });
-        }
-        evaluator.opcodes.push(AcirOpcode::RAM(MemoryBlock {
-            id: AcirBlockId(array_id.as_u32()),
-            len: array_len,
-            trace,
-        }));
-    }
-
-    fn generate_outputs(
-        inputs: Vec<Expression>,
-        bits: &mut Vec<Witness>,
-        evaluator: &mut Evaluator,
-    ) -> Vec<Expression> {
-        let outputs = vecmap(0..inputs.len(), |_| evaluator.add_witness_to_cs().into());
-        if bits.is_empty() {
-            *bits = operations::sort::evaluate_permutation(&inputs, &outputs, evaluator);
-        } else {
-            operations::sort::evaluate_permutation_with_witness(&inputs, &outputs, bits, evaluator);
-        }
-        outputs
-    }
-    fn generate_permutation_constraints(
-        &self,
-        evaluator: &mut Evaluator,
-        array_id: ArrayId,
-        array_len: u32,
-    ) {
-        let (len, read_write) = match self.typ {
-            ArrayType::Init(_, _) | ArrayType::WriteOnly => (0, true),
-            ArrayType::ReadOnly(last) => (last.unwrap_or(self.trace.len()), false),
-            ArrayType::ReadWrite(last) => (last.unwrap_or(self.trace.len()), true),
-        };
-        if len == 0 {
-            return;
-        }
-        self.add_block_opcode(evaluator, array_id, array_len);
-        let len_bits = AcirMem::bits(len);
-        // permutations
-        let mut in_counter = Vec::new();
-        let mut in_index = Vec::new();
-        let mut in_value = Vec::new();
-        let mut in_op = Vec::new();
-
-        let mut tuple_expressions = Vec::new();
-        for (counter, item) in self.trace.iter().take(len).enumerate() {
-            let counter_expr = Expression::from_field(FieldElement::from(counter as i128));
-            in_counter.push(counter_expr.clone());
-            in_index.push(item.index.clone());
-            in_value.push(item.value.clone());
-            if read_write {
-                in_op.push(item.operation.clone());
-            }
-            tuple_expressions.push(vec![item.index.clone(), counter_expr.clone()]);
-        }
-        let mut bit_counter = Vec::new();
-        let out_counter = Self::generate_outputs(in_counter, &mut bit_counter, evaluator);
-        let out_index = Self::generate_outputs(in_index, &mut bit_counter, evaluator);
-        let out_value = Self::generate_outputs(in_value, &mut bit_counter, evaluator);
-        let out_op = if read_write {
-            Self::generate_outputs(in_op, &mut bit_counter, evaluator)
-        } else {
-            Vec::new()
-        };
-        // sort directive
-        evaluator.opcodes.push(AcirOpcode::Directive(Directive::PermutationSort {
-            inputs: tuple_expressions,
-            tuple: 2,
-            bits: bit_counter,
-            sort_by: vec![0, 1],
-        }));
-        if read_write {
-            let init = subtract(&out_op[0], FieldElement::one(), &Expression::one());
-            evaluator.opcodes.push(AcirOpcode::Arithmetic(init));
-        }
-        for i in 0..len - 1 {
-            // index sort
-            let index_sub = subtract(&out_index[i + 1], FieldElement::one(), &out_index[i]);
-            let primary_order = constraints::boolean_expr(&index_sub, evaluator);
-            evaluator.opcodes.push(AcirOpcode::Arithmetic(primary_order));
-            // counter sort
-            let cmp = constraints::evaluate_cmp(
-                &out_counter[i],
-                &out_counter[i + 1],
-                len_bits,
-                false,
-                evaluator,
-            );
-            let sub_cmp = subtract(&cmp, FieldElement::one(), &Expression::one());
-            let secondary_order = subtract(
-                &mul_with_witness(evaluator, &index_sub, &sub_cmp),
-                FieldElement::one(),
-                &sub_cmp,
-            );
-            evaluator.opcodes.push(AcirOpcode::Arithmetic(secondary_order));
-            // consistency checks
-            let sub2 = subtract(&out_value[i + 1], FieldElement::one(), &out_value[i]);
-            let load_on_same_adr = if read_write {
-                let sub1 = subtract(&Expression::one(), FieldElement::one(), &out_op[i + 1]);
-                let store_on_new_adr = mul_with_witness(evaluator, &index_sub, &sub1);
-                evaluator.opcodes.push(AcirOpcode::Arithmetic(store_on_new_adr));
-                mul_with_witness(evaluator, &sub1, &sub2)
-            } else {
-                subtract(
-                    &mul_with_witness(evaluator, &index_sub, &sub2),
-                    FieldElement::one(),
-                    &sub2,
-                )
-            };
-            evaluator.opcodes.push(AcirOpcode::Arithmetic(load_on_same_adr));
-        }
-    }
-}
-
-/// Handle virtual memory access
-#[derive(Default)]
-pub(crate) struct AcirMem {
-    virtual_memory: BTreeMap<ArrayId, ArrayHeap>,
-}
-
-impl AcirMem {
-    // Returns the memory_map for the array
-    fn array_map_mut(&mut self, array_id: ArrayId) -> &mut BTreeMap<MemAddress, InternalVar> {
-        &mut self.virtual_memory.entry(array_id).or_default().memory_map
-    }
-
-    // returns the memory trace for the array
-    fn array_heap_mut(&mut self, array_id: ArrayId) -> &mut ArrayHeap {
-        let e = self.virtual_memory.entry(array_id);
-        e.or_default()
-    }
-
-    // Write the value to the array's VM at the specified index
-    pub(super) fn insert(&mut self, array_id: ArrayId, index: MemAddress, value: InternalVar) {
-        let heap = self.virtual_memory.entry(array_id).or_default();
-        let value_expr = value.to_expression();
-        heap.memory_map.insert(index, value);
-        heap.stage(index, value_expr, Expression::one());
-    }
-
-    //Map the outputs into the array
-    pub(super) fn map_array(&mut self, a: ArrayId, outputs: &[Witness], ctx: &SsaContext) {
-        let array = &ctx.mem[a];
-        for i in 0..array.len {
-            let var = if i < outputs.len() as u32 {
-                InternalVar::from(outputs[i as usize])
-            } else {
-                InternalVar::zero_expr()
-            };
-            self.array_map_mut(array.id).insert(i, var);
-        }
-    }
-
-    //Ensure we do not optimise writes when the array is returned
-    pub(crate) fn return_array(&mut self, array_id: ArrayId) {
-        let heap = self.array_heap_mut(array_id);
-        match heap.typ {
-            ArrayType::ReadOnly(_) | ArrayType::ReadWrite(_) => {
-                heap.typ = ArrayType::ReadWrite(None);
-            }
-            _ => (),
-        }
-    }
-
-    // Load array values into InternalVars
-    pub(super) fn load_array(
-        &mut self,
-        array: &MemArray,
-        evaluator: &mut Evaluator,
-    ) -> Vec<InternalVar> {
-        vecmap(0..array.len, |offset| {
-            operations::load::evaluate_with(
-                array,
-                &InternalVar::from(FieldElement::from(offset as i128)),
-                self,
-                None,
-                evaluator,
-            )
-            .expect("infallible: array out of bounds error")
-        })
-    }
-
-    // Number of bits required to store the input
-    fn bits(mut t: usize) -> u32 {
-        let mut r = 0;
-        while t != 0 {
-            t >>= 1;
-            r += 1;
-        }
-        r
-    }
-
-    // Loads the associated `InternalVar` for the element
-    // in the `array` at the given `offset`.
-    //
-    // We check if the address of the array element
-    // is in the memory_map.
-    //
-    //
-    // Returns `None` if not found
-    pub(super) fn load_array_element_constant_index(
-        &mut self,
-        array: &MemArray,
-        offset: MemAddress,
-    ) -> Option<InternalVar> {
-        // Check the memory_map to see if the element is there
-        self.array_map_mut(array.id).get(&offset).cloned()
-    }
-
-    // Apply staged stores to the memory trace
-    fn commit(&mut self, array_id: &ArrayId, clear: bool) {
-        let e = self.virtual_memory.entry(*array_id).or_default();
-        e.commit_staged();
-        if clear {
-            e.memory_map.clear();
-        }
-    }
-    pub(crate) fn add_to_trace(
-        &mut self,
-        array_id: &ArrayId,
-        index: Expression,
-        value: Expression,
-        op: Expression,
-    ) {
-        self.commit(array_id, op != Expression::zero());
-        let item = MemOp { operation: op, value, index };
-        self.array_heap_mut(*array_id).push(item);
-    }
-    pub(crate) fn acir_gen(&self, evaluator: &mut Evaluator, ctx: &SsaContext) {
-        //Temporary hack - We hardcode Barretenberg support here.
-        //TODO: to remove once opcodesupported usage is clarified
-        let is_opcode_supported: OpcodeSupported = |o| match o {
-            AcirOpcode::Block(_) => false,
-            AcirOpcode::ROM(_) | AcirOpcode::RAM(_) => true,
-            _ => unreachable!(),
-        };
-        for mem in &self.virtual_memory {
-            let array = &ctx.mem[*mem.0];
-            mem.1.acir_gen(evaluator, array.id, array.len, is_opcode_supported);
-        }
-    }
-}
-
-type OpcodeSupported = fn(&AcirOpcode) -> bool;
diff --git a/crates/noirc_evaluator/src/ssa/acir_gen/constraints.rs b/crates/noirc_evaluator/src/ssa/acir_gen/constraints.rs
deleted file mode 100644
index 0900c34ce36..00000000000
--- a/crates/noirc_evaluator/src/ssa/acir_gen/constraints.rs
+++ /dev/null
@@ -1,726 +0,0 @@
-use crate::{
-    errors::RuntimeErrorKind,
-    ssa::{acir_gen::expression_to_witness, builtin::Endian},
-    Evaluator,
-};
-use acvm::{
-    acir::{
-        circuit::{
-            directives::{Directive, QuotientDirective},
-            opcodes::{BlackBoxFuncCall, FunctionInput, Opcode as AcirOpcode},
-        },
-        native_types::{Expression, Witness},
-    },
-    FieldElement,
-};
-use num_bigint::BigUint;
-use num_traits::One;
-use std::{
-    cmp::Ordering,
-    ops::{Mul, Neg},
-};
-
-// Code in this file, will generate constraints without
-// using only the Evaluator and ACIR Expression types
-
-pub(crate) fn mul_with_witness(
-    evaluator: &mut Evaluator,
-    a: &Expression,
-    b: &Expression,
-) -> Expression {
-    let a_arith;
-    let a_arith = if !a.mul_terms.is_empty() && !b.is_const() {
-        let a_witness = evaluator.create_intermediate_variable(a.clone());
-        a_arith = Expression::from(a_witness);
-        &a_arith
-    } else {
-        a
-    };
-    let b_arith;
-    let b_arith = if !b.mul_terms.is_empty() && !a.is_const() {
-        if a == b {
-            a_arith
-        } else {
-            let b_witness = evaluator.create_intermediate_variable(b.clone());
-            b_arith = Expression::from(b_witness);
-            &b_arith
-        }
-    } else {
-        b
-    };
-    mul(a_arith, b_arith)
-}
-
-//a*b
-pub(crate) fn mul(a: &Expression, b: &Expression) -> Expression {
-    if a.is_const() {
-        return b * a.q_c;
-    } else if b.is_const() {
-        return a * b.q_c;
-    } else if !(a.is_linear() && b.is_linear()) {
-        unreachable!("Can only multiply linear terms");
-    }
-
-    let mut output = Expression::from_field(a.q_c * b.q_c);
-
-    //TODO to optimize...
-    for lc in &a.linear_combinations {
-        let single = single_mul(lc.1, b);
-        output = add(&output, lc.0, &single);
-    }
-
-    //linear terms
-    let mut i1 = 0; //a
-    let mut i2 = 0; //b
-    while i1 < a.linear_combinations.len() && i2 < b.linear_combinations.len() {
-        let coeff_a = b.q_c * a.linear_combinations[i1].0;
-        let coeff_b = a.q_c * b.linear_combinations[i2].0;
-        match a.linear_combinations[i1].1.cmp(&b.linear_combinations[i2].1) {
-            Ordering::Greater => {
-                if coeff_b != FieldElement::zero() {
-                    output.linear_combinations.push((coeff_b, b.linear_combinations[i2].1));
-                }
-                i2 += 1;
-            }
-            Ordering::Less => {
-                if coeff_a != FieldElement::zero() {
-                    output.linear_combinations.push((coeff_a, a.linear_combinations[i1].1));
-                }
-                i1 += 1;
-            }
-            Ordering::Equal => {
-                if coeff_a + coeff_b != FieldElement::zero() {
-                    output
-                        .linear_combinations
-                        .push((coeff_a + coeff_b, a.linear_combinations[i1].1));
-                }
-
-                i1 += 1;
-                i2 += 1;
-            }
-        }
-    }
-    while i1 < a.linear_combinations.len() {
-        let coeff_a = b.q_c * a.linear_combinations[i1].0;
-        output.linear_combinations.push((coeff_a, a.linear_combinations[i1].1));
-        i1 += 1;
-    }
-    while i2 < b.linear_combinations.len() {
-        let coeff_b = a.q_c * b.linear_combinations[i2].0;
-        output.linear_combinations.push((coeff_b, b.linear_combinations[i2].1));
-        i2 += 1;
-    }
-
-    output
-}
-
-// returns a - k*b
-pub(crate) fn subtract(a: &Expression, k: FieldElement, b: &Expression) -> Expression {
-    add(a, k.neg(), b)
-}
-
-// returns a + k*b
-// TODO: possibly rename to add_mul
-// TODO also check why we are doing all of this complicated logic with i1 and i2
-// TODO in either case, we can put this in ACIR, if its useful
-pub(crate) fn add(a: &Expression, k: FieldElement, b: &Expression) -> Expression {
-    if a.is_const() {
-        return (b * k) + a.q_c;
-    } else if b.is_const() {
-        return a.clone() + (k * b.q_c);
-    }
-
-    let mut output = Expression::from_field(a.q_c + k * b.q_c);
-
-    //linear combinations
-    let mut i1 = 0; //a
-    let mut i2 = 0; //b
-    while i1 < a.linear_combinations.len() && i2 < b.linear_combinations.len() {
-        match a.linear_combinations[i1].1.cmp(&b.linear_combinations[i2].1) {
-            Ordering::Greater => {
-                let coeff = b.linear_combinations[i2].0 * k;
-                if coeff != FieldElement::zero() {
-                    output.linear_combinations.push((coeff, b.linear_combinations[i2].1));
-                }
-                i2 += 1;
-            }
-            Ordering::Less => {
-                output.linear_combinations.push(a.linear_combinations[i1]);
-                i1 += 1;
-            }
-            Ordering::Equal => {
-                let coeff = a.linear_combinations[i1].0 + b.linear_combinations[i2].0 * k;
-                if coeff != FieldElement::zero() {
-                    output.linear_combinations.push((coeff, a.linear_combinations[i1].1));
-                }
-                i2 += 1;
-                i1 += 1;
-            }
-        }
-    }
-    while i1 < a.linear_combinations.len() {
-        output.linear_combinations.push(a.linear_combinations[i1]);
-        i1 += 1;
-    }
-    while i2 < b.linear_combinations.len() {
-        let coeff = b.linear_combinations[i2].0 * k;
-        if coeff != FieldElement::zero() {
-            output.linear_combinations.push((coeff, b.linear_combinations[i2].1));
-        }
-        i2 += 1;
-    }
-
-    //mul terms
-
-    i1 = 0; //a
-    i2 = 0; //b
-
-    while i1 < a.mul_terms.len() && i2 < b.mul_terms.len() {
-        match (a.mul_terms[i1].1, a.mul_terms[i1].2).cmp(&(b.mul_terms[i2].1, b.mul_terms[i2].2)) {
-            Ordering::Greater => {
-                let coeff = b.mul_terms[i2].0 * k;
-                if coeff != FieldElement::zero() {
-                    output.mul_terms.push((coeff, b.mul_terms[i2].1, b.mul_terms[i2].2));
-                }
-                i2 += 1;
-            }
-            Ordering::Less => {
-                output.mul_terms.push(a.mul_terms[i1]);
-                i1 += 1;
-            }
-            Ordering::Equal => {
-                let coeff = a.mul_terms[i1].0 + b.mul_terms[i2].0 * k;
-                if coeff != FieldElement::zero() {
-                    output.mul_terms.push((coeff, a.mul_terms[i1].1, a.mul_terms[i1].2));
-                }
-                i2 += 1;
-                i1 += 1;
-            }
-        }
-    }
-    while i1 < a.mul_terms.len() {
-        output.mul_terms.push(a.mul_terms[i1]);
-        i1 += 1;
-    }
-
-    while i2 < b.mul_terms.len() {
-        let coeff = b.mul_terms[i2].0 * k;
-        if coeff != FieldElement::zero() {
-            output.mul_terms.push((coeff, b.mul_terms[i2].1, b.mul_terms[i2].2));
-        }
-        i2 += 1;
-    }
-
-    output
-}
-
-// returns w*b.linear_combinations
-pub(crate) fn single_mul(w: Witness, b: &Expression) -> Expression {
-    let mut output = Expression::default();
-    let mut i1 = 0;
-    while i1 < b.linear_combinations.len() {
-        if (w, b.linear_combinations[i1].1) < (b.linear_combinations[i1].1, w) {
-            output.mul_terms.push((b.linear_combinations[i1].0, w, b.linear_combinations[i1].1));
-        } else {
-            output.mul_terms.push((b.linear_combinations[i1].0, b.linear_combinations[i1].1, w));
-        }
-        i1 += 1;
-    }
-    output
-}
-
-pub(crate) fn boolean(witness: Witness) -> Expression {
-    Expression {
-        mul_terms: vec![(FieldElement::one(), witness, witness)],
-        linear_combinations: vec![(-FieldElement::one(), witness)],
-        q_c: FieldElement::zero(),
-    }
-}
-
-pub(crate) fn boolean_expr(expr: &Expression, evaluator: &mut Evaluator) -> Expression {
-    subtract(&mul_with_witness(evaluator, expr, expr), FieldElement::one(), expr)
-}
-
-//constrain witness a to be num_bits-size integer, i.e between 0 and 2^num_bits-1
-pub(crate) fn range_constraint(
-    witness: Witness,
-    num_bits: u32,
-    evaluator: &mut Evaluator,
-) -> Result<(), RuntimeErrorKind> {
-    if num_bits == 1 {
-        // Add a bool gate
-        let bool_constraint = boolean(witness);
-        evaluator.push_opcode(AcirOpcode::Arithmetic(bool_constraint));
-    } else if num_bits == FieldElement::max_num_bits() {
-        // Don't apply any constraints if the range is for the maximum number of bits
-        let message = format!(
-            "All Witnesses are by default u{}. Applying this type does not apply any constraints.",
-            FieldElement::max_num_bits()
-        );
-        return Err(RuntimeErrorKind::UnstructuredError { message });
-    } else if num_bits % 2 == 1 {
-        // Note if the number of bits is odd, then Barretenberg will panic
-        // new witnesses; r is constrained to num_bits-1 and b is 1 bit
-        let r_witness = evaluator.add_witness_to_cs();
-        let b_witness = evaluator.add_witness_to_cs();
-        let exp_big = BigUint::from(2_u128).pow(num_bits - 1);
-        let exp = FieldElement::from_be_bytes_reduce(&exp_big.to_bytes_be());
-        evaluator.push_opcode(AcirOpcode::Directive(Directive::Quotient(QuotientDirective {
-            a: Expression::from(witness),
-            b: Expression::from_field(exp),
-            q: b_witness,
-            r: r_witness,
-            predicate: None,
-        })));
-
-        try_range_constraint(r_witness, num_bits - 1, evaluator);
-        try_range_constraint(b_witness, 1, evaluator);
-
-        //Add the constraint a = r + 2^N*b
-        let mut f = FieldElement::from(2_i128);
-        f = f.pow(&FieldElement::from((num_bits - 1) as i128));
-        let res = add(&r_witness.into(), f, &b_witness.into());
-        let my_constraint = add(&res, -FieldElement::one(), &witness.into());
-        evaluator.push_opcode(AcirOpcode::Arithmetic(my_constraint));
-    } else {
-        let gate = AcirOpcode::BlackBoxFuncCall(BlackBoxFuncCall::RANGE {
-            input: FunctionInput { witness, num_bits },
-        });
-        evaluator.push_opcode(gate);
-    }
-
-    Ok(())
-}
-
-// returns a witness of a>=b
-pub(crate) fn bound_check(
-    a: &Expression,
-    b: &Expression,
-    max_bits: u32,
-    evaluator: &mut Evaluator,
-) -> Witness {
-    assert!(max_bits + 1 < FieldElement::max_num_bits()); //n.b what we really need is 2^{max_bits+1}<p
-    let mut sub = subtract(a, FieldElement::one(), b);
-    let two = FieldElement::from(2_i128);
-    let two_s = two.pow(&FieldElement::from(max_bits as i128));
-    sub.q_c += two_s;
-    let q_witness = evaluator.add_witness_to_cs();
-    let r_witness = evaluator.add_witness_to_cs();
-    //2^s+a-b=q*2^s +r
-    let expr = add(&r_witness.into(), two_s, &q_witness.into());
-    evaluator.push_opcode(AcirOpcode::Arithmetic(subtract(&sub, FieldElement::one(), &expr)));
-    evaluator.push_opcode(AcirOpcode::Directive(Directive::Quotient(QuotientDirective {
-        a: sub,
-        b: Expression::from_field(two_s),
-        q: q_witness,
-        r: r_witness,
-        predicate: None,
-    })));
-    try_range_constraint(r_witness, max_bits, evaluator);
-    evaluator.push_opcode(AcirOpcode::Arithmetic(boolean(q_witness)));
-    q_witness
-}
-
-// Generate constraints that are satisfied iff
-// a < b , when offset is 1, or
-// a <= b, when offset is 0
-// bits is the bit size of a and b (or an upper bound of the bit size)
-///////////////
-// a<=b is done by constraining b-a to a bit size of 'bits':
-// if a<=b, 0 <= b-a <= b < 2^bits
-// if a>b, b-a = p+b-a > p-2^bits >= 2^bits  (if log(p) >= bits + 1)
-// n.b: we do NOT check here that a and b are indeed 'bits' size
-// a < b <=> a+1<=b
-pub(crate) fn bound_constraint_with_offset(
-    a: &Expression,
-    b: &Expression,
-    offset: &Expression,
-    bits: u32,
-    evaluator: &mut Evaluator,
-) {
-    assert!(
-        bits < FieldElement::max_num_bits(),
-        "range check with bit size of the prime field is not implemented yet"
-    );
-
-    let mut aof = add(a, FieldElement::one(), offset);
-
-    if b.is_const() && b.q_c.fits_in_u128() {
-        let f = if *offset == Expression::one() {
-            aof = a.clone();
-            assert!(b.q_c.to_u128() >= 1);
-            b.q_c.to_u128() - 1
-        } else {
-            b.q_c.to_u128()
-        };
-
-        if f < 3 {
-            match f {
-                0 => evaluator.push_opcode(AcirOpcode::Arithmetic(aof)),
-                1 => {
-                    let expr = boolean_expr(&aof, evaluator);
-                    evaluator.push_opcode(AcirOpcode::Arithmetic(expr));
-                }
-                2 => {
-                    let y = expression_to_witness(boolean_expr(&aof, evaluator), evaluator);
-                    let two = FieldElement::from(2_i128);
-                    let y_expr = y.into();
-                    let eee = subtract(&mul_with_witness(evaluator, &aof, &y_expr), two, &y_expr);
-                    evaluator.push_opcode(AcirOpcode::Arithmetic(eee));
-                }
-                _ => unreachable!(),
-            }
-            return;
-        }
-        let bit_size = bit_size_u128(f);
-        if bit_size < 128 {
-            let r = (1_u128 << bit_size) - f - 1;
-            assert!(bits + bit_size < FieldElement::max_num_bits()); //we need to ensure a+r does not overflow
-            let aor = add(&aof, FieldElement::from(r), &Expression::one());
-            let witness = expression_to_witness(aor, evaluator);
-            try_range_constraint(witness, bit_size, evaluator);
-            return;
-        }
-    }
-
-    let sub_expression = subtract(b, FieldElement::one(), &aof); //b-(a+offset)
-    let w = expression_to_witness(sub_expression, evaluator);
-    try_range_constraint(w, bits, evaluator);
-}
-
-pub(crate) fn try_range_constraint(w: Witness, bits: u32, evaluator: &mut Evaluator) {
-    if let Err(err) = range_constraint(w, bits, evaluator) {
-        eprintln!("{err}");
-    }
-}
-
-//decompose lhs onto radix-base with limb_size limbs
-pub(crate) fn to_radix_base(
-    lhs: &Expression,
-    radix: u32,
-    limb_size: u32,
-    endianness: Endian,
-    evaluator: &mut Evaluator,
-) -> Vec<Witness> {
-    // ensure there is no overflow
-    let rad = BigUint::from(radix);
-    let max = rad.pow(limb_size) - BigUint::one();
-
-    if max < FieldElement::modulus() {
-        let (mut result, bytes) = to_radix_little(radix, limb_size, evaluator);
-
-        evaluator.push_opcode(AcirOpcode::Directive(Directive::ToLeRadix {
-            a: lhs.clone(),
-            b: result.clone(),
-            radix,
-        }));
-
-        if endianness == Endian::Big {
-            result.reverse();
-        }
-
-        evaluator.push_opcode(AcirOpcode::Arithmetic(subtract(lhs, FieldElement::one(), &bytes)));
-        result
-    } else {
-        let min = rad.pow(limb_size - 1) - BigUint::one();
-        assert!(min < FieldElement::modulus());
-
-        let max_bits = max.bits() as u32;
-        let a = evaluate_constant_modulo(lhs, radix, max_bits, evaluator)
-            .to_witness()
-            .expect("Constant expressions should already be simplified");
-        let y = subtract(lhs, FieldElement::one(), &Expression::from(a));
-        let radix_f = FieldElement::from(radix as i128);
-        let y = Expression::default().add_mul(FieldElement::one() / radix_f, &y);
-        let mut b = to_radix_base(&y, radix, limb_size - 1, endianness, evaluator);
-        match endianness {
-            Endian::Little => b.insert(0, a),
-            Endian::Big => b.push(a),
-        }
-
-        b
-    }
-}
-
-//Decomposition into b-base: \sum ai b^i, where 0<=ai<b
-// radix: the base, (it is a constant, not a witness)
-// num_limbs: the number of elements in the decomposition
-// output: (the elements of the decomposition as witness, the sum expression)
-pub(crate) fn to_radix_little(
-    radix: u32,
-    num_limbs: u32,
-    evaluator: &mut Evaluator,
-) -> (Vec<Witness>, Expression) {
-    let mut digits = Expression::default();
-    let mut radix_pow = FieldElement::one();
-
-    let shift = FieldElement::from(radix as i128);
-    let mut result = Vec::new();
-    let bit_size = bit_size_u32(radix);
-    for _ in 0..num_limbs {
-        let limb_witness = evaluator.add_witness_to_cs();
-        result.push(limb_witness);
-        let limb_expr = limb_witness.into();
-        digits = add(&digits, radix_pow, &limb_expr);
-        radix_pow = radix_pow.mul(shift);
-
-        if 1_u128 << (bit_size - 1) != radix as u128 {
-            try_range_constraint(limb_witness, bit_size, evaluator);
-        }
-        bound_constraint_with_offset(
-            &limb_witness.into(),
-            &Expression::from_field(shift),
-            &Expression::one(),
-            bit_size,
-            evaluator,
-        );
-    }
-    (result, digits)
-}
-
-//Returns 1 if lhs < rhs
-pub(crate) fn evaluate_cmp(
-    lhs: &Expression,
-    rhs: &Expression,
-    bit_size: u32,
-    signed: bool,
-    evaluator: &mut Evaluator,
-) -> Expression {
-    if signed {
-        //TODO use range_constraints instead of bit decomposition, like in the unsigned case
-        let mut sub_expr = subtract(lhs, FieldElement::one(), rhs);
-        let two_pow = BigUint::one() << (bit_size + 1);
-        sub_expr.q_c += FieldElement::from_be_bytes_reduce(&two_pow.to_bytes_be());
-        let bits = to_radix_base(&sub_expr, 2, bit_size + 2, Endian::Little, evaluator);
-        bits[(bit_size - 1) as usize].into()
-    } else {
-        let is_greater = bound_check(lhs, rhs, bit_size, evaluator);
-        subtract(&Expression::one(), FieldElement::one(), &is_greater.into())
-    }
-}
-
-//truncate lhs (a number whose value requires max_bits) into a rhs-bits number: i.e it returns b such that lhs mod 2^rhs is b
-pub(crate) fn evaluate_truncate(
-    lhs: &Expression,
-    rhs: u32,
-    max_bits: u32,
-    evaluator: &mut Evaluator,
-) -> Expression {
-    assert!(max_bits > rhs, "max_bits = {max_bits}, rhs = {rhs}");
-    let exp_big = BigUint::from(2_u32).pow(rhs);
-
-    //0. Check for constant expression. This can happen through arithmetic simplifications
-    if let Some(a_c) = lhs.to_const() {
-        let mut a_big = BigUint::from_bytes_be(&a_c.to_be_bytes());
-        a_big %= exp_big;
-        return Expression::from(FieldElement::from_be_bytes_reduce(&a_big.to_bytes_be()));
-    }
-    let exp = FieldElement::from_be_bytes_reduce(&exp_big.to_bytes_be());
-
-    //1. Generate witnesses a,b,c
-    let b_witness = evaluator.add_witness_to_cs();
-    let c_witness = evaluator.add_witness_to_cs();
-    evaluator.push_opcode(AcirOpcode::Directive(Directive::Quotient(QuotientDirective {
-        a: lhs.clone(),
-        b: Expression::from_field(exp),
-        q: c_witness,
-        r: b_witness,
-        predicate: None,
-    })));
-
-    try_range_constraint(b_witness, rhs, evaluator); //TODO propagate the error using ?
-    try_range_constraint(c_witness, max_bits - rhs, evaluator);
-
-    //2. Add the constraint a = b+2^Nc
-    let mut f = FieldElement::from(2_i128);
-    f = f.pow(&FieldElement::from(rhs as i128));
-    let b_arith = b_witness.into();
-    let c_arith = c_witness.into();
-    let res = add(&b_arith, f, &c_arith); //b+2^Nc
-    let my_constraint = add(&res, -FieldElement::one(), lhs);
-    evaluator.push_opcode(AcirOpcode::Arithmetic(my_constraint));
-
-    Expression::from(b_witness)
-}
-
-//Returns b such that lhs (a number whose value requires max_bits) mod rhs is b
-pub(crate) fn evaluate_constant_modulo(
-    lhs: &Expression,
-    rhs: u32,
-    max_bits: u32,
-    evaluator: &mut Evaluator,
-) -> Expression {
-    let modulus = FieldElement::from(rhs as i128);
-    let modulus_exp = Expression::from_field(modulus);
-    assert_ne!(rhs, 0);
-    let modulus_bits = bit_size_u128((rhs - 1) as u128);
-    assert!(max_bits >= rhs, "max_bits = {max_bits}, rhs = {rhs}");
-    //0. Check for constant expression. This can happen through arithmetic simplifications
-    if let Some(a_c) = lhs.to_const() {
-        let mut a_big = BigUint::from_bytes_be(&a_c.to_be_bytes());
-        a_big %= BigUint::from_bytes_be(&modulus.to_be_bytes());
-        return Expression::from(FieldElement::from_be_bytes_reduce(&a_big.to_bytes_be()));
-    }
-
-    //1. Generate witnesses b,c
-    let b_witness = evaluator.add_witness_to_cs();
-    let c_witness = evaluator.add_witness_to_cs();
-    evaluator.push_opcode(AcirOpcode::Directive(Directive::Quotient(QuotientDirective {
-        a: lhs.clone(),
-        b: modulus_exp.clone(),
-        q: c_witness,
-        r: b_witness,
-        predicate: None,
-    })));
-    bound_constraint_with_offset(
-        &Expression::from(b_witness),
-        &modulus_exp,
-        &Expression::one(),
-        modulus_bits,
-        evaluator,
-    );
-    //if rhs is a power of 2, then we avoid this range check as it is redundant with the previous one.
-    if rhs & (rhs - 1) != 0 {
-        try_range_constraint(b_witness, modulus_bits, evaluator);
-    }
-    let c_bound = FieldElement::modulus() / BigUint::from(rhs) - BigUint::one();
-    try_range_constraint(c_witness, c_bound.bits() as u32, evaluator);
-
-    //2. Add the constraint lhs = b+q*rhs
-    let b_arith = b_witness.into();
-    let c_arith = c_witness.into();
-    let res = add(&b_arith, modulus, &c_arith);
-    let my_constraint = add(&res, -FieldElement::one(), lhs);
-    evaluator.push_opcode(AcirOpcode::Arithmetic(my_constraint));
-
-    Expression::from(b_witness)
-}
-
-pub(crate) fn evaluate_udiv(
-    lhs: &Expression,
-    rhs: &Expression,
-    bit_size: u32,
-    predicate: &Expression,
-    evaluator: &mut Evaluator,
-) -> (Witness, Witness) {
-    let q_witness = evaluator.add_witness_to_cs();
-    let r_witness = evaluator.add_witness_to_cs();
-    let pa = mul_with_witness(evaluator, lhs, predicate);
-    evaluator.push_opcode(AcirOpcode::Directive(Directive::Quotient(QuotientDirective {
-        a: lhs.clone(),
-        b: rhs.clone(),
-        q: q_witness,
-        r: r_witness,
-        predicate: Some(predicate.clone()),
-    })));
-
-    //r<b
-    let r_expr = Expression::from(r_witness);
-    try_range_constraint(r_witness, bit_size, evaluator);
-    bound_constraint_with_offset(&r_expr, rhs, predicate, bit_size, evaluator);
-    //range check q<=a
-    try_range_constraint(q_witness, bit_size, evaluator);
-    // a-b*q-r = 0
-    let mut d = mul_with_witness(evaluator, rhs, &Expression::from(q_witness));
-    d = add(&d, FieldElement::one(), &Expression::from(r_witness));
-    d = mul_with_witness(evaluator, &d, predicate);
-    let div_euclidean = subtract(&pa, FieldElement::one(), &d);
-
-    evaluator.push_opcode(AcirOpcode::Arithmetic(div_euclidean));
-    (q_witness, r_witness)
-}
-
-/// Creates a new witness and constrains it to be the inverse of x
-pub(crate) fn evaluate_inverse(
-    x_witness: Witness,
-    predicate: &Expression,
-    evaluator: &mut Evaluator,
-) -> Witness {
-    // Create a fresh witness - n.b we could check if x is constant or not
-    let inverse_witness = evaluator.add_witness_to_cs();
-    evaluator.push_opcode(AcirOpcode::Directive(Directive::Invert {
-        x: x_witness,
-        result: inverse_witness,
-    }));
-
-    //x*inverse = 1
-    let one = mul(&x_witness.into(), &inverse_witness.into());
-    let lhs = mul_with_witness(evaluator, &one, predicate);
-    evaluator.push_opcode(AcirOpcode::Arithmetic(subtract(&lhs, FieldElement::one(), predicate)));
-    inverse_witness
-}
-
-//Zero Equality gate: returns 1 if x is not null and 0 else
-pub(crate) fn evaluate_zero_equality(x_witness: Witness, evaluator: &mut Evaluator) -> Witness {
-    let m = evaluator.add_witness_to_cs(); //'inverse' of x
-    evaluator.push_opcode(AcirOpcode::Directive(Directive::Invert { x: x_witness, result: m }));
-
-    //y=x*m         y is 1 if x is not null, and 0 else
-    let y_witness = evaluator.add_witness_to_cs();
-    evaluator.push_opcode(AcirOpcode::Arithmetic(Expression {
-        mul_terms: vec![(FieldElement::one(), x_witness, m)],
-        linear_combinations: vec![(-FieldElement::one(), y_witness)],
-        q_c: FieldElement::zero(),
-    }));
-
-    //x=y*x
-    let xy = mul(&x_witness.into(), &y_witness.into());
-    evaluator.push_opcode(AcirOpcode::Arithmetic(subtract(
-        &xy,
-        FieldElement::one(),
-        &x_witness.into(),
-    )));
-    y_witness
-}
-
-// Given two lists, `A` and `B` of `Expression`s
-// We generate constraints that A and B are equal
-// An `Expression` is returned that indicates whether this
-// was true.
-//
-// This method does not check the arrays length.
-// We assume this has been checked by the caller.
-pub(crate) fn arrays_eq_predicate(
-    a_values: &[Expression],
-    b_values: &[Expression],
-    evaluator: &mut Evaluator,
-) -> Expression {
-    let mut sum = Expression::default();
-
-    for (a_iter, b_iter) in a_values.iter().zip(b_values) {
-        let diff_expr = subtract(a_iter, FieldElement::one(), b_iter);
-
-        let diff_witness = evaluator.add_witness_to_cs();
-
-        evaluator.push_opcode(AcirOpcode::Arithmetic(subtract(
-            &diff_expr,
-            FieldElement::one(),
-            &diff_witness.into(),
-        )));
-        //TODO: avoid creating witnesses for diff
-        sum =
-            add(&sum, FieldElement::one(), &evaluate_zero_equality(diff_witness, evaluator).into());
-    }
-    sum
-}
-
-// TODO: An issue should be created for this
-pub(crate) fn evaluate_sdiv(
-    _lhs: &Expression,
-    _rhs: &Expression,
-    _evaluator: &mut Evaluator,
-) -> (Expression, Expression) {
-    todo!();
-}
-
-const fn num_bits<T>() -> usize {
-    std::mem::size_of::<T>() * 8
-}
-
-fn bit_size_u128(a: u128) -> u32 where {
-    num_bits::<u128>() as u32 - a.leading_zeros()
-}
-
-fn bit_size_u32(a: u32) -> u32 where {
-    num_bits::<u32>() as u32 - a.leading_zeros()
-}
diff --git a/crates/noirc_evaluator/src/ssa/acir_gen/internal_var.rs b/crates/noirc_evaluator/src/ssa/acir_gen/internal_var.rs
deleted file mode 100644
index 27d6b0ec25b..00000000000
--- a/crates/noirc_evaluator/src/ssa/acir_gen/internal_var.rs
+++ /dev/null
@@ -1,188 +0,0 @@
-use crate::ssa::node::NodeId;
-use acvm::{
-    acir::native_types::{Expression, Witness},
-    FieldElement,
-};
-
-#[derive(Clone, Debug, Eq)]
-pub(crate) struct InternalVar {
-    // A multi-variate degree-2 polynomial
-    expression: Expression,
-    // A witness associated to `expression`.
-    // semantically `cached_witness` and `expression`
-    // should be the equal.
-    //
-    // Example: `z = x + y`
-    // `z` can be seen as the same to `x + y`
-    // ie if `z = 10` , then `x+y` must be equal to
-    // 10.
-    // There are places where we can use `cached_witness`
-    // in place of `expression` for performance reasons
-    // due to the fact that `cached_witness` is a single variable
-    // whereas `expression` is a multi-variate polynomial which can
-    // contain many degree-2 terms.
-    //
-    // Note that we also protect against the case that `expression`
-    // changes and `cached_witness` becomes "dirty" or outdated.
-    // This is because one is not allowed to modify the `expression`
-    // once set. Additionally, there are no methods that allow one
-    // to modify the `cached_witness`
-    cached_witness: Option<Witness>,
-    id: Option<NodeId>,
-}
-
-impl InternalVar {
-    pub(crate) fn expression(&self) -> &Expression {
-        &self.expression
-    }
-    pub(crate) fn set_id(&mut self, id: NodeId) {
-        self.id = Some(id);
-    }
-    pub(crate) fn get_id(&self) -> Option<NodeId> {
-        self.id
-    }
-    pub(crate) fn cached_witness(&self) -> &Option<Witness> {
-        &self.cached_witness
-    }
-    pub(crate) fn set_witness(&mut self, w: Witness) {
-        debug_assert!(self.cached_witness.is_none() || self.cached_witness == Some(w));
-        self.cached_witness = Some(w);
-    }
-
-    pub(crate) fn to_expression(&self) -> Expression {
-        if let Some(w) = self.cached_witness {
-            w.into()
-        } else {
-            self.expression().clone()
-        }
-    }
-
-    /// If the InternalVar holds a constant expression
-    /// Return that constant.Otherwise, return None.
-    pub(super) fn to_const(&self) -> Option<FieldElement> {
-        self.expression.to_const()
-    }
-
-    /// The expression term is degree-2 multi-variate polynomial, so
-    /// in order to check if if represents a constant,
-    /// we need to check that the degree-2 terms `mul_terms`
-    /// and the degree-1 terms `linear_combinations` do not exist.
-    ///
-    /// Example: f(x,y) = xy + 5
-    /// `f` is not a constant expression because there
-    /// is a bi-variate term `xy`.
-    /// Example: f(x,y) = x + y + 5
-    /// `f` is not a constant expression because there are
-    /// two uni-variate terms `x` and `y`
-    /// Example: f(x,y) = 10
-    /// `f` is a constant expression because there are no
-    /// bi-variate or uni-variate terms, just a constant.
-    pub(crate) fn is_const_expression(&self) -> bool {
-        self.expression.is_const()
-    }
-
-    /// Creates an `InternalVar` from an `Expression`.
-    /// If `Expression` represents a degree-1 polynomial
-    /// then we also assign it to the `cached_witness`
-    pub(crate) fn from_expression(expression: Expression) -> InternalVar {
-        let witness = expression.to_witness();
-        InternalVar { expression, cached_witness: witness, id: None }
-    }
-
-    pub(crate) fn zero_expr() -> InternalVar {
-        InternalVar::from_expression(Expression::zero())
-    }
-
-    /// Creates an `InternalVar` from a `Witness`.
-    /// Since a `Witness` can alway be coerced into an
-    /// Expression, this method is infallible.
-    pub(crate) fn from_witness(witness: Witness) -> InternalVar {
-        InternalVar {
-            expression: Expression::from(witness),
-            cached_witness: Some(witness),
-            id: None,
-        }
-    }
-
-    /// Creates an `InternalVar` from a `FieldElement`.
-    pub(crate) fn from_constant(constant: FieldElement) -> InternalVar {
-        InternalVar { expression: Expression::from_field(constant), cached_witness: None, id: None }
-    }
-}
-
-impl PartialEq for InternalVar {
-    fn eq(&self, other: &Self) -> bool {
-        // An InternalVar is Equal to another InternalVar if _any_ of the fields
-        // in the InternalVar are equal.
-
-        let expressions_are_same = self.expression == other.expression;
-
-        // Check if `cached_witnesses` are the same
-        //
-        // This may happen if the expressions are the same
-        // but one is simplified and the other is not.
-        //
-        // The caller whom created both `InternalVar` objects
-        // may have known this and set their cached_witnesses to
-        // be the same.
-        // Example:
-        // z = 2*x + y
-        // t = x + x + y
-        // After simplification, it is clear that both RHS are the same
-        // However, since when we check for equality, we do not check for
-        // simplification, or in particular, we may eagerly assume
-        // the two expressions of the RHS are different.
-        //
-        // The caller can notice this and thus do:
-        // InternalVar::new(expr: 2*x + y, witness: z)
-        // InternalVar::new(expr: x + x + y, witness: z)
-        let cached_witnesses_same =
-            self.cached_witness.is_some() && self.cached_witness == other.cached_witness;
-
-        let node_ids_same = self.id.is_some() && self.id == other.id;
-
-        expressions_are_same || cached_witnesses_same || node_ids_same
-    }
-}
-
-impl From<Expression> for InternalVar {
-    fn from(expression: Expression) -> InternalVar {
-        InternalVar::from_expression(expression)
-    }
-}
-
-impl From<Witness> for InternalVar {
-    fn from(witness: Witness) -> InternalVar {
-        InternalVar::from_witness(witness)
-    }
-}
-
-impl From<FieldElement> for InternalVar {
-    fn from(constant: FieldElement) -> InternalVar {
-        InternalVar::from_constant(constant)
-    }
-}
-
-#[cfg(test)]
-mod tests {
-    use crate::ssa::acir_gen::InternalVar;
-    use acvm::FieldElement;
-
-    #[test]
-    fn internal_var_const_expression() {
-        let expected_constant = FieldElement::from(123456789u128);
-
-        // Initialize an InternalVar with a FieldElement
-        let internal_var = InternalVar::from_constant(expected_constant);
-
-        // We currently do not create witness when the InternalVar was created using a constant
-        assert!(internal_var.cached_witness().is_none());
-
-        match internal_var.to_const() {
-            Some(got_constant) => assert_eq!(got_constant, expected_constant),
-            None => {
-                panic!("`InternalVar` was initialized with a constant, so a field element was expected")
-            }
-        }
-    }
-}
diff --git a/crates/noirc_evaluator/src/ssa/acir_gen/internal_var_cache.rs b/crates/noirc_evaluator/src/ssa/acir_gen/internal_var_cache.rs
deleted file mode 100644
index fc9f9ae5af7..00000000000
--- a/crates/noirc_evaluator/src/ssa/acir_gen/internal_var_cache.rs
+++ /dev/null
@@ -1,287 +0,0 @@
-use crate::{
-    ssa::{
-        acir_gen::InternalVar,
-        context::SsaContext,
-        node::{Node, NodeId, NodeObject, ObjectType},
-    },
-    Evaluator,
-};
-use acvm::{
-    acir::native_types::{Expression, Witness},
-    FieldElement,
-};
-use std::collections::HashMap;
-
-use super::expression_to_witness;
-
-#[derive(Default)]
-pub(crate) struct InternalVarCache {
-    /// Map node id to an InternalVar
-    inner: HashMap<NodeId, InternalVar>,
-    /// Map field values to an InternalVar, which lazily gets a witness when required
-    /// This avoids us to re-create another witness for the same value
-    /// A witness for a field value should be avoided but can be needed as an opcode input, for example the logic opcode.
-    constants: HashMap<FieldElement, InternalVar>,
-}
-
-impl InternalVarCache {
-    //This function stores the substitution with the arithmetic expression in the cache
-    //When an instruction performs arithmetic operation, its output can be represented as an arithmetic expression of its arguments
-    //Substitute a node object as an arithmetic expression
-    // Returns `None` if `NodeId` represents an array pointer.
-    pub(super) fn get_or_compute_internal_var(
-        &mut self,
-        id: NodeId,
-        evaluator: &mut Evaluator,
-        ctx: &SsaContext,
-    ) -> Option<InternalVar> {
-        if let Some(internal_var) = self.inner.get(&id) {
-            return Some(internal_var.clone());
-        }
-
-        let mut var = match ctx.try_get_node(id)? {
-            NodeObject::Const(c) => {
-                // use the InternalVar from constants if exists
-                let field_value = FieldElement::from_be_bytes_reduce(&c.value.to_bytes_be());
-                let mut result = InternalVar::from_constant(field_value);
-                if let Some(c_var) = self.constants.get(&field_value) {
-                    result = c_var.clone();
-                }
-
-                //use witness from other nodes if exists
-                let new_vec = Vec::new();
-                let constant_ids = ctx.constants.get(&field_value).unwrap_or(&new_vec);
-                let cached_witness =
-                    constant_ids.iter().find_map(|c_id| match self.inner.get(c_id) {
-                        Some(i_var) => *i_var.cached_witness(),
-                        None => None,
-                    });
-                if let Some(w) = cached_witness {
-                    result.set_witness(w);
-                }
-
-                result
-            }
-            NodeObject::Variable(variable) => {
-                let variable_type = variable.get_type();
-                match variable_type {
-                    ObjectType::Numeric(..) => {
-                        let witness =
-                            variable.witness.unwrap_or_else(|| evaluator.add_witness_to_cs());
-                        InternalVar::from_witness(witness)
-                    }
-                    ObjectType::ArrayPointer(_) | ObjectType::NotAnObject => return None,
-                    ObjectType::Function => {
-                        unreachable!("ICE: functions should have been removed by this stage")
-                    }
-                }
-            }
-            NodeObject::Function(..) => {
-                unreachable!("ICE: functions should have been removed by this stage")
-            }
-            // TODO: Why do we create a `Witness` for an instruction (Guillaume)
-            NodeObject::Instr(..) => {
-                let witness = evaluator.add_witness_to_cs();
-                InternalVar::from_witness(witness)
-            }
-        };
-
-        var.set_id(id);
-        self.inner.insert(id, var.clone());
-        Some(var)
-    }
-
-    pub(super) fn get_or_compute_internal_var_unwrap(
-        &mut self,
-        id: NodeId,
-        evaluator: &mut Evaluator,
-        ctx: &SsaContext,
-    ) -> InternalVar {
-        self.get_or_compute_internal_var(id, evaluator, ctx)
-            .expect("ICE: `NodeId` type cannot be converted into an `InternalVar`")
-    }
-
-    pub(super) fn get(&mut self, id: &NodeId) -> Option<&InternalVar> {
-        self.inner.get(id)
-    }
-
-    // Transform a field element into a witness
-    // It implements a 'get or create' pattern to ensure only one witness is created per element
-    fn const_to_witness(
-        &mut self,
-        value: FieldElement,
-        evaluator: &mut Evaluator,
-        ctx: &SsaContext,
-    ) -> Witness {
-        if let Some(ids) = ctx.constants.get(&value) {
-            //we have a constant node object for the value
-            if let Some(id) = ids.first() {
-                let var = self.get_or_compute_internal_var_unwrap(*id, evaluator, ctx);
-                if let Some(w) = var.cached_witness() {
-                    return *w;
-                }
-            }
-            // We generate a witness and assigns it
-            let w = evaluator.create_intermediate_variable(Expression::from(value));
-            for &id in ids {
-                let mut cached_var = self.get_or_compute_internal_var_unwrap(id, evaluator, ctx);
-                if let Some(cached_witness) = cached_var.cached_witness() {
-                    assert_eq!(*cached_witness, w);
-                } else {
-                    cached_var.set_witness(w);
-                }
-                self.update(cached_var);
-            }
-            w
-        } else {
-            //if not, we use the constants map
-            let var =
-                self.constants.entry(value).or_insert_with(|| InternalVar::from_constant(value));
-            Self::const_to_witness_helper(var, evaluator)
-        }
-    }
-
-    // Helper function which generates a witness for an InternalVar
-    // Do not call outside const_to_witness()
-    fn const_to_witness_helper(var: &mut InternalVar, evaluator: &mut Evaluator) -> Witness {
-        let w = Self::internal_get_or_compute_witness(var, evaluator);
-        if w.is_none() {
-            let witness = expression_to_witness(var.to_expression(), evaluator);
-            var.set_witness(witness);
-        }
-        var.cached_witness().expect("Infallible, the witness is computed before")
-    }
-
-    /// Get or compute a witness for an internal var
-    /// WARNING: It generates a witness even if the internal var is constant, so it should be used only if the var is an input
-    /// to some ACIR opcode which requires a witness
-    pub(crate) fn get_or_compute_witness_unwrap(
-        &mut self,
-        mut var: InternalVar,
-        evaluator: &mut Evaluator,
-        ctx: &SsaContext,
-    ) -> Witness {
-        if let Some(v) = var.to_const() {
-            self.const_to_witness(v, evaluator, ctx)
-        } else {
-            let w = Self::internal_get_or_compute_witness(&mut var, evaluator)
-                .expect("infallible non const expression");
-            var.set_witness(w);
-            self.update(var);
-            w
-        }
-    }
-
-    /// Get or compute a witness equating the internal var
-    /// It returns None when the variable is a constant instead of creating a witness
-    /// because we should not need a witness in that case
-    /// If you really need one, you can use get_or_compute_witness_unwrap()
-    pub(crate) fn get_or_compute_witness(
-        &mut self,
-        mut var: InternalVar,
-        evaluator: &mut Evaluator,
-    ) -> Option<Witness> {
-        let w = Self::internal_get_or_compute_witness(&mut var, evaluator);
-        if w.is_some() {
-            assert!(var.cached_witness().is_some());
-        } else {
-            return None;
-        };
-        self.update(var);
-
-        w
-    }
-
-    /// Generates a `Witness` that is equal to the `expression`.
-    /// - If a `Witness` has previously been generated, we return it.
-    /// - If the Expression represents a constant, we return None.
-    fn internal_get_or_compute_witness(
-        var: &mut InternalVar,
-        evaluator: &mut Evaluator,
-    ) -> Option<Witness> {
-        // Check if we've already generated a `Witness` which is equal to
-        // the stored `Expression`
-        if let Some(witness) = var.cached_witness() {
-            return Some(*witness);
-        }
-
-        // We do not generate a witness for constant values. It can only be done at the InternalVarCache level.
-        if var.is_const_expression() {
-            return None;
-        }
-
-        var.set_witness(expression_to_witness(var.expression().clone(), evaluator));
-
-        *var.cached_witness()
-    }
-
-    pub(super) fn update(&mut self, var: InternalVar) {
-        if let Some(id) = var.get_id() {
-            self.inner.insert(id, var);
-        } else if let Some(value) = var.to_const() {
-            self.constants.insert(value, var);
-        }
-    }
-}
-
-#[cfg(test)]
-mod test {
-
-    use acvm::{acir::native_types::Witness, FieldElement};
-
-    use crate::{
-        ssa::{
-            acir_gen::internal_var_cache::{InternalVar, InternalVarCache},
-            context::SsaContext,
-        },
-        Evaluator,
-    };
-
-    // Check that only one witness is generated for const values
-    #[test]
-    fn test_const_witness() {
-        let mut eval = Evaluator::default();
-        let ctx = SsaContext::default();
-        let mut var_cache = InternalVarCache::default();
-        let v1 = var_cache.get_or_compute_internal_var_unwrap(ctx.one(), &mut eval, &ctx);
-        let v2 = var_cache.get_or_compute_internal_var_unwrap(ctx.zero(), &mut eval, &ctx);
-        let w1 = var_cache.get_or_compute_witness_unwrap(v1, &mut eval, &ctx);
-        let w2 = var_cache.get_or_compute_witness_unwrap(v2, &mut eval, &ctx);
-        let w11 = var_cache.get_or_compute_witness_unwrap(
-            InternalVar::from_constant(FieldElement::one()),
-            &mut eval,
-            &ctx,
-        );
-        let w21 = var_cache.get_or_compute_witness_unwrap(
-            InternalVar::from_constant(FieldElement::zero()),
-            &mut eval,
-            &ctx,
-        );
-        let two = FieldElement::one() + FieldElement::one();
-        assert!(var_cache.constants.is_empty());
-        assert_eq!(w1, w11);
-        assert_eq!(w2, w21);
-        var_cache.const_to_witness(two, &mut eval, &ctx);
-        assert!(var_cache.constants.len() == 1);
-        var_cache.const_to_witness(two, &mut eval, &ctx);
-        assert!(var_cache.constants.len() == 1);
-        var_cache.const_to_witness(FieldElement::one(), &mut eval, &ctx);
-        assert!(var_cache.constants.len() == 1);
-    }
-
-    #[test]
-    fn internal_var_from_witness() {
-        let mut evaluator = Evaluator::default();
-        let expected_witness = Witness(1234);
-        // Initialize an InternalVar with a `Witness`
-        let mut internal_var = InternalVar::from_witness(expected_witness);
-
-        // We should get back the same `Witness`
-        let got_witness =
-            InternalVarCache::internal_get_or_compute_witness(&mut internal_var, &mut evaluator);
-        match got_witness {
-            Some(got_witness) => assert_eq!(got_witness, expected_witness),
-            None => panic!("expected a `Witness` value"),
-        }
-    }
-}
diff --git a/crates/noirc_evaluator/src/ssa/acir_gen/operations.rs b/crates/noirc_evaluator/src/ssa/acir_gen/operations.rs
deleted file mode 100644
index 46a785fc714..00000000000
--- a/crates/noirc_evaluator/src/ssa/acir_gen/operations.rs
+++ /dev/null
@@ -1,13 +0,0 @@
-pub(super) mod binary;
-mod bitwise;
-mod cmp;
-
-pub(super) mod condition;
-pub(super) mod constrain;
-pub(super) mod intrinsics;
-pub(super) mod load;
-pub(super) mod not;
-pub(super) mod r#return;
-pub(crate) mod sort;
-pub(super) mod store;
-pub(super) mod truncate;
diff --git a/crates/noirc_evaluator/src/ssa/acir_gen/operations/binary.rs b/crates/noirc_evaluator/src/ssa/acir_gen/operations/binary.rs
deleted file mode 100644
index 166a55b0d52..00000000000
--- a/crates/noirc_evaluator/src/ssa/acir_gen/operations/binary.rs
+++ /dev/null
@@ -1,245 +0,0 @@
-use crate::{
-    ssa::{
-        acir_gen::{
-            constraints, internal_var_cache::InternalVarCache, operations, Acir, InternalVar,
-        },
-        context::SsaContext,
-        node::{self, BinaryOp, Node, ObjectType},
-    },
-    Evaluator,
-};
-use acvm::{acir::native_types::Expression, FieldElement};
-use num_bigint::BigUint;
-use num_traits::{One, Zero};
-
-fn get_predicate(
-    var_cache: &mut InternalVarCache,
-    binary: &node::Binary,
-    evaluator: &mut Evaluator,
-    ctx: &SsaContext,
-) -> InternalVar {
-    let predicate_node_id = match binary.predicate {
-        Some(pred) => pred,
-        None => return InternalVar::from(Expression::one()),
-    };
-    var_cache.get_or_compute_internal_var_unwrap(predicate_node_id, evaluator, ctx)
-}
-
-pub(crate) fn evaluate(
-    binary: &node::Binary,
-    res_type: ObjectType,
-    acir_gen: &mut Acir,
-    evaluator: &mut Evaluator,
-    ctx: &SsaContext,
-) -> Option<InternalVar> {
-    let r_size = ctx[binary.rhs].size_in_bits();
-    let l_size = ctx[binary.lhs].size_in_bits();
-    let max_size = u32::max(r_size, l_size);
-    if binary.predicate == Some(ctx.zero()) {
-        return None;
-    }
-
-    let binary_output = match &binary.operator {
-            BinaryOp::Add | BinaryOp::SafeAdd => {
-                let l_c = acir_gen.var_cache.get_or_compute_internal_var_unwrap(binary.lhs, evaluator, ctx);
-                let r_c = acir_gen.var_cache.get_or_compute_internal_var_unwrap(binary.rhs, evaluator, ctx);
-                InternalVar::from(constraints::add(
-                    l_c.expression(),
-                    FieldElement::one(),
-                    r_c.expression(),
-                ))
-            },
-            BinaryOp::Sub { max_rhs_value } | BinaryOp::SafeSub { max_rhs_value } => {
-                let l_c = acir_gen.var_cache.get_or_compute_internal_var_unwrap(binary.lhs, evaluator, ctx);
-                let r_c = acir_gen.var_cache.get_or_compute_internal_var_unwrap(binary.rhs, evaluator, ctx);
-                if res_type == ObjectType::native_field() {
-                    InternalVar::from(constraints::subtract(
-                        l_c.expression(),
-                        FieldElement::one(),
-                        r_c.expression(),
-                    ))
-                } else {
-                    //we need the type of rhs and its max value, then:
-                    //lhs-rhs+k*2^bit_size where k=ceil(max_value/2^bit_size)
-                    let bit_size = ctx[binary.rhs].get_type().bits();
-                    let r_big = BigUint::one() << bit_size;
-                    let mut k = max_rhs_value / &r_big;
-                    if max_rhs_value % &r_big != BigUint::zero() {
-                        k = &k + BigUint::one();
-                    }
-                    k = &k * r_big;
-                    let f = FieldElement::from_be_bytes_reduce(&k.to_bytes_be());
-                    let mut sub_expr = constraints::subtract(
-                        l_c.expression(),
-                        FieldElement::one(),
-                        r_c.expression(),
-                    );
-                    sub_expr.q_c += f;
-                    let mut sub_var = sub_expr.into();
-                    //TODO: uses interval analysis for more precise check
-                    if let Some(lhs_const) = l_c.to_const() {
-                        if max_rhs_value <= &BigUint::from_bytes_be(&lhs_const.to_be_bytes()) {
-                            sub_var = InternalVar::from(constraints::subtract(
-                                l_c.expression(),
-                                FieldElement::one(),
-                                r_c.expression(),
-                            ));
-                        }
-                    }
-                    sub_var
-                }
-            }
-            BinaryOp::Mul | BinaryOp::SafeMul => {
-                let l_c = acir_gen.var_cache.get_or_compute_internal_var_unwrap(binary.lhs, evaluator, ctx);
-                let r_c = acir_gen.var_cache.get_or_compute_internal_var_unwrap(binary.rhs, evaluator, ctx);
-                InternalVar::from(constraints::mul_with_witness(
-                evaluator,
-                l_c.expression(),
-                r_c.expression(),
-            ))
-            },
-            BinaryOp::Udiv(_) => {
-                let l_c = acir_gen.var_cache.get_or_compute_internal_var_unwrap(binary.lhs, evaluator, ctx);
-                let r_c = acir_gen.var_cache.get_or_compute_internal_var_unwrap(binary.rhs, evaluator, ctx);
-                let predicate = get_predicate(&mut acir_gen.var_cache,binary, evaluator, ctx);
-                let (q_wit, _) = constraints::evaluate_udiv(
-                    l_c.expression(),
-                    r_c.expression(),
-                    max_size,
-                    predicate.expression(),
-                    evaluator,
-                );
-                InternalVar::from(q_wit)
-            }
-            BinaryOp::Sdiv(_) => {
-                let l_c = acir_gen.var_cache.get_or_compute_internal_var_unwrap(binary.lhs, evaluator, ctx);
-                let r_c = acir_gen.var_cache.get_or_compute_internal_var_unwrap(binary.rhs, evaluator, ctx);
-                InternalVar::from(
-                constraints::evaluate_sdiv(l_c.expression(), r_c.expression(), evaluator).0,
-            )
-        },
-            BinaryOp::Urem(_) => {
-                let l_c = acir_gen.var_cache.get_or_compute_internal_var_unwrap(binary.lhs, evaluator, ctx);
-                let r_c = acir_gen.var_cache.get_or_compute_internal_var_unwrap(binary.rhs, evaluator, ctx);
-                let predicate = get_predicate(&mut acir_gen.var_cache,binary, evaluator, ctx);
-                let (_, r_wit) = constraints::evaluate_udiv(
-                    l_c.expression(),
-                    r_c.expression(),
-                    max_size,
-                    predicate.expression(),
-                    evaluator,
-                );
-                InternalVar::from(r_wit)
-            }
-            BinaryOp::Srem(_) => {
-                let l_c = acir_gen.var_cache.get_or_compute_internal_var_unwrap(binary.lhs, evaluator, ctx);
-                let r_c = acir_gen.var_cache.get_or_compute_internal_var_unwrap(binary.rhs, evaluator, ctx);
-                InternalVar::from(
-                // TODO: we should use variable naming here instead of .1
-                constraints::evaluate_sdiv(l_c.expression(), r_c.expression(), evaluator).1,
-            )},
-            BinaryOp::Div(_) => {
-                let l_c = acir_gen.var_cache.get_or_compute_internal_var_unwrap(binary.lhs, evaluator, ctx);
-                let r_c = acir_gen.var_cache.get_or_compute_internal_var_unwrap(binary.rhs, evaluator, ctx);
-                let predicate = get_predicate(&mut acir_gen.var_cache,binary, evaluator, ctx).expression().clone();
-                if let Some(r_value) = r_c.to_const() {
-                    if r_value.is_zero() {
-                        panic!("Panic - division by zero");
-                    } else {
-                        (l_c.expression() * r_value.inverse()).into()
-                    }
-                } else {
-                    //TODO avoid creating witnesses here.
-                    let x_witness = acir_gen.var_cache.get_or_compute_witness(r_c, evaluator).expect("unexpected constant expression"); 
-                    let inverse = Expression::from(constraints::evaluate_inverse(
-                        x_witness, &predicate, evaluator,
-                    ));
-                    InternalVar::from(constraints::mul_with_witness(
-                        evaluator,
-                        l_c.expression(),
-                        &inverse,
-                    ))
-                }
-            }
-            BinaryOp::Eq => {
-                let l_c = acir_gen.var_cache.get_or_compute_internal_var(binary.lhs, evaluator, ctx);
-                let r_c = acir_gen.var_cache.get_or_compute_internal_var(binary.rhs, evaluator, ctx);
-                InternalVar::from(
-                operations::cmp::evaluate_eq(acir_gen,binary.lhs, binary.rhs, l_c, r_c, ctx, evaluator),
-            )},
-            BinaryOp::Ne => {
-                let l_c = acir_gen.var_cache.get_or_compute_internal_var(binary.lhs, evaluator, ctx);
-                let r_c = acir_gen.var_cache.get_or_compute_internal_var(binary.rhs, evaluator, ctx);
-                InternalVar::from(
-                operations::cmp::evaluate_neq(acir_gen,binary.lhs, binary.rhs, l_c, r_c, ctx, evaluator),
-            )},
-            BinaryOp::Ult => {
-                let l_c = acir_gen.var_cache.get_or_compute_internal_var_unwrap(binary.lhs, evaluator, ctx);
-                let r_c = acir_gen.var_cache.get_or_compute_internal_var_unwrap(binary.rhs, evaluator, ctx);
-                let size = ctx[binary.lhs].get_type().bits();
-                constraints::evaluate_cmp(
-                    l_c.expression(),
-                    r_c.expression(),
-                    size,
-                    false,
-                    evaluator,
-                )
-                .into()
-            }
-            BinaryOp::Ule => {
-                let l_c = acir_gen.var_cache.get_or_compute_internal_var_unwrap(binary.lhs, evaluator, ctx);
-                let r_c = acir_gen.var_cache.get_or_compute_internal_var_unwrap(binary.rhs, evaluator, ctx);
-                let size = ctx[binary.lhs].get_type().bits();
-                let e = constraints::evaluate_cmp(
-                    r_c.expression(),
-                    l_c.expression(),
-                    size,
-                    false,
-                    evaluator,
-                );
-                constraints::subtract(&Expression::one(), FieldElement::one(), &e).into()
-            }
-            BinaryOp::Slt => {
-                let l_c = acir_gen.var_cache.get_or_compute_internal_var_unwrap(binary.lhs, evaluator, ctx);
-                let r_c = acir_gen.var_cache.get_or_compute_internal_var_unwrap(binary.rhs, evaluator, ctx);
-                let s = ctx[binary.lhs].get_type().bits();
-                constraints::evaluate_cmp(l_c.expression(), r_c.expression(), s, true, evaluator)
-                    .into()
-            }
-            BinaryOp::Sle => {
-                let l_c = acir_gen.var_cache.get_or_compute_internal_var_unwrap(binary.lhs, evaluator, ctx);
-                let r_c = acir_gen.var_cache.get_or_compute_internal_var_unwrap(binary.rhs, evaluator, ctx);
-                let s = ctx[binary.lhs].get_type().bits();
-                let e = constraints::evaluate_cmp(
-                    r_c.expression(),
-                    l_c.expression(),
-                    s,
-                    true,
-                    evaluator,
-                );
-                constraints::subtract(&Expression::one(), FieldElement::one(), &e).into()
-            }
-            BinaryOp::Lt | BinaryOp::Lte => {
-                // TODO Create an issue to change this function to return a RuntimeErrorKind
-                // TODO then replace `unimplemented` with an error
-                // TODO (This is a breaking change)
-                unimplemented!(
-                "Field comparison is not implemented yet, try to cast arguments to integer type"
-            )
-            }
-            BinaryOp::And | BinaryOp::Or | BinaryOp::Xor => {
-                let l_c = acir_gen.var_cache.get_or_compute_internal_var_unwrap(binary.lhs, evaluator, ctx);
-                let r_c = acir_gen.var_cache.get_or_compute_internal_var_unwrap(binary.rhs, evaluator, ctx);
-                let bit_size = res_type.bits();
-                let opcode = binary.operator.clone();
-                let bitwise_result = match operations::bitwise::simplify_bitwise(&l_c, &r_c, bit_size, &opcode) {
-                    Some(simplified_internal_var) => simplified_internal_var.expression().clone(),
-                    None => operations::bitwise::evaluate_bitwise(l_c, r_c, bit_size, evaluator, &mut acir_gen.var_cache, ctx, opcode),
-                };
-                InternalVar::from(bitwise_result)
-            }
-            BinaryOp::Shl | BinaryOp::Shr(_) => todo!("ShiftLeft and ShiftRight operations with shifts which are only known at runtime are not yet implemented."),
-            i @ BinaryOp::Assign => unreachable!("Invalid Instruction: {:?}", i),
-        };
-    Some(binary_output)
-}
diff --git a/crates/noirc_evaluator/src/ssa/acir_gen/operations/bitwise.rs b/crates/noirc_evaluator/src/ssa/acir_gen/operations/bitwise.rs
deleted file mode 100644
index 6801cdc124b..00000000000
--- a/crates/noirc_evaluator/src/ssa/acir_gen/operations/bitwise.rs
+++ /dev/null
@@ -1,167 +0,0 @@
-use acvm::{
-    acir::{
-        circuit::opcodes::{BlackBoxFuncCall, FunctionInput, Opcode as AcirOpcode},
-        native_types::Expression,
-    },
-    FieldElement,
-};
-
-use crate::{
-    ssa::{
-        acir_gen::{constraints, internal_var_cache::InternalVarCache, InternalVar},
-        context::SsaContext,
-        node::BinaryOp,
-    },
-    Evaluator,
-};
-
-pub(super) fn simplify_bitwise(
-    lhs: &InternalVar,
-    rhs: &InternalVar,
-    bit_size: u32,
-    opcode: &BinaryOp,
-) -> Option<InternalVar> {
-    // Simplifies Bitwise operations of the form `a OP a`
-    // where `a` is an integer
-    //
-    // a XOR a == 0
-    // a AND a == a
-    // a OR  a == a
-    if lhs == rhs {
-        return Some(match opcode {
-            BinaryOp::And => lhs.clone(),
-            BinaryOp::Or => lhs.clone(),
-            BinaryOp::Xor => InternalVar::from(FieldElement::zero()),
-            _ => unreachable!("This method should only be called on bitwise binary operators"),
-        });
-    }
-
-    assert!(bit_size < FieldElement::max_num_bits());
-    let max = FieldElement::from((1_u128 << bit_size) - 1);
-
-    let (field, var) = match (lhs.to_const(), rhs.to_const()) {
-        (Some(l_c), None) => (l_c.is_zero() || l_c == max).then_some((l_c, rhs))?,
-        (None, Some(r_c)) => (r_c.is_zero() || r_c == max).then_some((r_c, lhs))?,
-        _ => return None,
-    };
-
-    //simplify bitwise operation of the form: 0 OP var or 1 OP var
-    Some(match opcode {
-        BinaryOp::And => {
-            if field.is_zero() {
-                InternalVar::from(field)
-            } else {
-                var.clone()
-            }
-        }
-        BinaryOp::Xor => {
-            if field.is_zero() {
-                var.clone()
-            } else {
-                InternalVar::from(constraints::subtract(
-                    &Expression::from_field(field),
-                    FieldElement::one(),
-                    var.expression(),
-                ))
-            }
-        }
-        BinaryOp::Or => {
-            if field.is_zero() {
-                var.clone()
-            } else {
-                InternalVar::from(field)
-            }
-        }
-        _ => unreachable!(),
-    })
-}
-// Precondition: `lhs` and `rhs` do not represent constant expressions
-pub(super) fn evaluate_bitwise(
-    lhs: InternalVar,
-    rhs: InternalVar,
-    bit_size: u32,
-    evaluator: &mut Evaluator,
-    var_cache: &mut InternalVarCache,
-    ctx: &SsaContext,
-    opcode: BinaryOp,
-) -> Expression {
-    // Check precondition
-    if let (Some(_), Some(_)) = (lhs.to_const(), rhs.to_const()) {
-        unreachable!("ICE: `lhs` and `rhs` are expected to be simplified. Therefore it should not be possible for both to be constants.");
-    }
-
-    if bit_size == 1 {
-        match opcode {
-            BinaryOp::And => {
-                return constraints::mul_with_witness(evaluator, lhs.expression(), rhs.expression())
-            }
-            BinaryOp::Xor => {
-                let sum = constraints::add(lhs.expression(), FieldElement::one(), rhs.expression());
-                let mul =
-                    constraints::mul_with_witness(evaluator, lhs.expression(), rhs.expression());
-                return constraints::subtract(&sum, FieldElement::from(2_i128), &mul);
-            }
-            BinaryOp::Or => {
-                let sum = constraints::add(lhs.expression(), FieldElement::one(), rhs.expression());
-                let mul =
-                    constraints::mul_with_witness(evaluator, lhs.expression(), rhs.expression());
-                return constraints::subtract(&sum, FieldElement::one(), &mul);
-            }
-            _ => unreachable!(),
-        }
-    }
-    //We generate witness from const values in order to use the ACIR bitwise gates
-    // If the gate is implemented, it is expected to be better than going through bit decomposition, even if one of the operand is a constant
-    // If the gate is not implemented, we rely on the ACIR simplification to remove these witnesses
-    //
-    let mut a_witness = var_cache.get_or_compute_witness_unwrap(lhs, evaluator, ctx);
-    let mut b_witness = var_cache.get_or_compute_witness_unwrap(rhs, evaluator, ctx);
-
-    let result = evaluator.add_witness_to_cs();
-    let bit_size = if bit_size % 2 == 1 { bit_size + 1 } else { bit_size };
-    assert!(bit_size < FieldElement::max_num_bits() - 1);
-    let max = FieldElement::from((1_u128 << bit_size) - 1);
-    let gate = match opcode {
-        BinaryOp::And => AcirOpcode::BlackBoxFuncCall(BlackBoxFuncCall::AND {
-            lhs: FunctionInput { witness: a_witness, num_bits: bit_size },
-            rhs: FunctionInput { witness: b_witness, num_bits: bit_size },
-            output: result,
-        }),
-        BinaryOp::Xor => AcirOpcode::BlackBoxFuncCall(BlackBoxFuncCall::XOR {
-            lhs: FunctionInput { witness: a_witness, num_bits: bit_size },
-            rhs: FunctionInput { witness: b_witness, num_bits: bit_size },
-            output: result,
-        }),
-        BinaryOp::Or => {
-            a_witness = evaluator.create_intermediate_variable(constraints::subtract(
-                &Expression::from_field(max),
-                FieldElement::one(),
-                &Expression::from(a_witness),
-            ));
-            b_witness = evaluator.create_intermediate_variable(constraints::subtract(
-                &Expression::from_field(max),
-                FieldElement::one(),
-                &Expression::from(b_witness),
-            ));
-            // We do not have an OR gate yet, so we use the AND gate
-            AcirOpcode::BlackBoxFuncCall(BlackBoxFuncCall::AND {
-                lhs: FunctionInput { witness: a_witness, num_bits: bit_size },
-                rhs: FunctionInput { witness: b_witness, num_bits: bit_size },
-                output: result,
-            })
-        }
-        _ => unreachable!("ICE: expected a bitwise operation"),
-    };
-
-    evaluator.opcodes.push(gate);
-
-    if opcode == BinaryOp::Or {
-        constraints::subtract(
-            &Expression::from_field(max),
-            FieldElement::one(),
-            &Expression::from(result),
-        )
-    } else {
-        Expression::from(result)
-    }
-}
diff --git a/crates/noirc_evaluator/src/ssa/acir_gen/operations/cmp.rs b/crates/noirc_evaluator/src/ssa/acir_gen/operations/cmp.rs
deleted file mode 100644
index acc34e1ebac..00000000000
--- a/crates/noirc_evaluator/src/ssa/acir_gen/operations/cmp.rs
+++ /dev/null
@@ -1,133 +0,0 @@
-use crate::{
-    ssa::{
-        acir_gen::{acir_mem::AcirMem, constraints, Acir, InternalVar},
-        context::SsaContext,
-        mem::{MemArray, Memory},
-        node::NodeId,
-    },
-    Evaluator,
-};
-use acvm::{acir::native_types::Expression, FieldElement};
-use iter_extended::vecmap;
-
-// Given two `NodeId`s, generate constraints to check whether
-// they are Equal.
-//
-// This method returns an `Expression` representing `0` or `1`
-// If the two `NodeId`s are not equal, then the `Expression`
-// returned will represent `1`, otherwise `0` is returned.
-//
-// A `NodeId` can represent a primitive data type
-// like a `Field` or it could represent a composite type like an
-// `Array`. Depending on the type, the constraints that will be generated
-// will differ.
-//
-// TODO(check this): Types like structs are decomposed before getting to SSA
-// so in reality, the NEQ instruction will be done on the fields
-// of the struct
-pub(super) fn evaluate_neq(
-    acir_gen: &mut Acir,
-    lhs: NodeId,
-    rhs: NodeId,
-    l_c: Option<InternalVar>,
-    r_c: Option<InternalVar>,
-    ctx: &SsaContext,
-    evaluator: &mut Evaluator,
-) -> Expression {
-    // Check whether the `lhs` and `rhs` are trivially equal
-    if lhs == rhs {
-        return Expression::zero();
-    }
-
-    // Check whether the `lhs` and `rhs` are Arrays
-    if let (Some(a), Some(b)) = (Memory::deref(ctx, lhs), Memory::deref(ctx, rhs)) {
-        let array_a = &ctx.mem[a];
-        let array_b = &ctx.mem[b];
-
-        assert!(l_c.is_none());
-        assert!(r_c.is_none());
-
-        // TODO What happens if we call `l_c.expression()` on InternalVar
-        // TODO when we know that they should correspond to Arrays
-        // TODO(Guillaume): We can add an Option<Expression>  because
-        // TODO when the object is composite, it will return One
-        if array_a.len != array_b.len {
-            unreachable!(
-                "ICE: arrays have differing lengths {} and {}. 
-                We cannot compare two different types in Noir, 
-                so this should have been caught by the type checker",
-                array_a.len, array_b.len
-            )
-        }
-
-        let x = InternalVar::from(array_eq(&mut acir_gen.memory, array_a, array_b, evaluator));
-        // TODO we need a witness because of the directive, but we should use an expression
-        // TODO if we change the Invert directive to take an `Expression`, then we
-        // TODO can get rid of this extra gate.
-        let x_witness = acir_gen
-            .var_cache
-            .get_or_compute_witness(x, evaluator)
-            .expect("unexpected constant expression");
-
-        return Expression::from(constraints::evaluate_zero_equality(x_witness, evaluator));
-    }
-
-    // Arriving here means that `lhs` and `rhs` are not Arrays
-    let l_c = l_c.expect("ICE: unexpected array pointer");
-    let r_c = r_c.expect("ICE: unexpected array pointer");
-    let x = InternalVar::from(constraints::subtract(
-        l_c.expression(),
-        FieldElement::one(),
-        r_c.expression(),
-    ));
-
-    // Check if `x` is constant. If so, we can evaluate whether
-    // it is zero at compile time.
-    if let Some(x_const) = x.to_const() {
-        if x_const.is_zero() {
-            Expression::zero()
-        } else {
-            Expression::one()
-        }
-    } else {
-        //todo we need a witness because of the directive, but we should use an expression
-        let x_witness = acir_gen
-            .var_cache
-            .get_or_compute_witness(x, evaluator)
-            .expect("unexpected constant expression");
-        Expression::from(constraints::evaluate_zero_equality(x_witness, evaluator))
-    }
-}
-
-pub(super) fn evaluate_eq(
-    acir_gen: &mut Acir,
-    lhs: NodeId,
-    rhs: NodeId,
-    l_c: Option<InternalVar>,
-    r_c: Option<InternalVar>,
-    ctx: &SsaContext,
-    evaluator: &mut Evaluator,
-) -> Expression {
-    let neq = evaluate_neq(acir_gen, lhs, rhs, l_c, r_c, ctx, evaluator);
-    constraints::subtract(&Expression::one(), FieldElement::one(), &neq)
-}
-
-// Given two `MemArray`s, generate constraints that check whether
-// these two arrays are equal. An `Expression` is returned representing
-// `0` if the arrays were equal and `1` otherwise.
-//
-// N.B. We assumes the lengths of a and b are the same but it is not checked inside the function.
-fn array_eq(
-    memory_map: &mut AcirMem,
-    a: &MemArray,
-    b: &MemArray,
-    evaluator: &mut Evaluator,
-) -> Expression {
-    // Fetch the elements in both `MemArrays`s, these are `InternalVar`s
-    // We then convert these to `Expressions`
-    let internal_var_to_expr = |internal_var: InternalVar| internal_var.expression().clone();
-    let a_values = vecmap(memory_map.load_array(a, evaluator), internal_var_to_expr);
-    let b_values = vecmap(memory_map.load_array(b, evaluator), internal_var_to_expr);
-
-    constraints::arrays_eq_predicate(&a_values, &b_values, evaluator)
-}
diff --git a/crates/noirc_evaluator/src/ssa/acir_gen/operations/condition.rs b/crates/noirc_evaluator/src/ssa/acir_gen/operations/condition.rs
deleted file mode 100644
index db6c6c719da..00000000000
--- a/crates/noirc_evaluator/src/ssa/acir_gen/operations/condition.rs
+++ /dev/null
@@ -1,39 +0,0 @@
-use crate::{
-    ssa::{
-        acir_gen::{constraints, internal_var_cache::InternalVarCache, InternalVar},
-        context::SsaContext,
-        node::NodeId,
-    },
-    Evaluator,
-};
-use acvm::{acir::native_types::Expression, FieldElement};
-
-pub(crate) fn evaluate(
-    condition: NodeId,
-    lhs: NodeId,
-    rhs: NodeId,
-    var_cache: &mut InternalVarCache,
-    evaluator: &mut Evaluator,
-    ctx: &SsaContext,
-) -> Option<InternalVar> {
-    let cond = var_cache.get_or_compute_internal_var_unwrap(condition, evaluator, ctx);
-    let l_c = var_cache.get_or_compute_internal_var_unwrap(lhs, evaluator, ctx);
-    let r_c = var_cache.get_or_compute_internal_var_unwrap(rhs, evaluator, ctx);
-    let result =
-        evaluate_expression(cond.expression(), l_c.expression(), r_c.expression(), evaluator);
-    Some(result.into())
-}
-
-pub(super) fn evaluate_expression(
-    condition: &Expression,
-    lhs: &Expression,
-    rhs: &Expression,
-    evaluator: &mut Evaluator,
-) -> Expression {
-    let sub = constraints::subtract(lhs, FieldElement::one(), rhs);
-    constraints::add(
-        &constraints::mul_with_witness(evaluator, condition, &sub),
-        FieldElement::one(),
-        rhs,
-    )
-}
diff --git a/crates/noirc_evaluator/src/ssa/acir_gen/operations/constrain.rs b/crates/noirc_evaluator/src/ssa/acir_gen/operations/constrain.rs
deleted file mode 100644
index 1906c0c7f50..00000000000
--- a/crates/noirc_evaluator/src/ssa/acir_gen/operations/constrain.rs
+++ /dev/null
@@ -1,25 +0,0 @@
-use acvm::{
-    acir::circuit::opcodes::Opcode as AcirOpcode, acir::native_types::Expression, FieldElement,
-};
-
-use crate::{
-    ssa::{
-        acir_gen::{constraints, internal_var_cache::InternalVarCache, InternalVar},
-        context::SsaContext,
-        node::NodeId,
-    },
-    Evaluator,
-};
-
-pub(crate) fn evaluate(
-    value: &NodeId,
-    var_cache: &mut InternalVarCache,
-    evaluator: &mut Evaluator,
-    ctx: &SsaContext,
-) -> Option<InternalVar> {
-    let value = var_cache.get_or_compute_internal_var_unwrap(*value, evaluator, ctx);
-    let subtract =
-        constraints::subtract(&Expression::one(), FieldElement::one(), value.expression());
-    evaluator.push_opcode(AcirOpcode::Arithmetic(subtract));
-    Some(value)
-}
diff --git a/crates/noirc_evaluator/src/ssa/acir_gen/operations/intrinsics.rs b/crates/noirc_evaluator/src/ssa/acir_gen/operations/intrinsics.rs
deleted file mode 100644
index 1e003f105b6..00000000000
--- a/crates/noirc_evaluator/src/ssa/acir_gen/operations/intrinsics.rs
+++ /dev/null
@@ -1,437 +0,0 @@
-use crate::{
-    ssa::{
-        acir_gen::{
-            constraints::{bound_constraint_with_offset, to_radix_base},
-            operations::sort::evaluate_permutation,
-            Acir, AcirMem, InternalVar, InternalVarCache,
-        },
-        builtin,
-        context::SsaContext,
-        mem::Memory,
-        node::{self, Instruction, Node, NodeId, ObjectType},
-    },
-    Evaluator,
-};
-use acvm::{
-    acir::{
-        circuit::{
-            directives::{Directive, LogInfo},
-            opcodes::{BlackBoxFuncCall, FunctionInput, Opcode as AcirOpcode},
-        },
-        native_types::{Expression, Witness},
-        BlackBoxFunc,
-    },
-    FieldElement,
-};
-use iter_extended::vecmap;
-
-// Generate constraints for two types of functions:
-// - Builtin functions: These are functions that
-// are implemented by the compiler.
-// - ACIR black box functions. These are referred
-// to as `LowLevel`
-pub(crate) fn evaluate(
-    args: &[NodeId],
-    instruction: &Instruction,
-    opcode: builtin::Opcode,
-    acir_gen: &mut Acir,
-    ctx: &SsaContext,
-    evaluator: &mut Evaluator,
-) -> Option<InternalVar> {
-    use builtin::Opcode;
-
-    let instruction_id = instruction.id;
-    let res_type = instruction.res_type;
-
-    let outputs;
-    match opcode {
-        Opcode::ToBits(endianness) => {
-            // TODO: document where `0` and `1` are coming from, for args[0], args[1]
-            let bit_size = ctx.get_as_constant(args[1]).unwrap().to_u128() as u32;
-            let l_c =
-                acir_gen.var_cache.get_or_compute_internal_var_unwrap(args[0], evaluator, ctx);
-            outputs = to_radix_base(l_c.expression(), 2, bit_size, endianness, evaluator);
-            if let ObjectType::ArrayPointer(a) = res_type {
-                acir_gen.memory.map_array(a, &outputs, ctx);
-            }
-        }
-        Opcode::ToRadix(endianness) => {
-            // TODO: document where `0`, `1` and `2` are coming from, for args[0],args[1], args[2]
-            let radix = ctx.get_as_constant(args[1]).unwrap().to_u128() as u32;
-            let limb_size = ctx.get_as_constant(args[2]).unwrap().to_u128() as u32;
-            let l_c =
-                acir_gen.var_cache.get_or_compute_internal_var_unwrap(args[0], evaluator, ctx);
-            outputs = to_radix_base(l_c.expression(), radix, limb_size, endianness, evaluator);
-            if let ObjectType::ArrayPointer(a) = res_type {
-                acir_gen.memory.map_array(a, &outputs, ctx);
-            }
-        }
-        Opcode::Println(print_info) => {
-            outputs = Vec::new(); // print statements do not output anything
-            if print_info.show_output {
-                evaluate_println(
-                    &mut acir_gen.var_cache,
-                    &mut acir_gen.memory,
-                    print_info.is_string_output,
-                    args,
-                    ctx,
-                    evaluator,
-                );
-            }
-        }
-        Opcode::LowLevel(op) => {
-            outputs = match op {
-                BlackBoxFunc::SHA256 | BlackBoxFunc::Blake2s => {
-                    prepare_outputs(&mut acir_gen.memory, instruction_id, 32, ctx, evaluator)
-                }
-                BlackBoxFunc::Keccak256 => {
-                    prepare_outputs(&mut acir_gen.memory, instruction_id, 32, ctx, evaluator)
-                }
-                BlackBoxFunc::Pedersen | BlackBoxFunc::FixedBaseScalarMul => {
-                    prepare_outputs(&mut acir_gen.memory, instruction_id, 2, ctx, evaluator)
-                }
-                BlackBoxFunc::SchnorrVerify
-                | BlackBoxFunc::EcdsaSecp256k1
-                | BlackBoxFunc::EcdsaSecp256r1
-                | BlackBoxFunc::HashToField128Security => {
-                    prepare_outputs(&mut acir_gen.memory, instruction_id, 1, ctx, evaluator)
-                }
-                // There are some low level functions that have variable outputs and
-                // should not have a set output count in Noir
-                BlackBoxFunc::RecursiveAggregation => {
-                    prepare_outputs_no_count(&mut acir_gen.memory, instruction_id, ctx, evaluator)
-                }
-                _ => panic!("Unsupported low level function {:?}", op),
-            };
-            let func_call = match op {
-                BlackBoxFunc::SHA256 => BlackBoxFuncCall::SHA256 {
-                    inputs: resolve_array(&args[0], acir_gen, ctx, evaluator),
-                    outputs: outputs.to_vec(),
-                },
-                BlackBoxFunc::Blake2s => BlackBoxFuncCall::Blake2s {
-                    inputs: resolve_array(&args[0], acir_gen, ctx, evaluator),
-                    outputs: outputs.to_vec(),
-                },
-                BlackBoxFunc::Keccak256 => {
-                    let msg_size = acir_gen
-                        .var_cache
-                        .get_or_compute_internal_var(args[1], evaluator, ctx)
-                        .expect("ICE - could not get an expression for keccak message size");
-                    let witness =
-                        acir_gen.var_cache.get_or_compute_witness_unwrap(msg_size, evaluator, ctx);
-                    let var_message_size = FunctionInput { witness, num_bits: 32 };
-                    BlackBoxFuncCall::Keccak256VariableLength {
-                        inputs: resolve_array(&args[0], acir_gen, ctx, evaluator),
-                        var_message_size,
-                        outputs: outputs.to_vec(),
-                    }
-                }
-                BlackBoxFunc::Pedersen => {
-                    let separator =
-                        ctx.get_as_constant(args[1]).expect("domain separator to be comptime");
-                    BlackBoxFuncCall::Pedersen {
-                        inputs: resolve_array(&args[0], acir_gen, ctx, evaluator),
-                        outputs: (outputs[0], outputs[1]),
-                        domain_separator: separator.to_u128() as u32,
-                    }
-                }
-                BlackBoxFunc::FixedBaseScalarMul => BlackBoxFuncCall::FixedBaseScalarMul {
-                    input: resolve_variable(&args[0], acir_gen, ctx, evaluator).unwrap(),
-                    outputs: (outputs[0], outputs[1]),
-                },
-                BlackBoxFunc::SchnorrVerify => BlackBoxFuncCall::SchnorrVerify {
-                    public_key_x: resolve_variable(&args[0], acir_gen, ctx, evaluator).unwrap(),
-                    public_key_y: resolve_variable(&args[1], acir_gen, ctx, evaluator).unwrap(),
-                    signature: resolve_array(&args[2], acir_gen, ctx, evaluator),
-                    message: resolve_array(&args[3], acir_gen, ctx, evaluator),
-                    output: outputs[0],
-                },
-                BlackBoxFunc::EcdsaSecp256k1 => BlackBoxFuncCall::EcdsaSecp256k1 {
-                    public_key_x: resolve_array(&args[0], acir_gen, ctx, evaluator),
-                    public_key_y: resolve_array(&args[1], acir_gen, ctx, evaluator),
-                    signature: resolve_array(&args[2], acir_gen, ctx, evaluator),
-                    hashed_message: resolve_array(&args[3], acir_gen, ctx, evaluator),
-                    output: outputs[0],
-                },
-                BlackBoxFunc::EcdsaSecp256r1 => BlackBoxFuncCall::EcdsaSecp256r1 {
-                    public_key_x: resolve_array(&args[0], acir_gen, ctx, evaluator),
-                    public_key_y: resolve_array(&args[1], acir_gen, ctx, evaluator),
-                    signature: resolve_array(&args[2], acir_gen, ctx, evaluator),
-                    hashed_message: resolve_array(&args[3], acir_gen, ctx, evaluator),
-                    output: outputs[0],
-                },
-                BlackBoxFunc::HashToField128Security => BlackBoxFuncCall::HashToField128Security {
-                    inputs: resolve_array(&args[0], acir_gen, ctx, evaluator),
-                    output: outputs[0],
-                },
-                BlackBoxFunc::RecursiveAggregation => {
-                    let has_previous_aggregation = evaluator.opcodes.iter().any(|op| {
-                        matches!(
-                            op,
-                            AcirOpcode::BlackBoxFuncCall(
-                                BlackBoxFuncCall::RecursiveAggregation { .. }
-                            )
-                        )
-                    });
-
-                    let input_aggregation_object = if !has_previous_aggregation {
-                        None
-                    } else {
-                        Some(resolve_array(&args[4], acir_gen, ctx, evaluator))
-                    };
-
-                    BlackBoxFuncCall::RecursiveAggregation {
-                        verification_key: resolve_array(&args[0], acir_gen, ctx, evaluator),
-                        proof: resolve_array(&args[1], acir_gen, ctx, evaluator),
-                        public_inputs: resolve_array(&args[2], acir_gen, ctx, evaluator),
-                        key_hash: resolve_variable(&args[3], acir_gen, ctx, evaluator).unwrap(),
-                        input_aggregation_object,
-                        output_aggregation_object: outputs.to_vec(),
-                    }
-                }
-                _ => panic!("Unsupported low level function {:?}", op),
-            };
-            evaluator.opcodes.push(AcirOpcode::BlackBoxFuncCall(func_call));
-        }
-        Opcode::Sort => {
-            let mut in_expr = Vec::new();
-            let array_id = Memory::deref(ctx, args[0]).unwrap();
-            let array = &ctx.mem[array_id];
-            let num_bits = array.element_type.bits();
-            for i in 0..array.len {
-                in_expr.push(
-                    acir_gen
-                        .memory
-                        .load_array_element_constant_index(array, i)
-                        .unwrap()
-                        .to_expression(),
-                );
-            }
-            outputs =
-                prepare_outputs(&mut acir_gen.memory, instruction_id, array.len, ctx, evaluator);
-            let out_expr: Vec<Expression> = outputs.iter().map(|w| (*w).into()).collect();
-            for i in 0..(out_expr.len() - 1) {
-                bound_constraint_with_offset(
-                    &out_expr[i],
-                    &out_expr[i + 1],
-                    &Expression::zero(),
-                    num_bits,
-                    evaluator,
-                );
-            }
-            let bits = evaluate_permutation(&in_expr, &out_expr, evaluator);
-            let inputs = in_expr.iter().map(|a| vec![a.clone()]).collect();
-            evaluator.push_opcode(AcirOpcode::Directive(Directive::PermutationSort {
-                inputs,
-                tuple: 1,
-                bits,
-                sort_by: vec![0],
-            }));
-            if let node::ObjectType::ArrayPointer(a) = res_type {
-                acir_gen.memory.map_array(a, &outputs, ctx);
-            } else {
-                unreachable!();
-            }
-        }
-    }
-
-    // If more than witness is returned,
-    // the result is inside the result type of `Instruction`
-    // as a pointer to an array
-    (outputs.len() == 1).then(|| InternalVar::from(outputs[0]))
-}
-
-fn resolve_variable(
-    node_id: &NodeId,
-    acir_gen: &mut Acir,
-    cfg: &SsaContext,
-    evaluator: &mut Evaluator,
-) -> Option<FunctionInput> {
-    let node_object = cfg.try_get_node(*node_id).expect("could not find node for {node_id}");
-    match node_object {
-        node::NodeObject::Variable(v) => {
-            Some(FunctionInput { witness: v.witness?, num_bits: v.size_in_bits() })
-        }
-        _ => {
-            // Upon the case that the `NodeObject` is not a `Variable`,
-            // we attempt to fetch an associated `InternalVar`.
-            // Otherwise, this is a internal compiler error.
-            let internal_var = acir_gen.var_cache.get(node_id).expect("invalid input").clone();
-            let witness = acir_gen.var_cache.get_or_compute_witness(internal_var, evaluator)?;
-            Some(FunctionInput { witness, num_bits: node_object.size_in_bits() })
-        }
-    }
-}
-
-fn resolve_array(
-    node_id: &NodeId,
-    acir_gen: &mut Acir,
-    cfg: &SsaContext,
-    evaluator: &mut Evaluator,
-) -> Vec<FunctionInput> {
-    let node_object = cfg.try_get_node(*node_id).expect("could not find node for {node_id}");
-    let array_id = match node_object {
-        node::NodeObject::Variable(_) => {
-            let node_obj_type = node_object.get_type();
-            match node_obj_type {
-                node::ObjectType::ArrayPointer(a) => a,
-                _ => unreachable!(),
-            }
-        }
-        _ => todo!("generate a witness"),
-    };
-    let mut inputs = Vec::new();
-
-    let array = &cfg.mem[array_id];
-    let num_bits = array.element_type.bits();
-    for i in 0..array.len {
-        let mut arr_element = acir_gen
-            .memory
-            .load_array_element_constant_index(array, i)
-            .expect("array index out of bounds");
-        let witness =
-            acir_gen.var_cache.get_or_compute_witness_unwrap(arr_element.clone(), evaluator, cfg);
-        let func_input = FunctionInput { witness, num_bits };
-        arr_element.set_witness(witness);
-        acir_gen.memory.insert(array.id, i, arr_element);
-
-        inputs.push(func_input);
-    }
-
-    inputs
-}
-
-fn prepare_outputs(
-    memory_map: &mut AcirMem,
-    pointer: NodeId,
-    output_nb: u32,
-    ctx: &SsaContext,
-    evaluator: &mut Evaluator,
-) -> Vec<Witness> {
-    // Create fresh variables that will link to the output
-    let outputs = vecmap(0..output_nb, |_| evaluator.add_witness_to_cs());
-
-    let l_obj = ctx.try_get_node(pointer).unwrap();
-    if let node::ObjectType::ArrayPointer(a) = l_obj.get_type() {
-        memory_map.map_array(a, &outputs, ctx);
-    }
-    outputs
-}
-
-fn prepare_outputs_no_count(
-    memory_map: &mut AcirMem,
-    pointer: NodeId,
-    ctx: &SsaContext,
-    evaluator: &mut Evaluator,
-) -> Vec<Witness> {
-    // Create fresh variables that will link to the output
-    let l_obj = ctx.try_get_node(pointer).unwrap();
-    if let node::ObjectType::ArrayPointer(a) = l_obj.get_type() {
-        let mem_array = &ctx.mem[a];
-        let output_nb = mem_array.len;
-        let outputs = vecmap(0..output_nb, |_| evaluator.add_witness_to_cs());
-        memory_map.map_array(a, &outputs, ctx);
-        outputs
-    } else {
-        vec![evaluator.add_witness_to_cs()]
-    }
-}
-
-fn evaluate_println(
-    var_cache: &mut InternalVarCache,
-    memory_map: &mut AcirMem,
-    is_string_output: bool,
-    args: &[NodeId],
-    ctx: &SsaContext,
-    evaluator: &mut Evaluator,
-) {
-    assert_eq!(args.len(), 1, "print statements can only support one argument");
-    let node_id = args[0];
-
-    let mut log_string = "".to_owned();
-    let mut log_witnesses = Vec::new();
-
-    let obj_type = ctx.object_type(node_id);
-    match obj_type {
-        ObjectType::ArrayPointer(array_id) => {
-            let mem_array = &ctx.mem[array_id];
-            let mut field_elements = Vec::new();
-            for idx in 0..mem_array.len {
-                let var = memory_map
-                    .load_array_element_constant_index(mem_array, idx)
-                    .expect("array element being logged does not exist in memory");
-                let array_elem_expr = var.expression();
-                if array_elem_expr.is_const() {
-                    field_elements.push(array_elem_expr.q_c);
-                } else {
-                    let var = match var_cache.get(&node_id) {
-                        Some(var) => var.clone(),
-                        _ => InternalVar::from(array_elem_expr.clone()),
-                    };
-                    let w = var
-                        .cached_witness()
-                        .expect("array element to be logged is missing a witness");
-                    log_witnesses.push(w);
-                }
-            }
-
-            if is_string_output {
-                let final_string = noirc_abi::decode_string_value(&field_elements);
-                log_string.push_str(&final_string);
-            } else if !field_elements.is_empty() {
-                let fields = vecmap(field_elements, format_field_string);
-                log_string = format!("[{}]", fields.join(", "));
-            }
-        }
-        _ => match ctx.get_as_constant(node_id) {
-            Some(field) => {
-                log_string = format_field_string(field);
-            }
-            None => {
-                let var = var_cache
-                    .get(&node_id)
-                    .unwrap_or_else(|| {
-                        panic!(
-                            "invalid input for print statement: {:?}",
-                            ctx.try_get_node(node_id).expect("node is missing from SSA")
-                        )
-                    })
-                    .clone();
-                if let Some(field) = var.to_const() {
-                    log_string = format_field_string(field);
-                } else if let Some(w) = var_cache.get_or_compute_witness(var, evaluator) {
-                    // We check whether there has already been a cached witness for this node. If not, we generate a new witness and include it in the logs
-                    // TODO we need a witness because of the directive, but we should use an expression
-                    log_witnesses.push(w);
-                } else {
-                    unreachable!(
-                        "a witness should have been computed for the non-constant expression"
-                    );
-                }
-            }
-        },
-    };
-
-    // Only one of the witness vector or the output string should be non-empty
-    assert!(log_witnesses.is_empty() ^ log_string.is_empty());
-
-    let log_directive = if !log_string.is_empty() {
-        Directive::Log(LogInfo::FinalizedOutput(log_string))
-    } else {
-        Directive::Log(LogInfo::WitnessOutput(log_witnesses))
-    };
-
-    evaluator.opcodes.push(AcirOpcode::Directive(log_directive));
-}
-
-/// This trims any leading zeroes.
-/// A singular '0' will be prepended as well if the trimmed string has an odd length.
-/// A hex string's length needs to be even to decode into bytes, as two digits correspond to
-/// one byte.
-fn format_field_string(field: FieldElement) -> String {
-    let mut trimmed_field = field.to_hex().trim_start_matches('0').to_owned();
-    if trimmed_field.len() % 2 != 0 {
-        trimmed_field = "0".to_owned() + &trimmed_field;
-    };
-    "0x".to_owned() + &trimmed_field
-}
diff --git a/crates/noirc_evaluator/src/ssa/acir_gen/operations/load.rs b/crates/noirc_evaluator/src/ssa/acir_gen/operations/load.rs
deleted file mode 100644
index f2580c43f59..00000000000
--- a/crates/noirc_evaluator/src/ssa/acir_gen/operations/load.rs
+++ /dev/null
@@ -1,62 +0,0 @@
-use acvm::acir::native_types::Expression;
-use noirc_errors::Location;
-
-use crate::{
-    errors::{RuntimeError, RuntimeErrorKind},
-    ssa::{
-        acir_gen::{acir_mem::AcirMem, internal_var_cache::InternalVarCache, InternalVar},
-        context::SsaContext,
-        mem::{self, ArrayId, MemArray},
-        node::NodeId,
-    },
-    Evaluator,
-};
-
-// Returns a variable corresponding to the element at the provided index in the array
-// Returns an error if index is constant and out-of-bound.
-pub(crate) fn evaluate(
-    array_id: ArrayId,
-    index: NodeId,
-    acir_mem: &mut AcirMem,
-    var_cache: &mut InternalVarCache,
-    location: Option<Location>,
-    evaluator: &mut Evaluator,
-    ctx: &SsaContext,
-) -> Result<InternalVar, RuntimeError> {
-    let mem_array = &ctx.mem[array_id];
-    let index = var_cache.get_or_compute_internal_var_unwrap(index, evaluator, ctx);
-    evaluate_with(mem_array, &index, acir_mem, location, evaluator)
-}
-
-// Same as evaluate(), but using MemArray and InternalVar instead of ArrayId and NodeId
-pub(crate) fn evaluate_with(
-    array: &MemArray,
-    index: &InternalVar,
-    acir_mem: &mut AcirMem,
-    location: Option<Location>,
-    evaluator: &mut Evaluator,
-) -> Result<InternalVar, RuntimeError> {
-    if let Some(idx) = index.to_const() {
-        let idx = mem::Memory::as_u32(idx);
-        // Check to see if the index has gone out of bounds
-        let array_length = array.len;
-        if idx >= array_length {
-            return Err(RuntimeError {
-                location,
-                kind: RuntimeErrorKind::ArrayOutOfBounds {
-                    index: idx as u128,
-                    bound: array_length as u128,
-                },
-            });
-        }
-
-        let array_element = acir_mem.load_array_element_constant_index(array, idx);
-        if let Some(element) = array_element {
-            return Ok(element);
-        }
-    }
-
-    let w = evaluator.add_witness_to_cs();
-    acir_mem.add_to_trace(&array.id, index.to_expression(), w.into(), Expression::zero());
-    Ok(InternalVar::from_witness(w))
-}
diff --git a/crates/noirc_evaluator/src/ssa/acir_gen/operations/not.rs b/crates/noirc_evaluator/src/ssa/acir_gen/operations/not.rs
deleted file mode 100644
index 76ad7c93a88..00000000000
--- a/crates/noirc_evaluator/src/ssa/acir_gen/operations/not.rs
+++ /dev/null
@@ -1,28 +0,0 @@
-use crate::{
-    ssa::{
-        acir_gen::{constraints, internal_var_cache::InternalVarCache, InternalVar},
-        context::SsaContext,
-        node::{NodeId, ObjectType},
-    },
-    Evaluator,
-};
-use acvm::{acir::native_types::Expression, FieldElement};
-
-pub(crate) fn evaluate(
-    value: &NodeId,
-    res_type: ObjectType,
-    var_cache: &mut InternalVarCache,
-    evaluator: &mut Evaluator,
-    ctx: &SsaContext,
-) -> Option<InternalVar> {
-    let a = (1_u128 << res_type.bits()) - 1;
-    let l_c = var_cache.get_or_compute_internal_var_unwrap(*value, evaluator, ctx);
-    Some(
-        constraints::subtract(
-            &Expression::from(FieldElement::from(a)),
-            FieldElement::one(),
-            l_c.expression(),
-        )
-        .into(),
-    )
-}
diff --git a/crates/noirc_evaluator/src/ssa/acir_gen/operations/return.rs b/crates/noirc_evaluator/src/ssa/acir_gen/operations/return.rs
deleted file mode 100644
index c3e935a1065..00000000000
--- a/crates/noirc_evaluator/src/ssa/acir_gen/operations/return.rs
+++ /dev/null
@@ -1,65 +0,0 @@
-use acvm::acir::native_types::Expression;
-
-use crate::{
-    errors::RuntimeErrorKind,
-    ssa::{
-        acir_gen::{acir_mem::AcirMem, internal_var_cache::InternalVarCache, InternalVar},
-        context::SsaContext,
-        mem::Memory,
-        node::NodeId,
-    },
-    Evaluator,
-};
-
-pub(crate) fn evaluate(
-    node_ids: &[NodeId],
-    memory_map: &mut AcirMem,
-    var_cache: &mut InternalVarCache,
-    evaluator: &mut Evaluator,
-    ctx: &SsaContext,
-) -> Result<Option<InternalVar>, RuntimeErrorKind> {
-    // XXX: When we return a node_id that was created from
-    // the UnitType, there is a witness associated with it
-    // Ideally no witnesses are created for such types.
-
-    // This can only ever be called in the main context.
-    // In all other context's, the return operation is transformed.
-
-    for node_id in node_ids {
-        // An array produces a single node_id
-        // We therefore need to check if the node_id is referring to an array
-        // and deference to get the elements
-        let objects = match Memory::deref(ctx, *node_id) {
-            Some(a) => {
-                let array = &ctx.mem[a];
-                memory_map.return_array(a);
-                memory_map.load_array(array, evaluator)
-            }
-            None => {
-                vec![var_cache.get_or_compute_internal_var_unwrap(*node_id, evaluator, ctx)]
-            }
-        };
-
-        for object in objects {
-            let witness = var_cache.get_or_compute_witness_unwrap(object, evaluator, ctx);
-            // Before pushing to the public inputs, we need to check that
-            // it was not a private ABI input
-            if evaluator.is_private_abi_input(witness) {
-                return Err(RuntimeErrorKind::Spanless(String::from(
-                    "we do not allow private ABI inputs to be returned as public outputs",
-                )));
-            }
-            // Check if the outputted witness needs separating from an existing occurrence in the
-            // abi. This behavior stems from usage of the `distinct` keyword.
-            let return_witness = if evaluator.should_proxy_witness_for_abi_output(witness) {
-                let proxy_constraint = Expression::from(witness);
-                evaluator.create_intermediate_variable(proxy_constraint)
-            } else {
-                witness
-            };
-            evaluator.return_values.push(return_witness);
-        }
-    }
-
-    Ok(None)
-}
diff --git a/crates/noirc_evaluator/src/ssa/acir_gen/operations/sort.rs b/crates/noirc_evaluator/src/ssa/acir_gen/operations/sort.rs
deleted file mode 100644
index e3577610c55..00000000000
--- a/crates/noirc_evaluator/src/ssa/acir_gen/operations/sort.rs
+++ /dev/null
@@ -1,210 +0,0 @@
-use acvm::{
-    acir::native_types::Expression,
-    acir::{circuit::opcodes::Opcode as AcirOpcode, native_types::Witness},
-    FieldElement,
-};
-
-use crate::{
-    ssa::acir_gen::constraints::{add, mul_with_witness, subtract},
-    Evaluator,
-};
-
-// Generate gates which ensure that out_expr is a permutation of in_expr
-// Returns the control bits of the sorting network used to generate the constrains
-pub(crate) fn evaluate_permutation(
-    in_expr: &[Expression],
-    out_expr: &[Expression],
-    evaluator: &mut Evaluator,
-) -> Vec<Witness> {
-    let bits = Vec::new();
-    let (w, b) = permutation_layer(in_expr, &bits, true, evaluator);
-    // we constrain the network output to out_expr
-    for (b, o) in b.iter().zip(out_expr) {
-        evaluator.push_opcode(AcirOpcode::Arithmetic(subtract(b, FieldElement::one(), o)));
-    }
-    w
-}
-
-// Same as evaluate_permutation() but uses the provided witness as network control bits
-pub(crate) fn evaluate_permutation_with_witness(
-    in_expr: &[Expression],
-    out_expr: &[Expression],
-    bits: &[Witness],
-    evaluator: &mut Evaluator,
-) {
-    let (w, b) = permutation_layer(in_expr, bits, false, evaluator);
-    debug_assert_eq!(w, *bits);
-    // we constrain the network output to out_expr
-    for (b, o) in b.iter().zip(out_expr) {
-        evaluator.opcodes.push(AcirOpcode::Arithmetic(subtract(b, FieldElement::one(), o)));
-    }
-}
-
-// Generates gates for a sorting network
-// returns witness corresponding to the network configuration and the expressions corresponding to the network output
-// in_expr: inputs of the sorting network
-// if generate_witness is false, it uses the witness provided in bits instead of generating them
-// in both cases it returns the witness of the network configuration
-// if generate_witness is true, bits is ignored
-fn permutation_layer(
-    in_expr: &[Expression],
-    bits: &[Witness],
-    generate_witness: bool,
-    evaluator: &mut Evaluator,
-) -> (Vec<Witness>, Vec<Expression>) {
-    let n = in_expr.len();
-    if n == 1 {
-        return (Vec::new(), in_expr.to_vec());
-    }
-    let n1 = n / 2;
-
-    // witness for the input switches
-    let mut conf = iter_extended::vecmap(0..n1, |i| {
-        if generate_witness {
-            evaluator.add_witness_to_cs()
-        } else {
-            bits[i]
-        }
-    });
-
-    // compute expressions after the input switches
-    // If inputs are a1,a2, and the switch value is c, then we compute expressions b1,b2 where
-    // b1 = a1+q, b2 = a2-q, q = c(a2-a1)
-    let mut in_sub1 = Vec::new();
-    let mut in_sub2 = Vec::new();
-    for i in 0..n1 {
-        //q = c*(a2-a1);
-        let intermediate = mul_with_witness(
-            evaluator,
-            &conf[i].into(),
-            &subtract(&in_expr[2 * i + 1], FieldElement::one(), &in_expr[2 * i]),
-        );
-        //b1=a1+q
-        in_sub1.push(add(&intermediate, FieldElement::one(), &in_expr[2 * i]));
-        //b2=a2-q
-        in_sub2.push(subtract(&in_expr[2 * i + 1], FieldElement::one(), &intermediate));
-    }
-    if n % 2 == 1 {
-        in_sub2.push(in_expr.last().unwrap().clone());
-    }
-    let mut out_expr = Vec::new();
-    // compute results for the sub networks
-    let bits1 = if generate_witness { bits } else { &bits[n1 + (n - 1) / 2..] };
-    let (w1, b1) = permutation_layer(&in_sub1, bits1, generate_witness, evaluator);
-    let bits2 = if generate_witness { bits } else { &bits[n1 + (n - 1) / 2 + w1.len()..] };
-    let (w2, b2) = permutation_layer(&in_sub2, bits2, generate_witness, evaluator);
-    // apply the output switches
-    for i in 0..(n - 1) / 2 {
-        let c = if generate_witness { evaluator.add_witness_to_cs() } else { bits[n1 + i] };
-        conf.push(c);
-        let intermediate =
-            mul_with_witness(evaluator, &c.into(), &subtract(&b2[i], FieldElement::one(), &b1[i]));
-        out_expr.push(add(&intermediate, FieldElement::one(), &b1[i]));
-        out_expr.push(subtract(&b2[i], FieldElement::one(), &intermediate));
-    }
-    if n % 2 == 0 {
-        out_expr.push(b1.last().unwrap().clone());
-    }
-    out_expr.push(b2.last().unwrap().clone());
-    conf.extend(w1);
-    conf.extend(w2);
-    (conf, out_expr)
-}
-
-#[cfg(test)]
-mod test {
-    use acvm::{
-        acir::native_types::WitnessMap,
-        pwg::{ACVMStatus, ACVM},
-        BlackBoxFunctionSolver, BlackBoxResolutionError, FieldElement,
-    };
-
-    use crate::{
-        ssa::acir_gen::operations::sort::{evaluate_permutation, permutation_layer},
-        Evaluator,
-    };
-    use rand::prelude::*;
-
-    struct MockBackend {}
-    impl BlackBoxFunctionSolver for MockBackend {
-        fn schnorr_verify(
-            &self,
-            _public_key_x: &FieldElement,
-            _public_key_y: &FieldElement,
-            _signature: &[u8],
-            _message: &[u8],
-        ) -> Result<bool, BlackBoxResolutionError> {
-            panic!("Path not trodden by this test")
-        }
-        fn pedersen(
-            &self,
-            _inputs: &[FieldElement],
-            _domain_separator: u32,
-        ) -> Result<(FieldElement, FieldElement), BlackBoxResolutionError> {
-            panic!("Path not trodden by this test")
-        }
-        fn fixed_base_scalar_mul(
-            &self,
-            _input: &FieldElement,
-        ) -> Result<(FieldElement, FieldElement), BlackBoxResolutionError> {
-            panic!("Path not trodden by this test")
-        }
-    }
-
-    // Check that a random network constrains its output to be a permutation of any random input
-    #[test]
-    fn test_permutation() {
-        let mut rng = rand::thread_rng();
-        for n in 2..50 {
-            let mut eval = Evaluator::default();
-
-            //we generate random inputs
-            let mut input = Vec::new();
-            let mut a_val = Vec::new();
-            let mut b_wit = Vec::new();
-            let mut initial_witness = WitnessMap::new();
-            for i in 0..n {
-                let w = eval.add_witness_to_cs();
-                input.push(w.into());
-                a_val.push(FieldElement::from(rng.next_u32() as i128));
-                initial_witness.insert(w, a_val[i]);
-            }
-
-            let mut output = Vec::new();
-            for _i in 0..n {
-                let w = eval.add_witness_to_cs();
-                b_wit.push(w);
-                output.push(w.into());
-            }
-            //generate constraints for the inputs
-            let w = evaluate_permutation(&input, &output, &mut eval);
-            //checks that it generate the same witness
-            let (w1, _) = permutation_layer(&input, &w, false, &mut eval);
-            assert_eq!(w, w1);
-            //we generate random network
-            let mut c = Vec::new();
-            for _i in 0..w.len() {
-                c.push(rng.next_u32() % 2 != 0);
-            }
-            // initialize bits
-            for i in 0..w.len() {
-                initial_witness.insert(w[i], FieldElement::from(c[i] as i128));
-            }
-            // compute the network output by solving the constraints
-            let backend = MockBackend {};
-            let mut acvm = ACVM::new(backend, eval.opcodes.clone(), initial_witness);
-            let solver_status = acvm.solve();
-            assert_eq!(solver_status, ACVMStatus::Solved, "Incomplete solution");
-            let solved_witness = acvm.finalize();
-
-            let mut b_val = Vec::new();
-            for i in 0..output.len() {
-                b_val.push(solved_witness[&b_wit[i]]);
-            }
-            // ensure the outputs are a permutation of the inputs
-            a_val.sort();
-            b_val.sort();
-            assert_eq!(a_val, b_val);
-        }
-    }
-}
diff --git a/crates/noirc_evaluator/src/ssa/acir_gen/operations/store.rs b/crates/noirc_evaluator/src/ssa/acir_gen/operations/store.rs
deleted file mode 100644
index b6733ef5227..00000000000
--- a/crates/noirc_evaluator/src/ssa/acir_gen/operations/store.rs
+++ /dev/null
@@ -1,70 +0,0 @@
-use acvm::acir::native_types::Expression;
-
-use crate::{
-    errors::RuntimeError,
-    ssa::{
-        acir_gen::{
-            acir_mem::AcirMem,
-            internal_var_cache::InternalVarCache,
-            operations::{condition, load},
-            InternalVar,
-        },
-        context::SsaContext,
-        mem,
-        node::Operation,
-    },
-    Evaluator,
-};
-
-pub(crate) fn evaluate(
-    store: &Operation,
-    acir_mem: &mut AcirMem,
-    var_cache: &mut InternalVarCache,
-    evaluator: &mut Evaluator,
-    ctx: &SsaContext,
-) -> Result<Option<InternalVar>, RuntimeError> {
-    if let Operation::Store { array_id, index, value, predicate, .. } = *store {
-        //maps the address to the rhs if address is known at compile time
-        let index_var = var_cache.get_or_compute_internal_var_unwrap(index, evaluator, ctx);
-        let value_var = var_cache.get_or_compute_internal_var_unwrap(value, evaluator, ctx);
-        let value_with_predicate = if let Some(predicate) = predicate {
-            if predicate.is_dummy() || ctx.is_one(predicate) {
-                value_var
-            } else if ctx.is_zero(predicate) {
-                return Ok(None);
-            } else {
-                let pred = var_cache.get_or_compute_internal_var_unwrap(predicate, evaluator, ctx);
-                let dummy_load =
-                    load::evaluate(array_id, index, acir_mem, var_cache, None, evaluator, ctx)?;
-                let result = condition::evaluate_expression(
-                    pred.expression(),
-                    value_var.expression(),
-                    dummy_load.expression(),
-                    evaluator,
-                );
-                result.into()
-            }
-        } else {
-            value_var
-        };
-
-        match index_var.to_const() {
-            Some(idx) => {
-                let idx = mem::Memory::as_u32(idx);
-                acir_mem.insert(array_id, idx, value_with_predicate);
-            }
-            None => {
-                acir_mem.add_to_trace(
-                    &array_id,
-                    index_var.to_expression(),
-                    value_with_predicate.to_expression(),
-                    Expression::one(),
-                );
-            }
-        }
-    } else {
-        unreachable!("Expected store, got {:?}", store.opcode());
-    }
-    //we do not generate constraint, so no output.
-    Ok(None)
-}
diff --git a/crates/noirc_evaluator/src/ssa/acir_gen/operations/truncate.rs b/crates/noirc_evaluator/src/ssa/acir_gen/operations/truncate.rs
deleted file mode 100644
index 1f99df2ca17..00000000000
--- a/crates/noirc_evaluator/src/ssa/acir_gen/operations/truncate.rs
+++ /dev/null
@@ -1,25 +0,0 @@
-use crate::{
-    ssa::{
-        acir_gen::{constraints, internal_var_cache::InternalVarCache, InternalVar},
-        context::SsaContext,
-        node::NodeId,
-    },
-    Evaluator,
-};
-
-pub(crate) fn evaluate(
-    value: &NodeId,
-    bit_size: u32,
-    max_bit_size: u32,
-    var_cache: &mut InternalVarCache,
-    evaluator: &mut Evaluator,
-    ctx: &SsaContext,
-) -> Option<InternalVar> {
-    let value = var_cache.get_or_compute_internal_var_unwrap(*value, evaluator, ctx);
-    Some(InternalVar::from_expression(constraints::evaluate_truncate(
-        value.expression(),
-        bit_size,
-        max_bit_size,
-        evaluator,
-    )))
-}
diff --git a/crates/noirc_evaluator/src/ssa/anchor.rs b/crates/noirc_evaluator/src/ssa/anchor.rs
deleted file mode 100644
index 53edc19ec4d..00000000000
--- a/crates/noirc_evaluator/src/ssa/anchor.rs
+++ /dev/null
@@ -1,300 +0,0 @@
-use crate::errors::RuntimeErrorKind;
-use crate::ssa::{
-    conditional::DecisionTree,
-    context::SsaContext,
-    mem::ArrayId,
-    node::{NodeId, ObjectType, Opcode, Operation},
-};
-use std::collections::{HashMap, VecDeque};
-
-#[derive(Clone, Debug)]
-pub(super) enum MemItem {
-    NonConst(NodeId),
-    Const(usize),     //represent a bunch of memory instructions having constant index
-    ConstLoad(usize), //represent a bunch of load instructions having constant index
-}
-
-#[derive(Debug)]
-pub(super) enum CseAction {
-    ReplaceWith(NodeId),
-    Remove(NodeId),
-    Keep,
-}
-
-/// A list of instructions with the same Operation variant
-#[derive(Default, Clone)]
-pub(super) struct Anchor {
-    map: HashMap<Opcode, HashMap<Operation, NodeId>>, //standard anchor
-    cast_map: HashMap<NodeId, HashMap<ObjectType, NodeId>>, //cast anchor
-    mem_map: HashMap<ArrayId, Vec<VecDeque<(usize, NodeId)>>>, //Memory anchor: one Vec for each array where Vec[i] contains the list of load and store instructions having index i, and the mem_item position in which they appear
-    mem_list: HashMap<ArrayId, VecDeque<MemItem>>, // list of the memory instructions, per array, and grouped into MemItems
-}
-
-impl Anchor {
-    pub(super) fn push_cast_front(
-        &mut self,
-        operation: &Operation,
-        id: NodeId,
-        res_type: ObjectType,
-    ) {
-        match operation {
-            Operation::Cast(cast_id) => {
-                let mut by_type = HashMap::new();
-                by_type.insert(res_type, id);
-                self.cast_map.insert(*cast_id, by_type);
-            }
-            _ => unreachable!(),
-        }
-    }
-
-    pub(super) fn push_front(&mut self, operation: &Operation, id: NodeId) {
-        let op = operation.opcode();
-
-        match operation {
-            Operation::Cast(_) => unreachable!(),
-            _ => {
-                if let std::collections::hash_map::Entry::Vacant(e) = self.map.entry(op) {
-                    let mut prev_list = HashMap::new();
-                    prev_list.insert(operation.clone(), id);
-                    e.insert(prev_list);
-                } else {
-                    self.map.get_mut(&op).unwrap().insert(operation.clone(), id);
-                }
-            }
-        }
-    }
-
-    pub(super) fn find_similar_instruction(&self, operation: &Operation) -> Option<NodeId> {
-        let op = operation.opcode();
-        self.map.get(&op).and_then(|inner| inner.get(operation).copied())
-    }
-
-    pub(super) fn find_similar_cast(
-        &self,
-        ir_gen: &SsaContext,
-        operator: &Operation,
-        res_type: super::node::ObjectType,
-    ) -> Option<NodeId> {
-        match operator {
-            Operation::Cast(id) => {
-                if self.cast_map.contains_key(id) {
-                    let by_type = &self.cast_map[id];
-                    if by_type.contains_key(&res_type) {
-                        let tu = by_type[&res_type];
-                        if let Some(ins) = ir_gen.try_get_instruction(tu) {
-                            if !ins.is_deleted() {
-                                return Some(tu);
-                            }
-                        }
-                    }
-                }
-            }
-            _ => unreachable!(),
-        }
-
-        None
-    }
-
-    fn get_mem_map(&self, a: &ArrayId) -> &Vec<VecDeque<(usize, NodeId)>> {
-        &self.mem_map[a]
-    }
-
-    pub(super) fn get_mem_all(&self, a: ArrayId) -> &VecDeque<MemItem> {
-        &self.mem_list[&a]
-    }
-
-    pub(super) fn use_array(&mut self, a: ArrayId, len: usize) {
-        if !self.mem_list.contains_key(&a) {
-            let def: VecDeque<(usize, NodeId)> = VecDeque::new();
-            self.mem_list.entry(a).or_insert_with(VecDeque::new);
-            self.mem_map.entry(a).or_insert_with(|| vec![def; len]);
-        }
-    }
-
-    pub(super) fn push_mem_instruction(
-        &mut self,
-        ctx: &SsaContext,
-        id: NodeId,
-    ) -> Result<(), RuntimeErrorKind> {
-        let ins = ctx.instruction(id);
-        let (array_id, index, is_load) = Anchor::get_mem_op(&ins.operation);
-        self.use_array(array_id, ctx.mem[array_id].len as usize);
-        let prev_list = self.mem_list.get_mut(&array_id).unwrap();
-        let len = prev_list.len();
-        if let Some(index_value) = ctx.get_as_constant(index) {
-            let mem_idx = index_value.to_u128() as usize;
-            let last_item = prev_list.front();
-            let item_pos = match last_item {
-                Some(MemItem::Const(pos)) => *pos,
-                Some(MemItem::ConstLoad(pos)) => {
-                    if is_load {
-                        *pos
-                    } else {
-                        let item_pos = pos + 1;
-                        prev_list.push_front(MemItem::Const(pos + 1));
-                        item_pos
-                    }
-                }
-                None | Some(MemItem::NonConst(_)) => {
-                    if is_load {
-                        prev_list.push_front(MemItem::ConstLoad(len));
-                    } else {
-                        prev_list.push_front(MemItem::Const(len));
-                    }
-                    len
-                }
-            };
-            let anchor_list = self.get_anchor_list_mut(&array_id, mem_idx)?;
-            anchor_list.push_front((item_pos, id));
-        } else {
-            prev_list.push_front(MemItem::NonConst(id));
-        }
-        Ok(())
-    }
-
-    pub(super) fn find_similar_mem_instruction(
-        &self,
-        ctx: &SsaContext,
-        op: &Operation,
-        prev_ins: &VecDeque<MemItem>,
-    ) -> Result<CseAction, RuntimeErrorKind> {
-        for iter in prev_ins.iter() {
-            if let Some(action) = self.match_mem_item(ctx, iter, op)? {
-                return Ok(action);
-            }
-        }
-
-        Ok(CseAction::Keep)
-    }
-
-    fn get_mem_op(op: &Operation) -> (ArrayId, NodeId, bool) {
-        match op {
-            Operation::Load { array_id, index, .. } => (*array_id, *index, true),
-            Operation::Store { array_id, index, .. } => (*array_id, *index, false),
-            _ => unreachable!(),
-        }
-    }
-
-    fn match_mem_item(
-        &self,
-        ctx: &SsaContext,
-        item: &MemItem,
-        op: &Operation,
-    ) -> Result<Option<CseAction>, RuntimeErrorKind> {
-        let (array_id, index, is_load) = Anchor::get_mem_op(op);
-        if let Some(b_value) = ctx.get_as_constant(index) {
-            match item {
-                MemItem::Const(p) | MemItem::ConstLoad(p) => {
-                    let b_idx = b_value.to_u128() as usize;
-                    let anchor_list = self.get_anchor_list(&array_id, b_idx)?;
-                    for (pos, id) in anchor_list {
-                        if pos == p {
-                            let action = Anchor::match_mem_id(ctx, *id, index, is_load);
-                            if action.is_some() {
-                                return Ok(action);
-                            }
-                        }
-                    }
-
-                    Ok(None)
-                }
-                MemItem::NonConst(id) => Ok(Anchor::match_mem_id(ctx, *id, index, is_load)),
-            }
-        } else {
-            match item {
-                MemItem::Const(_) => Ok(Some(CseAction::Keep)),
-                MemItem::ConstLoad(_) => {
-                    if is_load {
-                        Ok(None)
-                    } else {
-                        Ok(Some(CseAction::Keep))
-                    }
-                }
-                MemItem::NonConst(id) => Ok(Anchor::match_mem_id(ctx, *id, index, is_load)),
-            }
-        }
-    }
-
-    //Returns the anchor list of memory instructions for the array_id at the provided index
-    // It issues an out-of-bound error when the list does not exist at this index.
-    fn get_anchor_list(
-        &self,
-        array_id: &ArrayId,
-        index: usize,
-    ) -> Result<&VecDeque<(usize, NodeId)>, RuntimeErrorKind> {
-        let memory_map = self.get_mem_map(array_id);
-        memory_map.get(index).ok_or(RuntimeErrorKind::ArrayOutOfBounds {
-            index: index as u128,
-            bound: memory_map.len() as u128,
-        })
-    }
-
-    //Same as get_anchor_list() but returns a mutable anchor
-    fn get_anchor_list_mut(
-        &mut self,
-        array_id: &ArrayId,
-        index: usize,
-    ) -> Result<&mut VecDeque<(usize, NodeId)>, RuntimeErrorKind> {
-        let memory_map = self.mem_map.get_mut(array_id).unwrap();
-        let len = memory_map.len() as u128;
-        memory_map
-            .get_mut(index)
-            .ok_or(RuntimeErrorKind::ArrayOutOfBounds { index: index as u128, bound: len })
-    }
-
-    fn match_mem_id(
-        ctx: &SsaContext,
-        a: NodeId,
-        b_idx: NodeId,
-        b_is_load: bool,
-    ) -> Option<CseAction> {
-        if b_is_load {
-            if let Some(ins_iter) = ctx.try_get_instruction(a) {
-                match &ins_iter.operation {
-                    Operation::Load { index, .. } => {
-                        if !ctx.maybe_distinct(*index, b_idx) {
-                            return Some(CseAction::ReplaceWith(a));
-                        }
-                    }
-                    Operation::Store { index, value, predicate, .. } => {
-                        if !ctx.maybe_distinct(*index, b_idx) {
-                            if ctx.is_one(DecisionTree::unwrap_predicate(ctx, predicate)) {
-                                return Some(CseAction::ReplaceWith(*value));
-                            } else {
-                                return Some(CseAction::Keep);
-                            }
-                        }
-                        if ctx.maybe_equal(*index, b_idx) {
-                            return Some(CseAction::Keep);
-                        }
-                    }
-                    _ => {
-                        unreachable!(
-                            "invalid operator in the memory anchor list: {:?}",
-                            ins_iter.operation
-                        )
-                    }
-                }
-            }
-        } else if let Some(ins_iter) = ctx.try_get_instruction(a) {
-            match ins_iter.operation {
-                Operation::Load { index, .. } => {
-                    if ctx.maybe_equal(index, b_idx) {
-                        return Some(CseAction::Keep);
-                    }
-                }
-                Operation::Store { index, .. } => {
-                    if !ctx.maybe_distinct(index, b_idx) {
-                        return Some(CseAction::Remove(a));
-                    }
-                    if ctx.maybe_equal(index, b_idx) {
-                        return Some(CseAction::Keep);
-                    }
-                }
-                _ => unreachable!("invalid operator in the memory anchor list"),
-            }
-        }
-
-        None
-    }
-}
diff --git a/crates/noirc_evaluator/src/ssa/block.rs b/crates/noirc_evaluator/src/ssa/block.rs
deleted file mode 100644
index 26340a4a725..00000000000
--- a/crates/noirc_evaluator/src/ssa/block.rs
+++ /dev/null
@@ -1,618 +0,0 @@
-use crate::errors::RuntimeError;
-use crate::ssa::{
-    conditional::AssumptionId,
-    context::SsaContext,
-    mem::ArrayId,
-    node,
-    node::{Instruction, Mark, NodeId, Opcode},
-};
-use std::collections::{HashMap, HashSet, VecDeque};
-
-// A short-circuited block should not have more than 4 instructions (a nop, an optional not, an optional condition and a failing constraint)
-// so we do not need to check the whole instruction list when looking for short-circuit instructions.
-const MAX_SHORT_CIRCUIT_LEN: usize = 4;
-
-#[derive(PartialEq, Eq, Debug, Clone)]
-pub(crate) enum BlockType {
-    Normal,
-    ForJoin,
-    IfJoin,
-}
-
-#[derive(Debug, Copy, Clone, PartialEq, Eq, Hash)]
-pub(crate) struct BlockId(pub(super) arena::Index);
-
-impl BlockId {
-    pub(super) fn dummy() -> BlockId {
-        BlockId(SsaContext::dummy_id())
-    }
-    pub(super) fn is_dummy(&self) -> bool {
-        *self == BlockId::dummy()
-    }
-}
-
-#[derive(Debug)]
-pub(crate) struct BasicBlock {
-    pub(crate) id: BlockId,
-    pub(crate) kind: BlockType,
-    pub(crate) dominator: Option<BlockId>, //direct dominator
-    pub(crate) dominated: Vec<BlockId>,    //dominated sons
-    pub(crate) predecessor: Vec<BlockId>,  //for computing the dominator tree
-    pub(crate) left: Option<BlockId>,      //sequential successor
-    pub(crate) right: Option<BlockId>,     //jump successor
-    pub(crate) instructions: Vec<NodeId>,
-    pub(crate) value_map: HashMap<NodeId, NodeId>, //for generating the ssa form
-    pub(crate) assumption: AssumptionId,
-}
-
-impl BasicBlock {
-    pub(crate) fn new(prev: BlockId, kind: BlockType) -> BasicBlock {
-        BasicBlock {
-            id: BlockId(SsaContext::dummy_id()),
-            predecessor: vec![prev],
-            left: None,
-            right: None,
-            instructions: Vec::new(),
-            value_map: HashMap::new(),
-            dominator: None,
-            dominated: Vec::new(),
-            kind,
-            assumption: AssumptionId::dummy(),
-        }
-    }
-
-    pub(crate) fn get_current_value(&self, id: NodeId) -> Option<NodeId> {
-        self.value_map.get(&id).copied()
-    }
-
-    //When generating a new instance of a variable because of ssa, we update the value array
-    //to link the two variables
-    pub(crate) fn update_variable(&mut self, old_value: NodeId, new_value: NodeId) {
-        self.value_map.insert(old_value, new_value);
-    }
-
-    pub(crate) fn get_first_instruction(&self) -> NodeId {
-        self.instructions[0]
-    }
-
-    pub(crate) fn is_join(&self) -> bool {
-        self.kind == BlockType::ForJoin
-    }
-
-    //Create the first block for a CFG
-    pub(crate) fn create_cfg(ctx: &mut SsaContext) -> BlockId {
-        let root_block = BasicBlock::new(BlockId::dummy(), BlockType::Normal);
-        let root_block = ctx.insert_block(root_block);
-        root_block.predecessor = Vec::new();
-        let root_id = root_block.id;
-        ctx.current_block = root_id;
-        ctx.sealed_blocks.insert(root_id);
-        ctx.new_instruction(node::Operation::Nop, node::ObjectType::NotAnObject).unwrap();
-        root_id
-    }
-
-    pub(crate) fn written_arrays(&self, ctx: &SsaContext) -> HashSet<ArrayId> {
-        let mut result = HashSet::new();
-        for i in &self.instructions {
-            if let Some(node::Instruction {
-                operation: node::Operation::Store { array_id: x, .. },
-                ..
-            }) = ctx.try_get_instruction(*i)
-            {
-                result.insert(*x);
-            }
-
-            if let Some(ins) = ctx.try_get_instruction(*i) {
-                match &ins.operation {
-                    node::Operation::Store { array_id: a, .. } => {
-                        result.insert(*a);
-                    }
-                    node::Operation::Intrinsic(..) => {
-                        if let node::ObjectType::ArrayPointer(a) = ins.res_type {
-                            result.insert(a);
-                        }
-                    }
-                    node::Operation::Call { func, returned_arrays, .. } => {
-                        for a in returned_arrays {
-                            result.insert(a.0);
-                        }
-                        if let Some(f) = ctx.try_get_ssa_func(*func) {
-                            for typ in &f.result_types {
-                                if let node::ObjectType::ArrayPointer(a) = typ {
-                                    result.insert(*a);
-                                }
-                            }
-                        }
-                    }
-                    _ => (),
-                }
-            }
-        }
-        result
-    }
-
-    //Returns true if the block is a short-circuit
-    fn is_short_circuit(&self, ctx: &SsaContext, assumption: Option<NodeId>) -> bool {
-        let mut cond = None;
-        for (i, ins_id) in self.instructions.iter().enumerate() {
-            if let Some(ins) = ctx.try_get_instruction(*ins_id) {
-                if let Some(ass_value) = assumption {
-                    if cond.is_none()
-                        && ins.operation
-                            == (node::Operation::Cond {
-                                condition: ass_value,
-                                val_true: ctx.zero(),
-                                val_false: ctx.one(),
-                            })
-                    {
-                        cond = Some(*ins_id);
-                    }
-
-                    if let node::Operation::Constrain(a, _) = ins.operation {
-                        if a == ctx.zero() || Some(a) == cond {
-                            return true;
-                        }
-                    }
-                }
-            }
-            if i > MAX_SHORT_CIRCUIT_LEN {
-                break;
-            }
-        }
-
-        false
-    }
-}
-
-pub(crate) fn create_first_block(ctx: &mut SsaContext) {
-    ctx.first_block = BasicBlock::create_cfg(ctx);
-}
-
-//Creates a new sealed block (i.e whose predecessors are known)
-//It is not suitable for the first block because it uses the current block.
-//if left is true, the new block is left to the current block
-pub(crate) fn new_sealed_block(ctx: &mut SsaContext, kind: BlockType, left: bool) -> BlockId {
-    let current_block = ctx.current_block;
-    let new_block = BasicBlock::new(ctx.current_block, kind);
-    let new_block = ctx.insert_block(new_block);
-    let new_id = new_block.id;
-
-    new_block.dominator = Some(current_block);
-    ctx.sealed_blocks.insert(new_id);
-
-    //update current block
-    if left {
-        let cb = ctx.get_current_block_mut();
-        cb.left = Some(new_id);
-    }
-    ctx.current_block = new_id;
-    ctx.new_instruction(node::Operation::Nop, node::ObjectType::NotAnObject).unwrap();
-    new_id
-}
-
-//if left is true, the new block is left to the current block
-pub(crate) fn new_unsealed_block(ctx: &mut SsaContext, kind: BlockType, left: bool) -> BlockId {
-    let current_block = ctx.current_block;
-    let new_block = create_block(ctx, kind);
-    new_block.dominator = Some(current_block);
-    let new_idx = new_block.id;
-
-    //update current block
-    let cb = ctx.get_current_block_mut();
-    if left {
-        cb.left = Some(new_idx);
-    } else {
-        cb.right = Some(new_idx);
-    }
-
-    ctx.current_block = new_idx;
-    ctx.new_instruction(node::Operation::Nop, node::ObjectType::NotAnObject).unwrap();
-    new_idx
-}
-
-//create a block and sets its id, but do not update current block, and do not add dummy instruction!
-pub(crate) fn create_block(ctx: &mut SsaContext, kind: BlockType) -> &mut BasicBlock {
-    let new_block = BasicBlock::new(ctx.current_block, kind);
-    ctx.insert_block(new_block)
-}
-
-//link the current block to the target block so that current block becomes its target
-pub(crate) fn link_with_target(
-    ctx: &mut SsaContext,
-    target: BlockId,
-    left: Option<BlockId>,
-    right: Option<BlockId>,
-) {
-    if let Some(target_block) = ctx.try_get_block_mut(target) {
-        target_block.right = right;
-        target_block.left = left;
-        //TODO should also update the last instruction rhs to the first instruction of the current block  -- TODO should we do it here??
-        if let Some(right_uw) = right {
-            ctx[right_uw].dominator = Some(target);
-        }
-        if let Some(left_uw) = left {
-            ctx[left_uw].dominator = Some(target);
-        }
-    }
-}
-
-pub(crate) fn compute_dom(ctx: &mut SsaContext) {
-    let mut dominator_link = HashMap::new();
-
-    for block in ctx.iter_blocks() {
-        if let Some(dom) = block.dominator {
-            dominator_link.entry(dom).or_insert_with(Vec::new).push(block.id);
-        }
-    }
-    for (master, slave_vec) in dominator_link {
-        if let Some(dom_b) = ctx.try_get_block_mut(master) {
-            dom_b.dominated.clear();
-            for slave in slave_vec {
-                dom_b.dominated.push(slave);
-            }
-        }
-    }
-}
-
-pub(crate) fn compute_sub_dom(ctx: &mut SsaContext, blocks: &[BlockId]) {
-    let mut dominator_link = HashMap::new();
-
-    for &block_id in blocks {
-        let block = &ctx[block_id];
-        if let Some(dom) = block.dominator {
-            dominator_link.entry(dom).or_insert_with(Vec::new).push(block.id);
-        }
-    }
-    for (master, slave_vec) in dominator_link {
-        let dom_b = &mut ctx[master];
-        for slave in slave_vec {
-            dom_b.dominated.push(slave);
-        }
-    }
-}
-
-//breadth-first traversal of the CFG, from start, until we reach stop
-pub(crate) fn bfs(start: BlockId, stop: Option<BlockId>, ctx: &SsaContext) -> Vec<BlockId> {
-    let mut result = vec![start]; //list of blocks in the visited subgraph
-    let mut queue = VecDeque::new(); //Queue of elements to visit
-    queue.push_back(start);
-
-    while !queue.is_empty() {
-        let block = &ctx[queue.pop_front().unwrap()];
-
-        let mut test_and_push = |block_opt| {
-            if let Some(block_id) = block_opt {
-                if stop == Some(block_id) {
-                    return;
-                }
-                if !block_id.is_dummy() && !result.contains(&block_id) {
-                    result.push(block_id);
-                    queue.push_back(block_id);
-                }
-            }
-        };
-
-        test_and_push(block.left);
-        test_and_push(block.right);
-    }
-
-    result
-}
-
-//Find the exit (i.e join) block from a IF (i.e split) block
-pub(crate) fn find_join(ctx: &SsaContext, block_id: BlockId) -> BlockId {
-    let mut processed = HashMap::new();
-    find_join_helper(ctx, block_id, &mut processed)
-}
-
-//We follow down the path from the THEN and ELSE branches until we reach a common descendant
-fn find_join_helper(
-    ctx: &SsaContext,
-    block_id: BlockId,
-    processed: &mut HashMap<BlockId, BlockId>,
-) -> BlockId {
-    let mut left = ctx[block_id].left.unwrap();
-    let mut right = ctx[block_id].right.unwrap();
-    let mut left_descendants = Vec::new();
-    let mut right_descendants = Vec::new();
-
-    while !left.is_dummy() || !right.is_dummy() {
-        if let Some(block) = get_only_descendant(ctx, left, processed) {
-            left_descendants.push(block);
-            left = block;
-            if right_descendants.contains(&block) {
-                return block;
-            }
-        }
-        if let Some(block) = get_only_descendant(ctx, right, processed) {
-            right_descendants.push(block);
-            right = block;
-            if left_descendants.contains(&block) {
-                return block;
-            }
-        }
-    }
-    unreachable!("no join");
-}
-
-// Find the LCA of x and y
-// n.b. this is a naive implementation which assumes there is no cycle in the graph, so it should be used after loop flattening
-pub(super) fn lca(ctx: &SsaContext, x: BlockId, y: BlockId) -> BlockId {
-    if x == y {
-        return x;
-    }
-    let mut pred_x: HashSet<BlockId> = HashSet::new();
-    let mut pred_y: HashSet<BlockId> = HashSet::new();
-    let mut to_process_x = ctx[x].predecessor.clone();
-    let mut to_process_y = ctx[y].predecessor.clone();
-    pred_x.insert(x);
-    pred_y.insert(y);
-    pred_x.extend(&ctx[x].predecessor);
-    pred_y.extend(&ctx[y].predecessor);
-
-    while !to_process_x.is_empty() || !to_process_y.is_empty() {
-        if let Some(b) = to_process_x.pop() {
-            if pred_y.contains(&b) {
-                return b;
-            }
-            to_process_x.extend(&ctx[b].predecessor);
-            pred_x.extend(&ctx[b].predecessor);
-        }
-        if let Some(b) = to_process_y.pop() {
-            if pred_x.contains(&b) {
-                return b;
-            }
-            to_process_y.extend(&ctx[b].predecessor);
-            pred_y.extend(&ctx[b].predecessor);
-        }
-    }
-    unreachable!("Blocks {:?} and {:?} are not connected", x, y);
-}
-
-//get the most direct descendant which is 'only child'
-fn get_only_descendant(
-    ctx: &SsaContext,
-    block_id: BlockId,
-    processed: &mut HashMap<BlockId, BlockId>,
-) -> Option<BlockId> {
-    if block_id == BlockId::dummy() {
-        return None;
-    }
-    let block = &ctx[block_id];
-    if block.right.is_none() || block.kind == BlockType::ForJoin {
-        if let Some(left) = block.left {
-            processed.insert(block_id, left);
-        }
-        block.left
-    } else {
-        if processed.contains_key(&block_id) {
-            return Some(processed[&block_id]);
-        }
-        let descendant = find_join_helper(ctx, block_id, processed);
-        processed.insert(block_id, descendant);
-        Some(descendant)
-    }
-}
-
-//Set left as the left block of block_id
-//Set block_id as the only parent of left
-pub(super) fn rewire_block_left(ctx: &mut SsaContext, block_id: BlockId, left: BlockId) {
-    let block = &mut ctx[block_id];
-    if let Some(old_left) = block.left {
-        if left != old_left {
-            let i = block.dominated.iter().position(|value| *value == old_left).unwrap();
-            block.dominated.swap_remove(i);
-        }
-    }
-    if !block.dominated.contains(&left) {
-        block.dominated.push(left);
-    }
-    block.left = Some(left);
-    assert!(block.right != Some(left));
-
-    ctx[left].predecessor = vec![block_id];
-    ctx[left].dominator = Some(block_id);
-}
-
-//replace all instructions by a false constraint, except for return instruction which is kept and zeroed
-pub(super) fn short_circuit_instructions(
-    ctx: &mut SsaContext,
-    target: BlockId,
-    instructions: &[NodeId],
-) -> Vec<NodeId> {
-    // short-circuit the return instruction (if it exists)
-    zero_instructions(ctx, instructions, None);
-    //nop and constrain false
-    let unreachable_op = node::Operation::Constrain(ctx.zero(), None);
-    let unreachable_ins = ctx.add_instruction(Instruction::new(
-        unreachable_op,
-        node::ObjectType::NotAnObject,
-        Some(target),
-    ));
-    let nop = instructions[0];
-    debug_assert_eq!(ctx.instruction(nop).operation, node::Operation::Nop);
-    let mut stack = vec![nop, unreachable_ins];
-    //return:
-    for &i in instructions.iter() {
-        if let Some(ins) = ctx.try_get_instruction(i) {
-            if ins.operation.opcode() == Opcode::Return {
-                stack.push(i);
-                zero_instructions(ctx, &[i], None);
-            }
-        }
-    }
-
-    stack
-}
-
-//replace all instructions in the target block by a false constraint, except for return instruction
-pub(super) fn short_circuit_inline(ctx: &mut SsaContext, target: BlockId) {
-    let instructions = ctx[target].instructions.clone();
-    let stack = short_circuit_instructions(ctx, target, &instructions);
-    ctx[target].instructions = stack;
-}
-
-//Delete all instructions in the block
-pub(super) fn short_circuit_block(ctx: &mut SsaContext, block_id: BlockId) {
-    let instructions = ctx[block_id].instructions.clone();
-    zero_instructions(ctx, &instructions, None);
-}
-
-//Delete instructions and replace them with zeros, except for return instruction which is kept with zeroed return values, and the avoid instruction
-pub(super) fn zero_instructions(
-    ctx: &mut SsaContext,
-    instructions: &[NodeId],
-    avoid: Option<&NodeId>,
-) {
-    let mut zeros = HashMap::new();
-    let mut zero_keys = Vec::new();
-    for i in instructions {
-        let ins = ctx.instruction(*i);
-        if ins.res_type != node::ObjectType::NotAnObject {
-            zeros.insert(ins.res_type, ctx.zero_with_type(ins.res_type));
-        } else if let node::Operation::Return(ret) = &ins.operation {
-            for i in ret {
-                if *i != NodeId::dummy() {
-                    let typ = ctx.object_type(*i);
-                    assert_ne!(typ, node::ObjectType::NotAnObject);
-                    zero_keys.push(typ);
-                } else {
-                    zero_keys.push(node::ObjectType::NotAnObject);
-                }
-            }
-        }
-    }
-    for k in zero_keys.iter() {
-        let zero_id = if *k != node::ObjectType::NotAnObject {
-            ctx.zero_with_type(*k)
-        } else {
-            NodeId::dummy()
-        };
-        zeros.insert(*k, zero_id);
-    }
-
-    for i in instructions.iter().filter(|x| Some(*x) != avoid) {
-        let ins = ctx.instruction_mut(*i);
-        if ins.res_type != node::ObjectType::NotAnObject {
-            ins.mark = Mark::ReplaceWith(zeros[&ins.res_type]);
-        } else if ins.operation.opcode() != Opcode::Nop {
-            if ins.operation.opcode() == Opcode::Return {
-                let vec = iter_extended::vecmap(&zero_keys, |x| zeros[x]);
-                ins.operation = node::Operation::Return(vec);
-            } else {
-                ins.mark = Mark::Deleted;
-            }
-        }
-    }
-}
-
-//merge subgraph from start to end in one block, excluding end
-pub(super) fn merge_path(
-    ctx: &mut SsaContext,
-    start: BlockId,
-    end: BlockId,
-    assumption: Option<NodeId>,
-) -> Result<VecDeque<BlockId>, RuntimeError> {
-    let mut removed_blocks = VecDeque::new();
-    if start != end {
-        let mut next = start;
-        let mut instructions = Vec::new();
-        let mut block = &ctx[start];
-        let mut short_circuit = BlockId::dummy();
-
-        while next != end {
-            if block.dominated.len() > 1 || block.right.is_some() {
-                unreachable!("non sequential block sequence: {:?}", block);
-            }
-            block = &ctx[next];
-            removed_blocks.push_back(next);
-
-            if short_circuit.is_dummy() {
-                if instructions.is_empty() {
-                    instructions.extend(&block.instructions);
-                } else {
-                    let nonop = block.instructions.iter().filter(|&i| {
-                        if let Some(ins) = ctx.try_get_instruction(*i) {
-                            ins.operation.opcode() != Opcode::Nop
-                        } else {
-                            true
-                        }
-                    });
-                    instructions.extend(nonop);
-                }
-            }
-
-            if short_circuit.is_dummy() && block.is_short_circuit(ctx, assumption) {
-                instructions.clear();
-                instructions.extend(&block.instructions);
-                short_circuit = block.id;
-            }
-
-            if let Some(left) = block.left {
-                next = left;
-            } else {
-                if !end.is_dummy() {
-                    unreachable!("cannot reach block {:?}", end);
-                }
-                next = BlockId::dummy();
-            }
-        }
-        if !short_circuit.is_dummy() {
-            for &b in &removed_blocks {
-                if b != short_circuit {
-                    short_circuit_block(ctx, b);
-                }
-            }
-        }
-
-        //we assign the concatenated list of instructions to the start block, using a CSE pass
-        let mut modified = false;
-        super::optimizations::cse_block(ctx, start, &mut instructions, &mut modified)?;
-        //Wires start to end
-        if !end.is_dummy() {
-            rewire_block_left(ctx, start, end);
-        } else {
-            ctx[start].left = None;
-        }
-        removed_blocks.pop_front();
-    }
-    //housekeeping for the caller
-    Ok(removed_blocks)
-}
-
-// retrieve written arrays along the CFG until we reach stop
-pub(super) fn written_along(
-    ctx: &SsaContext,
-    block_id: BlockId,
-    stop: BlockId,
-    modified: &mut HashSet<ArrayId>,
-) {
-    if block_id == stop {
-        return;
-    }
-    //process block
-    modified.extend(ctx[block_id].written_arrays(ctx));
-
-    //process next block
-    if ctx[block_id].is_join() {
-        written_along(ctx, ctx[block_id].left.unwrap(), stop, modified);
-    } else if ctx[block_id].right.is_some() {
-        let join = find_join(ctx, block_id);
-        written_along(ctx, join, stop, modified);
-    } else if let Some(left) = ctx[block_id].left {
-        written_along(ctx, left, stop, modified);
-    } else {
-        unreachable!("could not reach stop block");
-    }
-}
-
-// compute the exit block of a graph
-pub(super) fn exit(ctx: &SsaContext, block_id: BlockId) -> BlockId {
-    let block = &ctx[block_id];
-    if let Some(left) = block.left {
-        if left != BlockId::dummy() {
-            return exit(ctx, left);
-        }
-    }
-    block_id
-}
diff --git a/crates/noirc_evaluator/src/ssa/builtin.rs b/crates/noirc_evaluator/src/ssa/builtin.rs
deleted file mode 100644
index ec4cb764534..00000000000
--- a/crates/noirc_evaluator/src/ssa/builtin.rs
+++ /dev/null
@@ -1,146 +0,0 @@
-use crate::ssa::{
-    context::SsaContext,
-    node::{NodeId, ObjectType},
-};
-use acvm::{acir::BlackBoxFunc, FieldElement};
-use num_bigint::BigUint;
-use num_traits::{One, Zero};
-
-/// Opcode here refers to either a black box function
-/// defined in ACIR, or a function which has its
-/// function signature defined in Noir, but its
-/// function definition is implemented in the compiler.
-#[derive(Clone, Debug, Hash, Copy, PartialEq, Eq)]
-pub(crate) enum Opcode {
-    LowLevel(BlackBoxFunc),
-    ToBits(Endian),
-    ToRadix(Endian),
-    Println(PrintlnInfo),
-    Sort,
-}
-
-impl std::fmt::Display for Opcode {
-    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
-        write!(f, "{}", self.name())
-    }
-}
-
-impl Opcode {
-    /// Searches for an `Opcode` using its
-    /// string equivalent name.
-    ///
-    /// Returns `None` if there is no string that
-    /// corresponds to any of the opcodes.
-    pub(crate) fn lookup(op_name: &str) -> Option<Opcode> {
-        match op_name {
-            "to_le_bits" => Some(Opcode::ToBits(Endian::Little)),
-            "to_be_bits" => Some(Opcode::ToBits(Endian::Big)),
-            "to_le_radix" => Some(Opcode::ToRadix(Endian::Little)),
-            "to_be_radix" => Some(Opcode::ToRadix(Endian::Big)),
-            "println" => {
-                Some(Opcode::Println(PrintlnInfo { is_string_output: false, show_output: true }))
-            }
-            "arraysort" => Some(Opcode::Sort),
-            _ => BlackBoxFunc::lookup(op_name).map(Opcode::LowLevel),
-        }
-    }
-
-    fn name(&self) -> &str {
-        match self {
-            Opcode::LowLevel(op) => op.name(),
-            Opcode::ToBits(endianness) => {
-                if *endianness == Endian::Little {
-                    "to_le_bits"
-                } else {
-                    "to_be_bits"
-                }
-            }
-            Opcode::ToRadix(endianness) => {
-                if *endianness == Endian::Little {
-                    "to_le_radix"
-                } else {
-                    "to_be_radix"
-                }
-            }
-            Opcode::Println(_) => "println",
-            Opcode::Sort => "arraysort",
-        }
-    }
-
-    pub(crate) fn get_max_value(&self) -> BigUint {
-        match self {
-            Opcode::LowLevel(op) => {
-                match op {
-                    // Pointers do not overflow
-                    BlackBoxFunc::SHA256
-                    | BlackBoxFunc::Keccak256
-                    | BlackBoxFunc::Blake2s
-                    | BlackBoxFunc::Pedersen
-                    | BlackBoxFunc::FixedBaseScalarMul
-                    | BlackBoxFunc::RecursiveAggregation => BigUint::zero(),
-                    // Verify returns zero or one
-                    BlackBoxFunc::SchnorrVerify
-                    | BlackBoxFunc::EcdsaSecp256k1
-                    | BlackBoxFunc::EcdsaSecp256r1 => BigUint::one(),
-                    BlackBoxFunc::HashToField128Security => ObjectType::native_field().max_size(),
-                    BlackBoxFunc::RANGE | BlackBoxFunc::AND | BlackBoxFunc::XOR => {
-                        unimplemented!("ICE: these opcodes do not have Noir builtin functions")
-                    }
-                }
-            }
-            Opcode::ToBits(_) | Opcode::ToRadix(_) | Opcode::Println(_) | Opcode::Sort => {
-                BigUint::zero()
-            } //pointers do not overflow
-        }
-    }
-
-    /// Returns the number of elements that the `Opcode` should return
-    /// and the type.
-    pub(crate) fn get_result_type(&self, args: &[NodeId], ctx: &SsaContext) -> (u32, ObjectType) {
-        match self {
-            Opcode::LowLevel(op) => {
-                match op {
-                    BlackBoxFunc::SHA256 | BlackBoxFunc::Blake2s | BlackBoxFunc::Keccak256 => {
-                        (32, ObjectType::unsigned_integer(8))
-                    }
-                    BlackBoxFunc::HashToField128Security => (1, ObjectType::native_field()),
-                    // See issue #775 on changing this to return a boolean
-                    BlackBoxFunc::SchnorrVerify
-                    | BlackBoxFunc::EcdsaSecp256k1
-                    | BlackBoxFunc::EcdsaSecp256r1 => (1, ObjectType::native_field()),
-                    BlackBoxFunc::Pedersen => (2, ObjectType::native_field()),
-                    BlackBoxFunc::FixedBaseScalarMul => (2, ObjectType::native_field()),
-                    BlackBoxFunc::RecursiveAggregation => {
-                        let a = super::mem::Memory::deref(ctx, args[4]).unwrap();
-                        (ctx.mem[a].len, ctx.mem[a].element_type)
-                    }
-                    BlackBoxFunc::RANGE | BlackBoxFunc::AND | BlackBoxFunc::XOR => {
-                        unreachable!("ICE: these opcodes do not have Noir builtin functions")
-                    }
-                }
-            }
-            Opcode::ToBits(_) => (FieldElement::max_num_bits(), ObjectType::boolean()),
-            Opcode::ToRadix(_) => (FieldElement::max_num_bits(), ObjectType::native_field()),
-            Opcode::Println(_) => (0, ObjectType::NotAnObject),
-            Opcode::Sort => {
-                let a = super::mem::Memory::deref(ctx, args[0]).unwrap();
-                (ctx.mem[a].len, ctx.mem[a].element_type)
-            }
-        }
-    }
-}
-
-#[derive(Clone, Debug, Hash, Copy, PartialEq, Eq)]
-pub(crate) struct PrintlnInfo {
-    // We store strings as arrays and there is no differentiation between them in the SSA.
-    // This bool simply states whether an array that is to be printed should be outputted as a utf8 string.
-    pub(crate) is_string_output: bool,
-    // This is a flag used during `nargo test` to determine whether to display println output.
-    pub(crate) show_output: bool,
-}
-
-#[derive(Clone, Copy, Debug, Hash, PartialEq, Eq)]
-pub(crate) enum Endian {
-    Big,
-    Little,
-}
diff --git a/crates/noirc_evaluator/src/ssa/conditional.rs b/crates/noirc_evaluator/src/ssa/conditional.rs
deleted file mode 100644
index b762a3d3f55..00000000000
--- a/crates/noirc_evaluator/src/ssa/conditional.rs
+++ /dev/null
@@ -1,1139 +0,0 @@
-use crate::{
-    errors::{RuntimeError, RuntimeErrorKind},
-    ssa::{
-        block::{BlockId, BlockType},
-        context::SsaContext,
-        flatten::UnrollContext,
-        inline::StackFrame,
-        node::{Binary, BinaryOp, Instruction, Mark, NodeId, ObjectType, Opcode, Operation},
-        {block, flatten, node, optimizations},
-    },
-};
-use noirc_errors::Location;
-use num_bigint::BigUint;
-use num_traits::One;
-
-// Functions that modify arrays work on a fresh array, which is copied to the original one,
-// so that the writing to the array is made explicit and handled like all the other ones with store instructions
-// we keep the original array name and add the _dup suffix for debugging purpose
-const DUPLICATED: &str = "_dup";
-
-#[derive(Debug, Clone)]
-pub(crate) struct Assumption {
-    pub(crate) parent: AssumptionId,
-    pub(crate) val_true: Vec<AssumptionId>,
-    pub(crate) val_false: Vec<AssumptionId>,
-    pub(crate) condition: NodeId,
-    pub(crate) entry_block: BlockId,
-    pub(crate) exit_block: BlockId,
-    value: Option<NodeId>,
-}
-
-impl Assumption {
-    pub(crate) fn new(parent: AssumptionId) -> Assumption {
-        Assumption {
-            parent,
-            val_true: Vec::new(),
-            val_false: Vec::new(),
-            condition: NodeId::dummy(),
-            entry_block: BlockId::dummy(),
-            exit_block: BlockId::dummy(),
-            value: None,
-        }
-    }
-}
-
-#[derive(Debug, Copy, Clone, PartialEq, Eq, Hash)]
-pub(crate) struct AssumptionId(pub(crate) arena::Index);
-
-impl AssumptionId {
-    pub(crate) fn dummy() -> AssumptionId {
-        AssumptionId(SsaContext::dummy_id())
-    }
-}
-
-//temporary data used to build the decision tree
-pub(crate) struct TreeBuilder {
-    pub(crate) join_to_process: Vec<BlockId>,
-    pub(crate) stack: StackFrame,
-}
-
-impl TreeBuilder {
-    pub(crate) fn new(entry: BlockId) -> TreeBuilder {
-        TreeBuilder { join_to_process: Vec::new(), stack: StackFrame::new(entry) }
-    }
-}
-
-#[derive(Debug, Clone)]
-pub(crate) struct DecisionTree {
-    arena: arena::Arena<Assumption>,
-    pub(crate) root: AssumptionId,
-}
-
-impl std::ops::Index<AssumptionId> for DecisionTree {
-    type Output = Assumption;
-
-    fn index(&self, index: AssumptionId) -> &Self::Output {
-        &self.arena[index.0]
-    }
-}
-
-impl std::ops::IndexMut<AssumptionId> for DecisionTree {
-    fn index_mut(&mut self, index: AssumptionId) -> &mut Self::Output {
-        &mut self.arena[index.0]
-    }
-}
-
-impl DecisionTree {
-    pub(crate) fn new(ctx: &SsaContext) -> DecisionTree {
-        let mut tree = DecisionTree { arena: arena::Arena::new(), root: AssumptionId::dummy() };
-        let root_id = tree.new_decision_leaf(AssumptionId::dummy());
-        tree.root = root_id;
-        tree[root_id].value = Some(ctx.one());
-        tree[root_id].condition = ctx.one();
-        tree
-    }
-
-    pub(crate) fn new_decision_leaf(&mut self, parent: AssumptionId) -> AssumptionId {
-        let node = Assumption::new(parent);
-        AssumptionId(self.arena.insert(node))
-    }
-
-    pub(crate) fn is_true_branch(&self, assumption: AssumptionId) -> bool {
-        assert_ne!(assumption, self.root);
-        let parent_id = self[assumption].parent;
-        assert!(
-            self[parent_id].val_true.contains(&assumption)
-                != self[parent_id].val_false.contains(&assumption)
-        );
-        self[parent_id].val_true.contains(&assumption)
-    }
-
-    fn new_instruction(
-        ctx: &mut SsaContext,
-        block_id: BlockId,
-        operator: BinaryOp,
-        lhs: NodeId,
-        rhs: NodeId,
-        typ: ObjectType,
-    ) -> Instruction {
-        let operation = Operation::binary(operator, lhs, rhs);
-        let mut i = Instruction::new(operation, typ, Some(block_id));
-        super::optimizations::simplify(ctx, &mut i).unwrap();
-        i
-    }
-
-    fn new_instruction_after_phi(
-        ctx: &mut SsaContext,
-        block_id: BlockId,
-        operator: BinaryOp,
-        lhs: NodeId,
-        rhs: NodeId,
-        typ: ObjectType,
-    ) -> NodeId {
-        let i = DecisionTree::new_instruction(ctx, block_id, operator, lhs, rhs, typ);
-        if let node::Mark::ReplaceWith(replacement) = i.mark {
-            return replacement;
-        }
-        ctx.insert_instruction_after_phi(i, block_id)
-    }
-
-    fn new_instruction_after(
-        ctx: &mut SsaContext,
-        block_id: BlockId,
-        operator: BinaryOp,
-        lhs: NodeId,
-        rhs: NodeId,
-        typ: ObjectType,
-        after: NodeId,
-    ) -> NodeId {
-        let i = DecisionTree::new_instruction(ctx, block_id, operator, lhs, rhs, typ);
-        if let node::Mark::ReplaceWith(replacement) = i.mark {
-            return replacement;
-        }
-        let id = ctx.add_instruction(i);
-        ctx.push_instruction_after(id, block_id, after)
-    }
-
-    pub(crate) fn compute_assumption(&mut self, ctx: &mut SsaContext, block_id: BlockId) -> NodeId {
-        let block = &ctx[block_id];
-        let assumption_id = block.assumption;
-        let assumption = &self[block.assumption];
-        if let Some(value) = assumption.value {
-            return value;
-        }
-        let parent_value = self[assumption.parent].value.unwrap();
-        let condition = self[assumption.parent].condition;
-        let ins = if self.is_true_branch(block.assumption) {
-            DecisionTree::new_instruction_after_phi(
-                ctx,
-                block_id,
-                BinaryOp::Mul,
-                parent_value,
-                condition,
-                ObjectType::boolean(),
-            )
-        } else {
-            let not_condition = DecisionTree::new_instruction_after_phi(
-                ctx,
-                block_id,
-                BinaryOp::Sub { max_rhs_value: BigUint::one() },
-                ctx.one(),
-                condition,
-                ObjectType::boolean(),
-            );
-            DecisionTree::new_instruction_after(
-                ctx,
-                block_id,
-                BinaryOp::Mul,
-                parent_value,
-                not_condition,
-                ObjectType::boolean(),
-                not_condition,
-            )
-        };
-        self[assumption_id].value = Some(ins);
-        ins
-    }
-
-    pub(crate) fn make_decision_tree(
-        &mut self,
-        ctx: &mut SsaContext,
-        mut builder: TreeBuilder,
-    ) -> Result<(), RuntimeError> {
-        let entry_block = builder.stack.block;
-        ctx[entry_block].assumption = self.root;
-        self.decision_tree(ctx, entry_block, &mut builder)
-    }
-
-    //Returns a boolean to indicate if we should process the children (true) of not (false) of the block
-    fn process_block(
-        &mut self,
-        ctx: &mut SsaContext,
-        current: BlockId,
-        data: &mut TreeBuilder,
-    ) -> Result<Vec<BlockId>, RuntimeError> {
-        data.stack.block = current;
-        let mut block_assumption = ctx[current].assumption;
-        let assumption = &self[block_assumption];
-        let mut result = Vec::new();
-        let current_block = &ctx[current];
-        let mut if_assumption = None;
-        let mut parent = AssumptionId::dummy();
-        let mut sibling = true;
-        let left = current_block.left;
-        let right = current_block.right;
-        // is it an exit block?
-        if data.join_to_process.contains(&current) {
-            assert!(current == *data.join_to_process.last().unwrap());
-            block_assumption = assumption.parent;
-            data.join_to_process.pop();
-        }
-        // is it an IF block?
-        if let Some(ins) = ctx.get_if_condition(current_block) {
-            //add a new assumption for the IF
-            if assumption.parent == AssumptionId::dummy() {
-                //Root assumption
-                parent = block_assumption;
-                sibling = true;
-            } else {
-                parent = assumption.parent;
-                sibling = self[assumption.parent].val_true.contains(&block_assumption);
-            };
-            let mut if_decision = Assumption::new(parent);
-            if let Operation::Jeq(condition, _) = ins.operation {
-                if_decision.condition = condition;
-            } else {
-                unreachable!();
-            }
-
-            //find exit node:
-            let exit = block::find_join(ctx, current_block.id);
-            assert!(ctx[exit].kind == BlockType::IfJoin);
-            if_decision.entry_block = current;
-            if_decision.exit_block = exit;
-            if_assumption = Some(if_decision);
-            data.join_to_process.push(exit);
-            result = vec![exit, right.unwrap(), left.unwrap()];
-        }
-        //Assumptions for the children
-        if let Some(if_decision) = if_assumption {
-            block_assumption = AssumptionId(self.arena.insert(if_decision));
-            if sibling {
-                self[parent].val_true.push(block_assumption);
-            } else {
-                self[parent].val_false.push(block_assumption);
-            }
-            //create the assumptions for else/then branches
-            let left_assumption = self.new_decision_leaf(block_assumption);
-            let right_assumption = self.new_decision_leaf(block_assumption);
-            self[block_assumption].val_true.push(left_assumption);
-            self[block_assumption].val_false.push(right_assumption);
-            ctx[left.unwrap()].assumption = left_assumption;
-            ctx[right.unwrap()].assumption = right_assumption;
-        } else {
-            match (left, right) {
-                (Some(l), None) => {
-                    ctx[l].assumption = block_assumption;
-                    result = vec![l];
-                }
-                (Some(l), Some(r)) => {
-                    ctx[l].assumption = block_assumption;
-                    ctx[r].assumption = block_assumption;
-                    result = vec![l, r];
-                }
-                (None, Some(_)) => {
-                    unreachable!("Infallible, only a split block can have right successor")
-                }
-                (None, None) => (),
-            }
-        }
-
-        ctx[current].assumption = block_assumption;
-        self.compute_assumption(ctx, current);
-        self.apply_condition_to_block(ctx, current, &mut data.stack)?;
-        Ok(result)
-    }
-
-    fn decision_tree(
-        &mut self,
-        ctx: &mut SsaContext,
-        current: BlockId,
-        data: &mut TreeBuilder,
-    ) -> Result<(), RuntimeError> {
-        let mut queue = vec![current]; //Stack of elements to visit
-
-        while let Some(current) = queue.pop() {
-            let children = self.process_block(ctx, current, data)?;
-
-            let mut test_and_push = |block_id: BlockId| {
-                if !block_id.is_dummy() && !queue.contains(&block_id) {
-                    let block = &ctx[block_id];
-                    if !block.is_join() || block.dominator == Some(current) {
-                        queue.push(block_id);
-                    }
-                }
-            };
-
-            for i in children {
-                test_and_push(i);
-            }
-        }
-        Ok(())
-    }
-
-    pub(crate) fn reduce(
-        &mut self,
-        ctx: &mut SsaContext,
-        node_id: AssumptionId,
-    ) -> Result<(), RuntimeError> {
-        //reduce children
-        let assumption = self[node_id].clone();
-        for i in assumption.val_true {
-            self.reduce(ctx, i)?;
-        }
-        for i in assumption.val_false {
-            self.reduce(ctx, i)?;
-        }
-        //reduce the node
-        if !assumption.entry_block.is_dummy() {
-            self.reduce_sub_graph(ctx, assumption.entry_block, assumption.exit_block)?;
-        }
-        Ok(())
-    }
-
-    //reduce if sub graph
-    pub(crate) fn reduce_sub_graph(
-        &self,
-        ctx: &mut SsaContext,
-        if_block_id: BlockId,
-        exit_block_id: BlockId,
-    ) -> Result<(), RuntimeError> {
-        //basic reduction as a first step (i.e no optimization)
-        let if_block = &ctx[if_block_id];
-        let mut to_remove = Vec::new();
-        let left = if_block.left.unwrap();
-        let right = if_block.right.unwrap();
-        let mut const_condition = None;
-        if ctx.is_one(self[if_block.assumption].condition) {
-            const_condition = Some(true);
-        }
-        if ctx.is_zero(self[if_block.assumption].condition) {
-            const_condition = Some(false);
-        }
-
-        //merge then branch
-        to_remove.extend(block::merge_path(
-            ctx,
-            left,
-            exit_block_id,
-            self[ctx[left].assumption].value,
-        )?);
-
-        //merge else branch
-        to_remove.extend(block::merge_path(
-            ctx,
-            right,
-            exit_block_id,
-            self[ctx[right].assumption].value,
-        )?);
-
-        to_remove.push(right);
-        let mut merged_ins;
-        if let Some(const_condition) = const_condition {
-            if const_condition {
-                merged_ins = ctx[left].instructions.clone();
-            } else {
-                merged_ins = ctx[right].instructions.clone();
-            }
-        } else {
-            let left_ins = ctx[left].instructions.clone();
-            let right_ins = ctx[right].instructions.clone();
-            merged_ins = self.synchronize(ctx, &left_ins, &right_ins, left);
-        }
-        let mut modified = false;
-        // write the merged instructions to the block
-        super::optimizations::cse_block(ctx, left, &mut merged_ins, &mut modified)?;
-        if modified {
-            // A second round is necessary when the synchronization optimizes function calls between the two branches.
-            // In that case, the first cse updates the result instructions to the same call and then
-            // the second cse can (and must) then simplify identical result instructions.
-            // We clear the list because we want to perform the cse on the block instructions, if we don't it will use the list instead.
-            // We should refactor cse_block so that its behavior is consistent and does not rely on the list being empty.
-            merged_ins.clear();
-            super::optimizations::cse_block(ctx, left, &mut merged_ins, &mut modified)?;
-        }
-        //housekeeping...
-        let if_block = &mut ctx[if_block_id];
-        if_block.dominated = vec![left];
-        if_block.right = None;
-        if_block.kind = BlockType::Normal;
-        if_block.instructions.pop();
-
-        block::rewire_block_left(ctx, left, exit_block_id);
-        for i in to_remove {
-            ctx.remove_block(i);
-        }
-        Ok(())
-    }
-
-    /// Apply the condition of the block to each instruction
-    /// in the block.
-    pub(crate) fn apply_condition_to_block(
-        &self,
-        ctx: &mut SsaContext,
-        block: BlockId,
-        stack: &mut StackFrame,
-    ) -> Result<(), RuntimeError> {
-        let assumption_id = ctx[block].assumption;
-        let instructions = ctx[block].instructions.clone();
-        self.apply_condition_to_instructions(ctx, &instructions, stack, assumption_id)?;
-        ctx[block].instructions.clear();
-        ctx[block].instructions.append(&mut stack.stack);
-        assert!(stack.stack.is_empty());
-        Ok(())
-    }
-
-    /// Applies a condition to each instruction
-    /// and places into the stack frame.
-    pub(crate) fn apply_condition_to_instructions(
-        &self,
-        ctx: &mut SsaContext,
-        instructions: &[NodeId],
-        result: &mut StackFrame,
-        predicate: AssumptionId,
-    ) -> Result<(), RuntimeError> {
-        if predicate == AssumptionId::dummy() || self[predicate].value != Some(ctx.zero()) {
-            let mut short_circuit = false;
-            for i in instructions {
-                if !self.apply_condition_to_instruction(
-                    ctx,
-                    result,
-                    *i,
-                    predicate,
-                    short_circuit,
-                )? {
-                    short_circuit = true;
-                }
-            }
-        }
-        Ok(())
-    }
-
-    fn short_circuit(
-        ctx: &mut SsaContext,
-        stack: &mut StackFrame,
-        condition: NodeId,
-        error_msg: &str,
-        location: Option<Location>,
-    ) -> Result<(), RuntimeError> {
-        if ctx.under_assumption(condition) {
-            let avoid = stack.stack.contains(&condition).then_some(&condition);
-            block::zero_instructions(ctx, &stack.stack, avoid);
-            let nop = stack.stack[0];
-            stack.stack.clear();
-            stack.stack.push(nop);
-            if avoid.is_some() {
-                stack.stack.push(condition);
-            }
-            let operation =
-                Operation::Cond { condition, val_true: ctx.zero(), val_false: ctx.one() };
-            let cond = ctx.add_instruction(Instruction::new(
-                operation,
-                ObjectType::boolean(),
-                Some(stack.block),
-            ));
-            stack.push(cond);
-            let unreachable = Operation::Constrain(cond, None);
-            let ins2 = ctx.add_instruction(Instruction::new(
-                unreachable,
-                ObjectType::NotAnObject,
-                Some(stack.block),
-            ));
-            stack.push(ins2);
-            Ok(())
-        } else {
-            Err(RuntimeError {
-                location,
-                kind: RuntimeErrorKind::UnstructuredError { message: error_msg.to_string() },
-            })
-        }
-    }
-
-    /// Applies a condition to the instruction
-    /// For most instructions, this does nothing
-    /// but for instructions with side-effects
-    /// this will alter the behavior.
-    pub(crate) fn apply_condition_to_instruction(
-        &self,
-        ctx: &mut SsaContext,
-        stack: &mut StackFrame,
-        ins_id: NodeId,
-        predicate: AssumptionId,
-        short_circuit: bool,
-    ) -> Result<bool, RuntimeError> {
-        let ass_cond;
-        let ass_value;
-        if predicate == AssumptionId::dummy() {
-            ass_cond = NodeId::dummy();
-            ass_value = NodeId::dummy();
-        } else {
-            ass_cond = self[predicate].condition;
-            ass_value = self[predicate].value.unwrap_or_else(NodeId::dummy);
-        }
-        assert!(!ctx.is_zero(ass_value), "code should have been already simplified");
-        let ins1 = ctx.instruction(ins_id);
-        match &ins1.operation {
-            Operation::Call { returned_arrays, .. } => {
-                for a in returned_arrays {
-                    stack.new_array(a.0);
-                }
-            }
-            Operation::Store { array_id, index, .. } => {
-                if *index != NodeId::dummy() {
-                    stack.new_array(*array_id);
-                }
-            }
-            _ => {
-                if let ObjectType::ArrayPointer(a) = ins1.res_type {
-                    stack.new_array(a);
-                }
-            }
-        }
-
-        let ins = ins1.clone();
-        if short_circuit {
-            stack.set_zero(ctx, ins.res_type);
-            let ins2 = ctx.instruction_mut(ins_id);
-            if ins2.res_type == ObjectType::NotAnObject {
-                ins2.mark = Mark::Deleted;
-            } else {
-                ins2.mark = Mark::ReplaceWith(stack.get_zero(ins2.res_type));
-            }
-        } else {
-            match &ins.operation {
-                Operation::Phi { block_args, .. } => {
-                    if ctx[stack.block].kind == BlockType::IfJoin {
-                        assert_eq!(block_args.len(), 2);
-                        let ins2 = ctx.instruction_mut(ins_id);
-                        ins2.operation = Operation::Cond {
-                            condition: ass_cond,
-                            val_true: block_args[0].0,
-                            val_false: block_args[1].0,
-                        };
-                        optimizations::simplify_id(ctx, ins_id).unwrap();
-                    }
-                    stack.push(ins_id);
-                }
-
-                Operation::Load { array_id, index, location } => {
-                    if let Some(idx) = ctx.get_as_constant(*index) {
-                        if (idx.to_u128() as u32) >= ctx.mem[*array_id].len {
-                            let error = format!(
-                                "index out of bounds: the len is {} but the index is {}",
-                                ctx.mem[*array_id].len,
-                                idx.to_u128()
-                            );
-                            DecisionTree::short_circuit(ctx, stack, ass_value, &error, *location)?;
-                            return Ok(false);
-                        }
-                    } else {
-                        // we use a 0 index when the predicate is false, to avoid out-of-bound issues
-                        let ass_value = Self::unwrap_predicate(ctx, &Some(ass_value));
-                        let op = Operation::Cast(ass_value);
-                        let pred = ctx.add_instruction(Instruction::new(
-                            op,
-                            ctx.object_type(*index),
-                            Some(stack.block),
-                        ));
-                        stack.push(pred);
-                        let op = Operation::Binary(node::Binary {
-                            lhs: *index,
-                            rhs: pred,
-                            operator: BinaryOp::Mul,
-                            predicate: None,
-                        });
-                        let idx = ctx.add_instruction(Instruction::new(
-                            op,
-                            ObjectType::native_field(),
-                            Some(stack.block),
-                        ));
-                        optimizations::simplify_id(ctx, idx).unwrap();
-                        stack.push(idx);
-
-                        let ins2 = ctx.instruction_mut(ins_id);
-                        ins2.operation = Operation::Load {
-                            array_id: *array_id,
-                            index: idx,
-                            location: *location,
-                        };
-                    }
-                    stack.push(ins_id);
-                }
-                Operation::Binary(binary_op) => {
-                    let mut cond = ass_value;
-                    if let Some(pred) = binary_op.predicate {
-                        assert_ne!(pred, NodeId::dummy());
-                        if ass_value == NodeId::dummy() {
-                            cond = pred;
-                        } else {
-                            let op = Operation::Binary(node::Binary {
-                                lhs: ass_value,
-                                rhs: pred,
-                                operator: BinaryOp::Mul,
-                                predicate: None,
-                            });
-                            cond = ctx.add_instruction(Instruction::new(
-                                op,
-                                ObjectType::boolean(),
-                                Some(stack.block),
-                            ));
-                            optimizations::simplify_id(ctx, cond).unwrap();
-                            stack.push(cond);
-                        }
-                    }
-                    stack.push(ins_id);
-                    let (side_effect, location) = match binary_op.operator {
-                        BinaryOp::Udiv(loc)
-                        | BinaryOp::Sdiv(loc)
-                        | BinaryOp::Urem(loc)
-                        | BinaryOp::Srem(loc)
-                        | BinaryOp::Div(loc) => (true, Some(loc)),
-                        _ => (false, None),
-                    };
-                    if side_effect {
-                        if ctx.is_zero(binary_op.rhs) {
-                            DecisionTree::short_circuit(
-                                ctx,
-                                stack,
-                                cond,
-                                "attempt to divide by zero",
-                                location,
-                            )?;
-                            return Ok(false);
-                        }
-                        if ctx.under_assumption(cond) {
-                            let ins2 = ctx.instruction_mut(ins_id);
-                            ins2.operation = Operation::Binary(Binary {
-                                lhs: binary_op.lhs,
-                                rhs: binary_op.rhs,
-                                operator: binary_op.operator.clone(),
-                                predicate: Some(cond),
-                            });
-                        }
-                    }
-                }
-                Operation::Store { array_id, index, value, predicate, location } => {
-                    if !ins.operation.is_dummy_store() {
-                        if let Some(idx) = ctx.get_as_constant(*index) {
-                            if (idx.to_u128() as u32) >= ctx.mem[*array_id].len {
-                                let error = format!(
-                                    "index out of bounds: the len is {} but the index is {}",
-                                    ctx.mem[*array_id].len,
-                                    idx.to_u128()
-                                );
-                                DecisionTree::short_circuit(
-                                    ctx, stack, ass_value, &error, *location,
-                                )?;
-                                return Ok(false);
-                            }
-                        }
-                        if !stack.is_new_array(ctx, array_id) && ctx.under_assumption(ass_value) {
-                            let pred =
-                                Self::and_conditions(Some(ass_value), *predicate, stack, ctx);
-                            // we use a 0 index when the predicate is false and index is not constant, to avoid out-of-bound issues
-                            let idx = if ctx.get_as_constant(*index).is_some() {
-                                *index
-                            } else {
-                                let op = Operation::Cast(Self::unwrap_predicate(ctx, &pred));
-
-                                let cast = ctx.add_instruction(Instruction::new(
-                                    op,
-                                    ctx.object_type(*index),
-                                    Some(stack.block),
-                                ));
-                                stack.push(cast);
-                                let op = Operation::Binary(node::Binary {
-                                    lhs: *index,
-                                    rhs: cast,
-                                    operator: BinaryOp::Mul,
-                                    predicate: None,
-                                });
-                                let idx = ctx.add_instruction(Instruction::new(
-                                    op,
-                                    ObjectType::native_field(),
-                                    Some(stack.block),
-                                ));
-                                optimizations::simplify_id(ctx, idx).unwrap();
-                                stack.push(idx);
-                                idx
-                            };
-                            let ins2 = ctx.instruction_mut(ins_id);
-                            ins2.operation = Operation::Store {
-                                array_id: *array_id,
-                                index: idx,
-                                value: *value,
-                                predicate: pred,
-                                location: *location,
-                            };
-                        }
-                    }
-                    stack.push(ins_id);
-                }
-                Operation::Intrinsic(_, _) => {
-                    stack.push(ins_id);
-                    if ctx.under_assumption(ass_value) {
-                        if let ObjectType::ArrayPointer(a) = ins.res_type {
-                            if stack.created_arrays[&a] != stack.block {
-                                let array = &ctx.mem[a].clone();
-                                let name = array.name.to_string() + DUPLICATED;
-                                ctx.new_array(&name, array.element_type, array.len, None);
-                                let array_dup = ctx.mem.last_id();
-                                let ins2 = ctx.instruction_mut(ins_id);
-                                ins2.res_type = ObjectType::ArrayPointer(array_dup);
-
-                                let mut memcpy_stack = StackFrame::new(stack.block);
-                                ctx.memcpy_inline(
-                                    ins.res_type,
-                                    ObjectType::ArrayPointer(array_dup),
-                                    &mut memcpy_stack,
-                                );
-                                self.apply_condition_to_instructions(
-                                    ctx,
-                                    &memcpy_stack.stack,
-                                    stack,
-                                    predicate,
-                                )?;
-                            }
-                        }
-                    }
-                }
-
-                Operation::Call {
-                    func: func_id,
-                    arguments,
-                    returned_arrays,
-                    predicate: ins_pred,
-                    location,
-                } => {
-                    if ctx.under_assumption(ass_value) {
-                        assert!(*ins_pred == AssumptionId::dummy());
-                        let mut ins2 = ctx.instruction_mut(ins_id);
-                        ins2.operation = Operation::Call {
-                            func: *func_id,
-                            arguments: arguments.clone(),
-                            returned_arrays: returned_arrays.clone(),
-                            predicate,
-                            location: *location,
-                        };
-                    }
-                    stack.push(ins_id);
-                }
-                Operation::Constrain(expr, loc) => {
-                    if ctx.under_assumption(ass_value) {
-                        let operation = Operation::Cond {
-                            condition: ass_value,
-                            val_true: *expr,
-                            val_false: ctx.one(),
-                        };
-                        if ctx.is_zero(*expr) {
-                            stack.stack.clear();
-                        }
-                        let cond = ctx.add_instruction(Instruction::new(
-                            operation,
-                            ObjectType::boolean(),
-                            Some(stack.block),
-                        ));
-                        stack.push(cond);
-                        let ins2 = ctx.instruction_mut(ins_id);
-                        ins2.operation = Operation::Constrain(cond, *loc);
-                        if ctx.is_zero(*expr) {
-                            stack.push(ins_id);
-                            return Ok(false);
-                        }
-                    }
-                    stack.push(ins_id);
-                }
-                _ => stack.push(ins_id),
-            }
-        }
-
-        Ok(true)
-    }
-
-    pub(crate) fn get_assumption_value(&self, assumption: AssumptionId) -> Option<NodeId> {
-        if assumption == AssumptionId::dummy() {
-            None
-        } else {
-            self[assumption].value
-        }
-    }
-
-    // returns condition1 AND condition2
-    fn and_conditions(
-        condition1: Option<NodeId>,
-        condition2: Option<NodeId>,
-        stack_frame: &mut StackFrame,
-        ctx: &mut SsaContext,
-    ) -> Option<NodeId> {
-        match (condition1, condition2) {
-            (None, None) => None,
-            (Some(cond), other) | (other, Some(cond)) if cond.is_dummy() => {
-                Self::and_conditions(None, other, stack_frame, ctx)
-            }
-            (Some(cond), None) | (None, Some(cond)) => Some(cond),
-            (Some(cond1), Some(cond2)) if cond1 == cond2 => condition1,
-            (Some(cond1), Some(cond2)) => {
-                let op = Operation::Binary(node::Binary {
-                    lhs: cond1,
-                    rhs: cond2,
-                    operator: BinaryOp::Mul,
-                    predicate: None,
-                });
-                let cond = ctx.add_instruction(Instruction::new(
-                    op,
-                    ObjectType::boolean(),
-                    Some(stack_frame.block),
-                ));
-                optimizations::simplify_id(ctx, cond).unwrap();
-                stack_frame.push(cond);
-                Some(cond)
-            }
-        }
-    }
-
-    // returns condition1 OR condition2
-    fn or_conditions(
-        condition1: Option<NodeId>,
-        condition2: Option<NodeId>,
-        stack_frame: &mut StackFrame,
-        ctx: &mut SsaContext,
-    ) -> Option<NodeId> {
-        match (condition1, condition2) {
-            (_condition, None) | (None, _condition) => None,
-            (Some(cond1), Some(cond2)) => {
-                if cond1.is_dummy() || cond2.is_dummy() {
-                    None
-                } else if cond1 == cond2 {
-                    condition1
-                } else {
-                    let op = Operation::Binary(node::Binary {
-                        lhs: cond1,
-                        rhs: cond2,
-                        operator: BinaryOp::Or,
-                        predicate: None,
-                    });
-                    let cond = ctx.add_instruction(Instruction::new(
-                        op,
-                        ObjectType::boolean(),
-                        Some(stack_frame.block),
-                    ));
-                    optimizations::simplify_id(ctx, cond).unwrap();
-                    stack_frame.push(cond);
-                    Some(cond)
-                }
-            }
-        }
-    }
-
-    pub(crate) fn unwrap_predicate(ctx: &SsaContext, predicate: &Option<NodeId>) -> NodeId {
-        let predicate = predicate.unwrap_or(NodeId::dummy());
-        if predicate.is_dummy() {
-            ctx.one()
-        } else {
-            predicate
-        }
-    }
-
-    fn synchronize(
-        &self,
-        ctx: &mut SsaContext,
-        left: &[NodeId],
-        right: &[NodeId],
-        block_id: BlockId,
-    ) -> Vec<NodeId> {
-        // 1. find potential matches between the two blocks
-        let mut candidates = Vec::new();
-        let keep_call_and_store = |node_id: NodeId| -> bool {
-            let ins = ctx.instruction(node_id);
-            matches!(ins.operation.opcode(), Opcode::Call(_) | Opcode::Store(_))
-        };
-        let l_iter = left.iter().enumerate().filter(|&i| keep_call_and_store(*i.1));
-        let mut r_iter = right.iter().enumerate().filter(|&i| keep_call_and_store(*i.1));
-        for left_node in l_iter {
-            let left_ins = ctx.instruction(*left_node.1);
-            for right_node in r_iter.by_ref() {
-                let right_ins = ctx.instruction(*right_node.1);
-                match (&left_ins.operation, &right_ins.operation) {
-                    (
-                        Operation::Call { func: left_func, returned_arrays: left_arrays, .. },
-                        Operation::Call { func: right_func, returned_arrays: right_arrays, .. },
-                    ) if left_func == right_func
-                        && left_arrays.is_empty()
-                        && right_arrays.is_empty() =>
-                    {
-                        candidates.push(Segment::new(left_node, right_node));
-                    }
-
-                    (
-                        Operation::Store { array_id: left_array, index: left_index, .. },
-                        Operation::Store { array_id: right_array, index: right_index, .. },
-                    ) if left_array == right_array && left_index == right_index => {
-                        candidates.push(Segment::new(left_node, right_node));
-                    }
-                    _ => (),
-                }
-            }
-        }
-        // 2. construct a solution
-        let mut solution = Vec::new();
-        // TODO: far from optimal greedy solution...
-        for i in &candidates {
-            if intersect(&solution, i).is_none() {
-                solution.push(Segment { left: i.left, right: i.right });
-            }
-        }
-
-        // 3. Merge the blocks using the solution
-        let mut left_pos = 0;
-        let mut right_pos = 0;
-        let mut stack_frame = StackFrame::new(block_id);
-        for i in solution {
-            stack_frame.stack.extend_from_slice(&left[left_pos..i.left.0]);
-            left_pos = i.left.0;
-            stack_frame.stack.extend_from_slice(&right[right_pos..i.right.0]);
-            right_pos = i.right.0;
-            //merge i:
-            let left_ins = ctx.instruction(left[left_pos]).clone();
-            let right_ins = ctx.instruction(right[right_pos]).clone();
-            let assumption = &self[ctx[block_id].assumption];
-
-            let merged_op = match (&left_ins.operation, &right_ins.operation) {
-                (
-                    Operation::Call {
-                        func: left_func,
-                        arguments: left_arg,
-                        returned_arrays: left_arrays,
-                        location: left_location,
-                        ..
-                    },
-                    Operation::Call { func: right_func, arguments: right_arg, .. },
-                ) => {
-                    debug_assert_eq!(left_func, right_func);
-                    let mut args = Vec::new();
-                    for a in left_arg.iter().enumerate() {
-                        let op = Operation::Cond {
-                            condition: self[assumption.parent].condition,
-                            val_true: *a.1,
-                            val_false: right_arg[a.0],
-                        };
-                        let typ = ctx.object_type(*a.1);
-                        let arg_id = ctx.add_instruction(Instruction::new(op, typ, Some(block_id)));
-                        stack_frame.stack.push(arg_id);
-                        args.push(arg_id);
-                    }
-                    Operation::Call {
-                        func: *left_func,
-                        arguments: args,
-                        returned_arrays: left_arrays.clone(),
-                        predicate: self.root,
-                        location: *left_location,
-                    }
-                }
-                (
-                    Operation::Store {
-                        array_id: left_array,
-                        index: left_index,
-                        value: left_val,
-                        predicate: left_pred,
-                        location: left_loc,
-                    },
-                    Operation::Store {
-                        value: right_val,
-                        predicate: right_pred,
-                        location: right_loc,
-                        ..
-                    },
-                ) => {
-                    let pred = Self::or_conditions(*left_pred, *right_pred, &mut stack_frame, ctx);
-                    let op = Operation::Cond {
-                        condition: self[assumption.parent].condition,
-                        val_true: *left_val,
-                        val_false: *right_val,
-                    };
-                    let merge =
-                        Instruction::new(op, ctx.mem[*left_array].element_type, Some(block_id));
-                    let merge_id = ctx.add_instruction(merge);
-                    let location = RuntimeError::merge_location(*left_loc, *right_loc);
-                    stack_frame.stack.push(merge_id);
-                    Operation::Store {
-                        array_id: *left_array,
-                        index: *left_index,
-                        value: merge_id,
-                        predicate: pred,
-                        location,
-                    }
-                }
-                _ => unreachable!(),
-            };
-            if let Opcode::Call(_) = merged_op.opcode() {
-                let left_ins = ctx.instruction_mut(left[left_pos]);
-                left_ins.mark = node::Mark::ReplaceWith(right[right_pos]);
-            }
-            let ins1 = ctx.instruction_mut(right[right_pos]);
-            ins1.operation = merged_op;
-            stack_frame.stack.push(ins1.id);
-            left_pos += 1;
-            right_pos += 1;
-        }
-        stack_frame.stack.extend_from_slice(&left[left_pos..left.len()]);
-        stack_frame.stack.extend_from_slice(&right[right_pos..right.len()]);
-        stack_frame.stack
-    }
-}
-
-//unroll an if sub-graph
-pub(super) fn unroll_if(
-    ctx: &mut SsaContext,
-    unroll_ctx: &mut UnrollContext,
-) -> Result<BlockId, RuntimeError> {
-    //1. find the join block
-    let if_block = &ctx[unroll_ctx.to_unroll];
-    let left = if_block.left.unwrap();
-    let right = if_block.right.unwrap();
-    assert!(if_block.kind == BlockType::Normal);
-    let exit = block::find_join(ctx, if_block.id);
-
-    //2. create the IF subgraph
-    let (new_entry, new_exit) =
-        if unroll_ctx.unroll_into.is_dummy() || unroll_ctx.unroll_into == unroll_ctx.to_unroll {
-            // simple mode:
-            create_if_subgraph(ctx, unroll_ctx.to_unroll, true)
-        } else {
-            //the unroll_into is required and will be used as the prev block
-            let prev = unroll_ctx.unroll_into;
-            create_if_subgraph(ctx, prev, false)
-        };
-    unroll_ctx.unroll_into = new_entry;
-
-    //3 Process the entry_block
-    flatten::unroll_std_block(ctx, unroll_ctx)?;
-
-    //4. Process the THEN branch
-    let then_block = ctx[new_entry].left.unwrap();
-    let else_block = ctx[new_entry].right.unwrap();
-    unroll_ctx.to_unroll = left;
-    unroll_ctx.unroll_into = then_block;
-    flatten::unroll_until(ctx, unroll_ctx, exit)?;
-
-    //Plug to the exit:
-    ctx[unroll_ctx.unroll_into].left = Some(new_exit);
-    ctx[new_exit].predecessor.push(unroll_ctx.unroll_into);
-
-    //5. Process the ELSE branch
-    unroll_ctx.to_unroll = right;
-    unroll_ctx.unroll_into = else_block;
-    flatten::unroll_until(ctx, unroll_ctx, exit)?;
-    ctx[unroll_ctx.unroll_into].left = Some(new_exit);
-    ctx[new_exit].predecessor.push(unroll_ctx.unroll_into);
-
-    //6. Prepare the process for the JOIN
-    unroll_ctx.to_unroll = exit;
-    unroll_ctx.unroll_into = new_exit;
-
-    Ok(exit)
-}
-
-//create the subgraph for unrolling IF statement
-fn create_if_subgraph(
-    ctx: &mut SsaContext,
-    prev_block: BlockId,
-    simple_mode: bool,
-) -> (BlockId, BlockId) {
-    //Entry block
-    ctx.current_block = prev_block;
-    let new_entry = if simple_mode {
-        prev_block
-    } else {
-        block::new_sealed_block(ctx, block::BlockType::Normal, true)
-    };
-    //Then block
-    ctx.current_block = new_entry;
-    let new_then = block::new_sealed_block(ctx, block::BlockType::Normal, true);
-    //Else block
-    ctx.current_block = new_entry;
-    let new_else = block::new_sealed_block(ctx, block::BlockType::Normal, false);
-    //Exit block
-    let new_exit = block::new_sealed_block(ctx, block::BlockType::IfJoin, false);
-    ctx[new_exit].dominator = Some(new_entry);
-    ctx[new_entry].right = Some(new_else);
-    ctx[new_exit].predecessor.push(new_then);
-
-    (new_entry, new_exit)
-}
-
-#[derive(Debug)]
-struct Segment {
-    left: (usize, NodeId),
-    right: (usize, NodeId),
-}
-
-impl Segment {
-    fn new(left_node: (usize, &NodeId), right_node: (usize, &NodeId)) -> Segment {
-        Segment { left: (left_node.0, *left_node.1), right: (right_node.0, *right_node.1) }
-    }
-
-    fn intersect(&self, other: &Segment) -> bool {
-        !((self.right.0 < other.right.0 && self.left.0 < other.left.0)
-            || (self.right.0 > other.right.0 && self.left.0 > other.left.0))
-    }
-}
-
-fn intersect(solution: &[Segment], candidate: &Segment) -> Option<usize> {
-    for i in solution.iter().enumerate() {
-        if i.1.intersect(candidate) {
-            return Some(i.0);
-        }
-    }
-    None
-}
diff --git a/crates/noirc_evaluator/src/ssa/context.rs b/crates/noirc_evaluator/src/ssa/context.rs
deleted file mode 100644
index 0fecb633db6..00000000000
--- a/crates/noirc_evaluator/src/ssa/context.rs
+++ /dev/null
@@ -1,1305 +0,0 @@
-use crate::errors::{RuntimeError, RuntimeErrorKind};
-use crate::ssa::{
-    acir_gen::Acir,
-    block::{BasicBlock, BlockId},
-    conditional::{DecisionTree, TreeBuilder},
-    function::{FuncIndex, SsaFunction},
-    inline::StackFrame,
-    mem::{ArrayId, Memory},
-    node::{
-        BinaryOp, FunctionKind, Instruction, Mark, Node, NodeId, NodeObject, ObjectType, Operation,
-    },
-    {block, builtin, flatten, function, inline, integer, node, optimizations},
-};
-use crate::Evaluator;
-use acvm::FieldElement;
-use iter_extended::vecmap;
-use noirc_errors::Location;
-use noirc_frontend::monomorphization::ast::{Definition, Expression, FuncId, Literal, Type};
-use num_bigint::BigUint;
-use std::collections::{HashMap, HashSet};
-
-use super::node::Opcode;
-
-// This is a 'master' class for generating the SSA IR from the AST
-// It contains all the data; the node objects representing the source code in the nodes arena
-// and The CFG in the blocks arena
-// everything else just reference objects from these two arena using their index.
-pub(crate) struct SsaContext {
-    pub(crate) first_block: BlockId,
-    pub(crate) current_block: BlockId,
-    blocks: arena::Arena<block::BasicBlock>,
-    pub(crate) nodes: arena::Arena<node::NodeObject>,
-    value_names: HashMap<NodeId, u32>,
-    pub(crate) sealed_blocks: HashSet<BlockId>,
-    pub(crate) mem: Memory,
-
-    pub(crate) functions: HashMap<FuncId, function::SsaFunction>,
-    pub(crate) opcode_ids: HashMap<builtin::Opcode, NodeId>,
-    pub(crate) constants: HashMap<FieldElement, Vec<NodeId>>,
-
-    //Adjacency Matrix of the call graph; list of rows where each row indicates the functions called by the function whose FuncIndex is the row number
-    pub(crate) call_graph: Vec<Vec<u8>>,
-    dummy_store: HashMap<ArrayId, NodeId>,
-    dummy_load: HashMap<ArrayId, NodeId>,
-
-    //debug information
-    #[allow(dead_code)]
-    locations: HashMap<NodeId, Location>,
-}
-
-impl Default for SsaContext {
-    fn default() -> Self {
-        let mut pc = SsaContext {
-            first_block: BlockId::dummy(),
-            current_block: BlockId::dummy(),
-            blocks: arena::Arena::new(),
-            nodes: arena::Arena::new(),
-            value_names: HashMap::new(),
-            sealed_blocks: HashSet::new(),
-            mem: Memory::default(),
-            functions: HashMap::new(),
-            opcode_ids: HashMap::new(),
-            call_graph: Vec::new(),
-            dummy_store: HashMap::new(),
-            dummy_load: HashMap::new(),
-            locations: HashMap::new(),
-            constants: HashMap::new(),
-        };
-        block::create_first_block(&mut pc);
-        pc.one_with_type(ObjectType::boolean());
-        pc.zero_with_type(ObjectType::boolean());
-        pc
-    }
-}
-
-impl SsaContext {
-    pub(crate) fn zero(&self) -> NodeId {
-        self.find_const_with_type(&FieldElement::zero(), ObjectType::boolean()).unwrap()
-    }
-
-    pub(crate) fn one(&self) -> NodeId {
-        self.find_const_with_type(&FieldElement::one(), ObjectType::boolean()).unwrap()
-    }
-
-    pub(crate) fn zero_with_type(&mut self, obj_type: ObjectType) -> NodeId {
-        self.get_or_create_const(FieldElement::zero(), obj_type)
-    }
-
-    pub(crate) fn one_with_type(&mut self, obj_type: ObjectType) -> NodeId {
-        self.get_or_create_const(FieldElement::one(), obj_type)
-    }
-
-    pub(crate) fn is_one(&self, id: NodeId) -> bool {
-        if id == NodeId::dummy() {
-            return false;
-        }
-        let typ = self.object_type(id);
-        if let Some(one) = self.find_const_with_type(&FieldElement::one(), typ) {
-            id == one
-        } else {
-            false
-        }
-    }
-
-    pub(crate) fn is_zero(&self, id: NodeId) -> bool {
-        if id == NodeId::dummy() {
-            return false;
-        }
-        let typ = self.object_type(id);
-        if let Some(zero) = self.find_const_with_type(&FieldElement::zero(), typ) {
-            id == zero
-        } else {
-            false
-        }
-    }
-
-    pub(crate) fn get_dummy_store(&self, a: ArrayId) -> NodeId {
-        self.dummy_store[&a]
-    }
-
-    pub(crate) fn get_dummy_load(&self, a: ArrayId) -> NodeId {
-        self.dummy_load[&a]
-    }
-
-    #[allow(clippy::map_entry)]
-    pub(crate) fn add_dummy_load(&mut self, a: ArrayId) {
-        if !self.dummy_load.contains_key(&a) {
-            let op_a = Operation::Load { array_id: a, index: NodeId::dummy(), location: None };
-            let dummy_load = node::Instruction::new(op_a, self.mem[a].element_type, None);
-            let id = self.add_instruction(dummy_load);
-            self.dummy_load.insert(a, id);
-        }
-    }
-    #[allow(clippy::map_entry)]
-    pub(crate) fn add_dummy_store(&mut self, a: ArrayId) {
-        if !self.dummy_store.contains_key(&a) {
-            let op_a = Operation::Store {
-                array_id: a,
-                index: NodeId::dummy(),
-                value: NodeId::dummy(),
-                predicate: None,
-                location: None,
-            };
-            let dummy_store = node::Instruction::new(op_a, ObjectType::NotAnObject, None);
-            let id = self.add_instruction(dummy_store);
-            self.dummy_store.insert(a, id);
-        }
-    }
-
-    pub(crate) fn get_function_index(&self) -> FuncIndex {
-        FuncIndex::new(self.functions.values().len())
-    }
-
-    pub(crate) fn insert_block(&mut self, block: BasicBlock) -> &mut BasicBlock {
-        let id = self.blocks.insert(block);
-        let block = &mut self.blocks[id];
-        block.id = BlockId(id);
-        block
-    }
-
-    //Display an object for debugging purposes
-    fn id_to_string(&self, id: NodeId) -> String {
-        let mut result = String::new();
-        if let Some(var) = self.try_get_node(id) {
-            result = format!("{var}");
-        }
-        if result.is_empty() {
-            result = format!("unknown {:?}", id.0.into_raw_parts().0);
-        }
-        result
-    }
-
-    fn binary_to_string(&self, binary: &node::Binary) -> String {
-        let lhs = self.id_to_string(binary.lhs);
-        let rhs = self.id_to_string(binary.rhs);
-
-        format!("{} {lhs}, {rhs}", binary.operator)
-    }
-
-    pub(crate) fn operation_to_string(&self, op: &Operation) -> String {
-        let join = |args: &[NodeId]| vecmap(args, |arg| self.id_to_string(*arg)).join(", ");
-
-        match op {
-            Operation::Binary(binary) => self.binary_to_string(binary),
-            Operation::Cast(value) => format!("cast {}", self.id_to_string(*value)),
-            Operation::Truncate { value, bit_size, max_bit_size } => {
-                format!(
-                    "truncate {}, bit size = {bit_size}, max bit size = {max_bit_size}",
-                    self.id_to_string(*value),
-                )
-            }
-            Operation::Not(v) => format!("not {}", self.id_to_string(*v)),
-            Operation::Constrain(v, ..) => format!("constrain {}", self.id_to_string(*v)),
-            Operation::Jne(v, b) => format!("jne {}, {b:?}", self.id_to_string(*v)),
-            Operation::Jeq(v, b) => format!("jeq {}, {b:?}", self.id_to_string(*v)),
-            Operation::Jmp(b) => format!("jmp {b:?}"),
-            Operation::Phi { root, block_args } => {
-                let mut s = format!("phi {}", self.id_to_string(*root));
-                for (value, block) in block_args {
-                    s = format!(
-                        "{s}, {} from block {}",
-                        self.id_to_string(*value),
-                        block.0.into_raw_parts().0
-                    );
-                }
-                s
-            }
-            Operation::Cond { condition, val_true: lhs, val_false: rhs } => {
-                let lhs = self.id_to_string(*lhs);
-                let rhs = self.id_to_string(*rhs);
-                format!("cond({}) {lhs}, {rhs}", self.id_to_string(*condition))
-            }
-            Operation::Load { array_id, index, .. } => {
-                format!("load {array_id:?}, index {}", self.id_to_string(*index))
-            }
-            Operation::Store { array_id, index, value, predicate, .. } => {
-                let pred_str = if let Some(predicate) = predicate {
-                    format!(", predicate {}", self.id_to_string(*predicate))
-                } else {
-                    String::new()
-                };
-                format!(
-                    "store {array_id:?}, index {}, value {}{}",
-                    self.id_to_string(*index),
-                    self.id_to_string(*value),
-                    pred_str
-                )
-            }
-            Operation::Intrinsic(opcode, args) => format!("intrinsic {opcode}({})", join(args)),
-            Operation::Nop => "nop".into(),
-            Operation::Call { func, arguments, returned_arrays, .. } => {
-                let name = self.try_get_func_id(*func).map(|id| self.functions[&id].name.clone());
-                let name = name.unwrap_or_else(|| self.id_to_string(*func));
-                format!("call {name}({}) _ {returned_arrays:?}", join(arguments))
-            }
-            Operation::Return(values) => format!("return ({})", join(values)),
-            Operation::Result { call_instruction, index } => {
-                let call = self.id_to_string(*call_instruction);
-                format!("result {index} of {call}")
-            }
-        }
-    }
-
-    pub(crate) fn print_block(&self, b: &block::BasicBlock) {
-        println!("************* Block n.{}", b.id.0.into_raw_parts().0);
-        println!("Assumption:{:?}", b.assumption);
-        self.print_instructions(&b.instructions);
-        if b.left.is_some() {
-            println!("Next block: {}", b.left.unwrap().0.into_raw_parts().0);
-        }
-    }
-
-    pub(crate) fn print_instructions(&self, instructions: &[NodeId]) {
-        for id in instructions {
-            self.print_node(*id);
-        }
-    }
-
-    pub(crate) fn print_node(&self, id: NodeId) {
-        println!("{}", self.node_to_string(id));
-    }
-
-    pub(crate) fn node_to_string(&self, id: NodeId) -> String {
-        match self.try_get_node(id) {
-            Some(NodeObject::Instr(ins)) => {
-                let mut str_res = if ins.res_name.is_empty() {
-                    format!("{:?}", id.0.into_raw_parts().0)
-                } else {
-                    ins.res_name.clone()
-                };
-                if let Mark::ReplaceWith(replacement) = ins.mark {
-                    let new = self.node_to_string(replacement);
-                    str_res = format!(
-                        "{str_res} -REPLACED with ({}) {new},    original was",
-                        replacement.0.into_raw_parts().0,
-                    );
-                } else if ins.is_deleted() {
-                    str_res = format!("{str_res}: DELETED");
-                }
-                let ins_str = self.operation_to_string(&ins.operation);
-                format!("{str_res}: {ins_str}")
-            }
-            Some(other) => format!("{other}"),
-            None => format!("unknown {:?}", id.0.into_raw_parts().0),
-        }
-    }
-
-    pub(crate) fn print(&self, text: &str) {
-        println!("{text}");
-        for (_, b) in self.blocks.iter() {
-            self.print_block(b);
-        }
-    }
-
-    pub(crate) fn remove_block(&mut self, block: BlockId) {
-        self.blocks.remove(block.0);
-    }
-
-    /// Add an instruction to self.nodes and sets its id.
-    /// This function does NOT push the instruction to the current block.
-    /// See push_instruction for that.
-    pub(crate) fn add_instruction(&mut self, instruction: node::Instruction) -> NodeId {
-        let obj = NodeObject::Instr(instruction);
-        let id = NodeId(self.nodes.insert(obj));
-        match &mut self[id] {
-            NodeObject::Instr(i) => i.id = id,
-            _ => unreachable!(),
-        }
-
-        id
-    }
-
-    /// Adds the instruction to self.nodes and pushes it to the current block
-    pub(crate) fn push_instruction(&mut self, instruction: node::Instruction) -> NodeId {
-        let id = self.add_instruction(instruction);
-        if let NodeObject::Instr(_) = &self[id] {
-            self.get_current_block_mut().instructions.push(id);
-        }
-        id
-    }
-
-    /// Adds the instruction to self.nodes and insert it after phi instructions of the provided block
-    pub(crate) fn insert_instruction_after_phi(
-        &mut self,
-        instruction: node::Instruction,
-        block: BlockId,
-    ) -> NodeId {
-        let id = self.add_instruction(instruction);
-        let mut pos = 0;
-        for i in &self[block].instructions {
-            if let Some(ins) = self.try_get_instruction(*i) {
-                let op = ins.operation.opcode();
-                if op != node::Opcode::Nop && op != node::Opcode::Phi {
-                    break;
-                }
-            }
-            pos += 1;
-        }
-        self[block].instructions.insert(pos, id);
-        id
-    }
-
-    //add the instruction to the block, after the provided instruction
-    pub(crate) fn push_instruction_after(
-        &mut self,
-        instruction_id: NodeId,
-        block: BlockId,
-        after: NodeId,
-    ) -> NodeId {
-        let mut pos = 0;
-        for i in &self[block].instructions {
-            if after == *i {
-                break;
-            }
-            pos += 1;
-        }
-        self[block].instructions.insert(pos + 1, instruction_id);
-        instruction_id
-    }
-
-    pub(crate) fn add_const(&mut self, constant: node::Constant) -> NodeId {
-        let obj = NodeObject::Const(constant);
-        let id = NodeId(self.nodes.insert(obj));
-        match &mut self[id] {
-            NodeObject::Const(c) => c.id = id,
-            _ => unreachable!(),
-        }
-
-        id
-    }
-
-    pub(crate) fn ssa_func(&self, func_id: FuncId) -> Option<&SsaFunction> {
-        self.functions.get(&func_id)
-    }
-
-    pub(crate) fn try_get_func_id(&self, id: NodeId) -> Option<FuncId> {
-        match &self[id] {
-            NodeObject::Function(FunctionKind::Normal(id), ..) => Some(*id),
-            _ => None,
-        }
-    }
-
-    pub(crate) fn try_get_ssa_func(&self, id: NodeId) -> Option<&SsaFunction> {
-        self.try_get_func_id(id).and_then(|id| self.ssa_func(id))
-    }
-
-    pub(crate) fn dummy_id() -> arena::Index {
-        arena::Index::from_raw_parts(std::usize::MAX, 0)
-    }
-
-    pub(crate) fn try_get_node(&self, id: NodeId) -> Option<&node::NodeObject> {
-        self.nodes.get(id.0)
-    }
-
-    pub(crate) fn try_get_node_mut(&mut self, id: NodeId) -> Option<&mut node::NodeObject> {
-        self.nodes.get_mut(id.0)
-    }
-
-    pub(crate) fn object_type(&self, id: NodeId) -> node::ObjectType {
-        self[id].get_type()
-    }
-
-    //Returns the object value if it is a constant, None if not.
-    pub(crate) fn get_as_constant(&self, id: NodeId) -> Option<FieldElement> {
-        if let Some(node::NodeObject::Const(c)) = self.try_get_node(id) {
-            return Some(FieldElement::from_be_bytes_reduce(&c.value.to_bytes_be()));
-        }
-        None
-    }
-
-    pub(crate) fn instruction(&self, id: NodeId) -> &node::Instruction {
-        self.try_get_instruction(id).expect("Index not found or not an instruction")
-    }
-
-    pub(crate) fn instruction_mut(&mut self, id: NodeId) -> &mut node::Instruction {
-        self.try_get_mut_instruction(id).expect("Index not found or not an instruction")
-    }
-
-    pub(crate) fn try_get_instruction(&self, id: NodeId) -> Option<&node::Instruction> {
-        if let Some(NodeObject::Instr(i)) = self.try_get_node(id) {
-            return Some(i);
-        }
-        None
-    }
-
-    pub(crate) fn try_get_mut_instruction(&mut self, id: NodeId) -> Option<&mut node::Instruction> {
-        if let Some(NodeObject::Instr(i)) = self.try_get_node_mut(id) {
-            return Some(i);
-        }
-        None
-    }
-
-    pub(crate) fn get_variable(&self, id: NodeId) -> Result<&node::Variable, RuntimeErrorKind> {
-        match self.nodes.get(id.0) {
-            Some(t) => match t {
-                node::NodeObject::Variable(o) => Ok(o),
-                _ => Err(RuntimeErrorKind::UnstructuredError {
-                    message: "Not an object".to_string(),
-                }),
-            },
-            _ => Err(RuntimeErrorKind::UnstructuredError { message: "Invalid id".to_string() }),
-        }
-    }
-
-    pub(crate) fn get_mut_variable(
-        &mut self,
-        id: NodeId,
-    ) -> Result<&mut node::Variable, RuntimeErrorKind> {
-        match self.nodes.get_mut(id.0) {
-            Some(t) => match t {
-                node::NodeObject::Variable(o) => Ok(o),
-                _ => Err(RuntimeErrorKind::UnstructuredError {
-                    message: "Not an object".to_string(),
-                }),
-            },
-            _ => Err(RuntimeErrorKind::UnstructuredError { message: "Invalid id".to_string() }),
-        }
-    }
-
-    pub(crate) fn get_result_instruction_mut(
-        &mut self,
-        target: BlockId,
-        call_instruction: NodeId,
-        index: u32,
-    ) -> Option<&mut Instruction> {
-        for id in &self.blocks[target.0].instructions {
-            if let Some(NodeObject::Instr(i)) = self.nodes.get(id.0) {
-                if i.operation == (Operation::Result { call_instruction, index }) {
-                    let id = *id;
-                    return self.try_get_mut_instruction(id);
-                }
-            }
-        }
-        None
-    }
-
-    pub(crate) fn root_value(&self, id: NodeId) -> NodeId {
-        self.get_variable(id).map(|v| v.root()).unwrap_or(id)
-    }
-
-    pub(crate) fn add_variable(&mut self, obj: node::Variable, root: Option<NodeId>) -> NodeId {
-        let id = NodeId(self.nodes.insert(NodeObject::Variable(obj)));
-        match &mut self[id] {
-            node::NodeObject::Variable(v) => {
-                v.id = id;
-                v.root = root;
-            }
-            _ => unreachable!(),
-        }
-        id
-    }
-
-    pub(crate) fn update_variable_id_in_block(
-        &mut self,
-        var_id: NodeId,
-        new_var: NodeId,
-        new_value: NodeId,
-        block_id: BlockId,
-    ) {
-        let root_id = self.root_value(var_id);
-        let root = self.get_variable(root_id).unwrap();
-        let root_name = root.name.clone();
-        let cb = &mut self[block_id];
-        cb.update_variable(var_id, new_value);
-        let v_name = self.value_names.entry(var_id).or_insert(0);
-        *v_name += 1;
-        let variable_id = *v_name;
-
-        if let Ok(new_var) = self.get_mut_variable(new_var) {
-            new_var.name = format!("{root_name}{variable_id}");
-        }
-    }
-
-    //Returns true if a may be distinct from b, and false else
-    pub(crate) fn maybe_distinct(&self, a: NodeId, b: NodeId) -> bool {
-        if a == NodeId::dummy() || b == NodeId::dummy() {
-            return true;
-        }
-        if a == b {
-            return false;
-        }
-        if let (Some(a_value), Some(b_value)) = (self.get_as_constant(a), self.get_as_constant(b)) {
-            if a_value == b_value {
-                return false;
-            }
-        }
-        true
-    }
-
-    //Returns true if a may be equal to b, and false otherwise
-    pub(crate) fn maybe_equal(&self, a: NodeId, b: NodeId) -> bool {
-        if a == NodeId::dummy() || b == NodeId::dummy() {
-            return true;
-        }
-
-        if a == b {
-            return true;
-        }
-        if let (Some(a_value), Some(b_value)) = (self.get_as_constant(a), self.get_as_constant(b)) {
-            if a_value != b_value {
-                return false;
-            }
-        }
-        true
-    }
-
-    //same as update_variable but using the var index instead of var
-    pub(crate) fn update_variable_id(
-        &mut self,
-        var_id: NodeId,
-        new_var: NodeId,
-        new_value: NodeId,
-    ) {
-        self.update_variable_id_in_block(var_id, new_var, new_value, self.current_block);
-    }
-
-    pub(crate) fn new_instruction(
-        &mut self,
-        opcode: Operation,
-        op_type: ObjectType,
-    ) -> Result<NodeId, RuntimeError> {
-        //Add a new instruction to the nodes arena
-        let mut i = Instruction::new(opcode, op_type, Some(self.current_block));
-
-        //Basic simplification - we ignore RunTimeErrors when creating an instruction
-        //because they must be managed after handling conditionals. For instance if false { b } should not fail whatever b is doing.
-        optimizations::simplify(self, &mut i).ok();
-
-        if let Mark::ReplaceWith(replacement) = i.mark {
-            return Ok(replacement);
-        }
-        Ok(self.push_instruction(i))
-    }
-
-    pub(crate) fn find_const_with_type(
-        &self,
-        value: &FieldElement,
-        e_type: node::ObjectType,
-    ) -> Option<NodeId> {
-        // we look for the node in the constants map
-        if let Some(ids) = self.constants.get(value) {
-            for &id in ids {
-                if self[id].get_type() == e_type {
-                    return Some(id);
-                }
-            }
-        }
-        None
-    }
-
-    // Retrieve the object corresponding to the const value given in argument
-    // If such object does not exist, we create one
-    pub(crate) fn get_or_create_const(&mut self, x: FieldElement, t: node::ObjectType) -> NodeId {
-        let value = BigUint::from_bytes_be(&x.to_be_bytes());
-        if let Some(prev_const) = self.find_const_with_type(&x, t) {
-            return prev_const;
-        }
-
-        let id = self.add_const(node::Constant {
-            id: NodeId::dummy(),
-            value,
-            value_str: String::new(),
-            value_type: t,
-        });
-        // Adds the id into the constants map
-        let ids = self.constants.entry(x).or_default();
-        ids.push(id);
-        id
-    }
-
-    // Return the type of the operation result, based on the left hand type
-    pub(crate) fn get_result_type(
-        &self,
-        op: &Operation,
-        lhs_type: node::ObjectType,
-    ) -> node::ObjectType {
-        use {BinaryOp::*, Operation::*};
-        match op {
-            Binary(node::Binary { operator: Eq, .. })
-            | Binary(node::Binary { operator: Ne, .. })
-            | Binary(node::Binary { operator: Ult, .. })
-            | Binary(node::Binary { operator: Ule, .. })
-            | Binary(node::Binary { operator: Slt, .. })
-            | Binary(node::Binary { operator: Sle, .. })
-            | Binary(node::Binary { operator: Lt, .. })
-            | Binary(node::Binary { operator: Lte, .. }) => ObjectType::boolean(),
-            Operation::Jne(_, _)
-            | Operation::Jeq(_, _)
-            | Operation::Jmp(_)
-            | Operation::Nop
-            | Operation::Constrain(..)
-            | Operation::Store { .. } => ObjectType::NotAnObject,
-            Operation::Load { array_id, .. } => self.mem[*array_id].element_type,
-            Operation::Cast(_) | Operation::Truncate { .. } => {
-                unreachable!("cannot determine result type")
-            }
-            _ => lhs_type,
-        }
-    }
-
-    pub(crate) fn new_array(
-        &mut self,
-        name: &str,
-        element_type: ObjectType,
-        len: u32,
-        def: Option<Definition>,
-    ) -> (NodeId, ArrayId) {
-        let array_index = self.mem.create_new_array(len, element_type, name);
-        self.add_dummy_load(array_index);
-        self.add_dummy_store(array_index);
-        //we create a variable pointing to this MemArray
-        let new_var = node::Variable {
-            id: NodeId::dummy(),
-            obj_type: ObjectType::ArrayPointer(array_index),
-            name: name.to_string(),
-            root: None,
-            def: def.clone(),
-            witness: None,
-            parent_block: self.current_block,
-        };
-        if let Some(def) = def {
-            self.mem[array_index].def = def;
-        }
-        (self.add_variable(new_var, None), array_index)
-    }
-
-    // Returns the value of the element array[index], if it exists in the memory_map
-    pub(crate) fn get_indexed_value(&self, array_id: ArrayId, index: NodeId) -> Option<&NodeId> {
-        if let Some(idx) = Memory::to_u32(self, index) {
-            self.mem.get_value_from_map(array_id, idx)
-        } else {
-            None
-        }
-    }
-
-    pub(crate) fn try_get_block_mut(&mut self, id: BlockId) -> Option<&mut block::BasicBlock> {
-        self.blocks.get_mut(id.0)
-    }
-
-    pub(crate) fn get_current_block(&self) -> &block::BasicBlock {
-        &self[self.current_block]
-    }
-
-    pub(crate) fn get_current_block_mut(&mut self) -> &mut block::BasicBlock {
-        let current = self.current_block;
-        &mut self[current]
-    }
-
-    pub(crate) fn iter_blocks(&self) -> impl Iterator<Item = &BasicBlock> {
-        self.blocks.iter().map(|(_id, block)| block)
-    }
-
-    pub(crate) fn log(&self, show_log: bool, before: &str, after: &str) {
-        if show_log {
-            self.print(before);
-            println!("{after}");
-        }
-    }
-
-    //Optimize, flatten and truncate IR and then generates ACIR representation from it
-    pub(crate) fn ir_to_acir(
-        &mut self,
-        evaluator: &mut Evaluator,
-        enable_logging: bool,
-        show_output: bool,
-    ) -> Result<(), RuntimeError> {
-        //SSA
-        self.log(enable_logging, "SSA:", "\ninline functions");
-        function::inline_all(self)?;
-
-        //Optimization
-        block::compute_dom(self);
-        optimizations::full_cse(self, self.first_block, false)?;
-        // The second cse is recommended because of opportunities occurring from the first one
-        // we could use an optimization level that will run more cse pass
-        optimizations::full_cse(self, self.first_block, false)?;
-        //flattening
-        self.log(enable_logging, "\nCSE:", "\nunrolling:");
-        //Unrolling
-        flatten::unroll_tree(self, self.first_block)?;
-        //reduce conditionals
-        let mut decision = DecisionTree::new(self);
-        let builder = TreeBuilder::new(self.first_block);
-        decision.make_decision_tree(self, builder)?;
-        decision.reduce(self, decision.root)?;
-        //Inlining
-        self.log(enable_logging, "reduce", "\ninlining:");
-        inline::inline_tree(self, self.first_block, &decision)?;
-
-        block::merge_path(self, self.first_block, BlockId::dummy(), None)?;
-        //The CFG is now fully flattened, so we keep only the first block.
-        let mut to_remove = Vec::new();
-        for b in &self.blocks {
-            if b.0 != self.first_block.0 {
-                to_remove.push(b.0);
-            }
-        }
-        for b in to_remove {
-            self.blocks.remove(b);
-        }
-        let first_block = self.first_block;
-        self[first_block].dominated.clear();
-
-        optimizations::cse(self, first_block, true)?;
-        //Truncation
-        integer::overflow_strategy(self)?;
-        self.log(enable_logging, "\noverflow:", "");
-        //ACIR
-        let mut acir = Acir::default();
-        acir.acir_gen(evaluator, self, &self[self.first_block], show_output)?;
-        if enable_logging {
-            print_acir_circuit(&evaluator.opcodes);
-            println!("DONE");
-            println!("ACIR opcodes generated : {}", evaluator.opcodes.len());
-        }
-        Ok(())
-    }
-
-    pub(crate) fn generate_empty_phi(&mut self, target_block: BlockId, phi_root: NodeId) -> NodeId {
-        //Ensure there is not already a phi for the variable (n.b. probably not useful)
-        for i in &self[target_block].instructions {
-            match self.try_get_instruction(*i) {
-                Some(Instruction { operation: Operation::Phi { root, .. }, .. })
-                    if *root == phi_root =>
-                {
-                    return *i;
-                }
-                _ => (),
-            }
-        }
-
-        let v_type = self.object_type(phi_root);
-        let operation = Operation::Phi { root: phi_root, block_args: vec![] };
-        let new_phi = Instruction::new(operation, v_type, Some(target_block));
-        let phi_id = self.add_instruction(new_phi);
-        self[target_block].instructions.insert(1, phi_id);
-        phi_id
-    }
-
-    fn memcpy(&mut self, l_type: ObjectType, r_type: ObjectType) -> Result<(), RuntimeError> {
-        if l_type == r_type {
-            return Ok(());
-        }
-
-        if let (ObjectType::ArrayPointer(a), ObjectType::ArrayPointer(b)) = (l_type, r_type) {
-            let len = self.mem[a].len;
-            let e_type = self.mem[b].element_type;
-            for i in 0..len {
-                let idx_b = self.get_or_create_const(
-                    FieldElement::from(i as i128),
-                    ObjectType::unsigned_integer(32),
-                );
-                let idx_a = self.get_or_create_const(
-                    FieldElement::from(i as i128),
-                    ObjectType::unsigned_integer(32),
-                );
-                let op_b = Operation::Load { array_id: b, index: idx_b, location: None };
-                let load = self.new_instruction(op_b, e_type)?;
-                let op_a = Operation::Store {
-                    array_id: a,
-                    index: idx_a,
-                    value: load,
-                    predicate: None,
-                    location: None,
-                };
-                self.new_instruction(op_a, l_type)?;
-            }
-        } else {
-            unreachable!("invalid type, expected arrays, got {:?} and {:?}", l_type, r_type);
-        }
-
-        Ok(())
-    }
-
-    //This function handles assignment statements of the form lhs = rhs, depending on the nature of the arguments:
-    // lhs can be: standard variable, array, array element (in which case we have an index)
-    // rhs can be: standard variable, array, array element (depending on lhs type), call instruction, intrinsic, other instruction
-    // For instance:
-    // - if lhs and rhs are standard variables, we create a new ssa variable of lhs
-    // - if lhs is an array element, we generate a store instruction
-    // - if lhs and rhs are arrays, we perform a copy of rhs into lhs,
-    // - if lhs is an array and rhs is a call instruction, we indicate in the call that lhs is the returned array (so that no copy is needed because the inlining will use it)
-    // ...
-    pub(crate) fn handle_assign(
-        &mut self,
-        lhs: NodeId,
-        index: Option<NodeId>,
-        rhs: NodeId,
-        location: Option<Location>,
-    ) -> Result<NodeId, RuntimeError> {
-        let lhs_type = self.object_type(lhs);
-        let rhs_type = self.object_type(rhs);
-
-        let mut ret_array = None;
-        if let Some(Instruction {
-            operation: Operation::Result { call_instruction: func, index: idx },
-            ..
-        }) = self.try_get_instruction(rhs)
-        {
-            if index.is_none() {
-                if let ObjectType::ArrayPointer(a) = lhs_type {
-                    ret_array = Some((*func, a, *idx));
-                }
-            }
-        }
-
-        if let Some((func, a, idx)) = ret_array {
-            if let Some(Instruction {
-                operation: Operation::Call { returned_arrays, arguments, .. },
-                ..
-            }) = self.try_get_mut_instruction(func)
-            {
-                returned_arrays.push((a, idx));
-                //Issue #579: we initialize the array, unless it is also in arguments in which case it is already initialized.
-                let mut init = false;
-                for i in arguments.clone() {
-                    if let ObjectType::ArrayPointer(b) = self.object_type(i) {
-                        if a == b {
-                            init = true;
-                        }
-                    }
-                }
-                if !init {
-                    let mut stack = StackFrame::new(self.current_block);
-                    self.init_array(a, &mut stack);
-                    let pos = self[self.current_block]
-                        .instructions
-                        .iter()
-                        .position(|x| *x == func)
-                        .unwrap();
-                    let current_block = self.current_block;
-                    for i in stack.stack {
-                        self[current_block].instructions.insert(pos, i);
-                    }
-                }
-            }
-            if let Some(i) = self.try_get_mut_instruction(rhs) {
-                i.mark = Mark::ReplaceWith(lhs);
-            }
-            return Ok(lhs);
-        }
-
-        if let Some(idx) = index {
-            if let ObjectType::ArrayPointer(a) = lhs_type {
-                //Store
-                let op_a = Operation::Store {
-                    array_id: a,
-                    index: idx,
-                    value: rhs,
-                    predicate: None,
-                    location,
-                };
-                return self.new_instruction(op_a, self.mem[a].element_type);
-            } else {
-                unreachable!("Index expression must be for an array");
-            }
-        } else if matches!(lhs_type, ObjectType::ArrayPointer(_)) {
-            if let Some(Instruction {
-                operation: Operation::Intrinsic(_, _),
-                res_type: result_type,
-                ..
-            }) = self.try_get_mut_instruction(rhs)
-            {
-                *result_type = lhs_type;
-                return Ok(lhs);
-            } else {
-                self.memcpy(lhs_type, rhs_type)?;
-                return Ok(lhs);
-            }
-        }
-        let lhs_obj = self.get_variable(lhs).unwrap();
-        let new_var = node::Variable {
-            id: lhs,
-            obj_type: lhs_type,
-            name: String::new(),
-            root: None,
-            def: lhs_obj.def.clone(),
-            witness: None,
-            parent_block: self.current_block,
-        };
-        let ls_root = lhs_obj.root();
-        //ssa: we create a new variable a1 linked to a
-        let new_var_id = self.add_variable(new_var, Some(ls_root));
-        let op = Operation::Binary(node::Binary {
-            lhs: new_var_id,
-            rhs,
-            operator: node::BinaryOp::Assign,
-            predicate: None,
-        });
-        let result = self.new_instruction(op, rhs_type)?;
-        self.update_variable_id(ls_root, new_var_id, result); //update the name and the value map
-        Ok(new_var_id)
-    }
-
-    fn new_instruction_inline(
-        &mut self,
-        operation: node::Operation,
-        op_type: node::ObjectType,
-        stack_frame: &mut StackFrame,
-    ) -> NodeId {
-        let i = node::Instruction::new(operation, op_type, Some(stack_frame.block));
-        let ins_id = self.add_instruction(i);
-        stack_frame.push(ins_id);
-        ins_id
-    }
-
-    fn init_array(&mut self, array_id: ArrayId, stack_frame: &mut StackFrame) {
-        let len = self.mem[array_id].len as usize;
-        let e_type = self.mem[array_id].element_type;
-        let values = vec![self.zero_with_type(e_type); len];
-        self.init_array_from_values(array_id, values, stack_frame);
-    }
-
-    pub(crate) fn init_array_from_values(
-        &mut self,
-        array_id: ArrayId,
-        values: Vec<NodeId>,
-        stack_frame: &mut StackFrame,
-    ) {
-        let len = self.mem[array_id].len as usize;
-        let e_type = self.mem[array_id].element_type;
-        assert_eq!(len, values.len());
-        for (i, v) in values.iter().enumerate() {
-            let index = self.get_or_create_const(
-                FieldElement::from(i as i128),
-                ObjectType::unsigned_integer(32),
-            );
-            let op_a =
-                Operation::Store { array_id, index, value: *v, predicate: None, location: None };
-            self.new_instruction_inline(op_a, e_type, stack_frame);
-        }
-    }
-
-    pub(crate) fn memcpy_inline(
-        &mut self,
-        l_type: ObjectType,
-        r_type: ObjectType,
-        stack_frame: &mut StackFrame,
-    ) {
-        if l_type == r_type {
-            return;
-        }
-
-        if let (ObjectType::ArrayPointer(a), ObjectType::ArrayPointer(b)) = (l_type, r_type) {
-            let len = self.mem[a].len;
-            let e_type = self.mem[b].element_type;
-            for i in 0..len {
-                let idx_b = self.get_or_create_const(
-                    FieldElement::from(i as i128),
-                    ObjectType::unsigned_integer(32),
-                );
-                let idx_a = self.get_or_create_const(
-                    FieldElement::from(i as i128),
-                    ObjectType::unsigned_integer(32),
-                );
-                let op_b = Operation::Load { array_id: b, index: idx_b, location: None };
-                let load = self.new_instruction_inline(op_b, e_type, stack_frame);
-                let op_a = Operation::Store {
-                    array_id: a,
-                    index: idx_a,
-                    value: load,
-                    predicate: None,
-                    location: None,
-                };
-                self.new_instruction_inline(op_a, l_type, stack_frame);
-            }
-        } else {
-            unreachable!("invalid type, expected arrays");
-        }
-    }
-
-    pub(crate) fn handle_assign_inline(
-        &mut self,
-        lhs: NodeId,
-        rhs: NodeId,
-        stack_frame: &mut inline::StackFrame,
-        block_id: BlockId,
-    ) -> NodeId {
-        let lhs_type = self.object_type(lhs);
-        let rhs_type = self.object_type(rhs);
-        if let ObjectType::ArrayPointer(a) = lhs_type {
-            //Array
-            let b = stack_frame.get_or_default(a);
-            self.memcpy_inline(ObjectType::ArrayPointer(b), rhs_type, stack_frame);
-            lhs
-        } else {
-            //new ssa
-            let lhs_obj = self.get_variable(lhs).unwrap();
-            let new_var = node::Variable {
-                id: NodeId::dummy(),
-                obj_type: lhs_type,
-                name: String::new(),
-                root: None,
-                def: lhs_obj.def.clone(),
-                witness: None,
-                parent_block: self.current_block,
-            };
-            let ls_root = lhs_obj.root();
-            //ssa: we create a new variable a1 linked to a
-            let new_var_id = self.add_variable(new_var, Some(ls_root));
-            //ass
-            let op = Operation::Binary(node::Binary {
-                lhs: new_var_id,
-                rhs,
-                operator: node::BinaryOp::Assign,
-                predicate: None,
-            });
-            let result = self.new_instruction_inline(op, rhs_type, stack_frame);
-            self.update_variable_id_in_block(ls_root, new_var_id, result, block_id); //update the name and the value map
-            result
-        }
-    }
-
-    pub(crate) fn under_assumption(&self, predicate: NodeId) -> bool {
-        !(predicate == NodeId::dummy() || predicate == self.one())
-    }
-
-    //Returns the instruction used by a IF statement. None if the block is not a IF block.
-    pub(crate) fn get_if_condition(&self, block: &BasicBlock) -> Option<&node::Instruction> {
-        if let Some(ins) = self.try_get_instruction(*block.instructions.last().unwrap()) {
-            if !block.is_join() && ins.operation.opcode() == super::node::Opcode::Jeq {
-                return Some(ins);
-            }
-        }
-        None
-    }
-
-    //Generate a new variable v and a phi instruction s.t. v = phi(a,b);
-    // c is a counter used to name the variable v for debugging purposes
-    // when a and b are pointers, we create a new array s.t v[i] = phi(a[i],b[i])
-    pub(crate) fn new_phi(&mut self, a: NodeId, b: NodeId, c: &mut u32) -> NodeId {
-        if a == NodeId::dummy() || b == NodeId::dummy() {
-            return NodeId::dummy();
-        }
-        if let Some(ins) = self.try_get_instruction(a) {
-            if ins.operation.opcode() == Opcode::Nop {
-                assert_eq!(self.try_get_instruction(b).unwrap().operation.opcode(), Opcode::Nop);
-                return NodeId::dummy();
-            }
-        }
-
-        let exit_block = self.current_block;
-        let block1 = self[exit_block].predecessor[0];
-        let block2 = self[exit_block].predecessor[1];
-
-        let a_type = self.object_type(a);
-
-        let name = format!("if_{}_ret{c}", exit_block.0.into_raw_parts().0);
-        *c += 1;
-        if let ObjectType::ArrayPointer(adr1) = a_type {
-            let len = self.mem[adr1].len;
-            let el_type = self.mem[adr1].element_type;
-            let (id, array_id) = self.new_array(&name, el_type, len, None);
-            for i in 0..len {
-                let index = self
-                    .get_or_create_const(FieldElement::from(i as u128), ObjectType::native_field());
-                self.current_block = block1;
-                let op = Operation::Load { array_id: adr1, index, location: None };
-                let v1 = self.new_instruction(op, el_type).unwrap();
-                self.current_block = block2;
-                let adr2 = super::mem::Memory::deref(self, b).unwrap();
-                let op = Operation::Load { array_id: adr2, index, location: None };
-                let v2 = self.new_instruction(op, el_type).unwrap();
-                self.current_block = exit_block;
-                let v = self.new_phi(v1, v2, c);
-                let op =
-                    Operation::Store { array_id, index, value: v, predicate: None, location: None };
-                self.new_instruction(op, el_type).unwrap();
-            }
-            id
-        } else {
-            let new_var = node::Variable::new(a_type, name, None, exit_block);
-            let v = self.add_variable(new_var, None);
-            let operation = Operation::Phi { root: v, block_args: vec![(a, block1), (b, block2)] };
-            let new_phi = node::Instruction::new(operation, a_type, Some(exit_block));
-            let phi_id = self.add_instruction(new_phi);
-            self[exit_block].instructions.insert(1, phi_id);
-            phi_id
-        }
-    }
-
-    pub(crate) fn push_function_id(&mut self, func_id: FuncId, name: &str) -> NodeId {
-        let index = self.nodes.insert_with(|index| {
-            let node_id = NodeId(index);
-            NodeObject::Function(FunctionKind::Normal(func_id), node_id, name.to_owned())
-        });
-
-        NodeId(index)
-    }
-
-    /// Return the standard NodeId for this FuncId.
-    /// The 'standard' NodeId is just the NodeId assigned to the function when it
-    /// is first compiled so that repeated NodeObjs are not made for the same function.
-    /// If this function returns None, it means the given FuncId has yet to be compiled.
-    pub(crate) fn get_function_node_id(&self, func_id: FuncId) -> Option<NodeId> {
-        self.functions.get(&func_id).map(|f| f.node_id)
-    }
-
-    pub(crate) fn function_already_compiled(&self, func_id: FuncId) -> bool {
-        self.ssa_func(func_id).is_some()
-    }
-
-    pub(crate) fn get_or_create_opcode_node_id(&mut self, opcode: builtin::Opcode) -> NodeId {
-        if let Some(id) = self.opcode_ids.get(&opcode) {
-            return *id;
-        }
-
-        let index = self.nodes.insert_with(|index| {
-            NodeObject::Function(FunctionKind::Builtin(opcode), NodeId(index), opcode.to_string())
-        });
-        self.opcode_ids.insert(opcode, NodeId(index));
-        NodeId(index)
-    }
-
-    pub(crate) fn get_builtin_opcode(
-        &self,
-        node_id: NodeId,
-        arguments: &[Expression],
-    ) -> Option<builtin::Opcode> {
-        match &self[node_id] {
-            NodeObject::Function(FunctionKind::Builtin(opcode), ..) => match opcode {
-                builtin::Opcode::Println(_) => {
-                    // Compiler sanity check. This should be caught during typechecking
-                    assert_eq!(
-                        arguments.len(),
-                        1,
-                        "print statements currently only support one argument"
-                    );
-                    let is_string = match &arguments[0] {
-                        Expression::Ident(ident) => match ident.typ {
-                            Type::String(_) => true,
-                            Type::Tuple(_) => {
-                                unreachable!("logging structs/tuples is not supported")
-                            }
-                            Type::Function { .. } => {
-                                unreachable!("logging functions is not supported")
-                            }
-                            _ => false,
-                        },
-                        Expression::Literal(literal) => matches!(literal, Literal::Str(_)),
-                        _ => unreachable!("logging this expression type is not supported"),
-                    };
-                    Some(builtin::Opcode::Println(builtin::PrintlnInfo {
-                        is_string_output: is_string,
-                        show_output: true,
-                    }))
-                }
-                _ => Some(*opcode),
-            },
-            _ => None,
-        }
-    }
-
-    pub(crate) fn convert_type(&mut self, t: &Type) -> ObjectType {
-        use noirc_frontend::Signedness;
-        match t {
-            Type::Bool => ObjectType::boolean(),
-            Type::Field => ObjectType::native_field(),
-            Type::Integer(sign, bit_size) => {
-                assert!(
-                    *bit_size < super::integer::short_integer_max_bit_size(),
-                    "long integers are not yet supported"
-                );
-                match sign {
-                    Signedness::Signed => ObjectType::signed_integer(*bit_size),
-                    Signedness::Unsigned => ObjectType::unsigned_integer(*bit_size),
-                }
-            }
-            Type::Array(..) => panic!("Cannot convert an array type {t} into an ObjectType since it is unknown which array it refers to"),
-            Type::MutableReference(..) => panic!("Mutable reference types are unimplemented in the old ssa backend"),
-            Type::Unit => ObjectType::NotAnObject,
-            Type::Function(..) => ObjectType::Function,
-            Type::Tuple(_) => todo!("Conversion to ObjectType is unimplemented for tuples"),
-            Type::String(_) => todo!("Conversion to ObjectType is unimplemented for strings"),
-            Type::Slice(_) => todo!("Conversion to ObjectType is unimplemented for slices"),
-        }
-    }
-
-    pub(crate) fn add_predicate(
-        &mut self,
-        pred: NodeId,
-        instruction: &mut Instruction,
-        stack: &mut StackFrame,
-    ) {
-        let op = &mut instruction.operation;
-
-        match op {
-            Operation::Binary(bin) => {
-                assert!(bin.predicate.is_none());
-                let cond = if let Some(pred_ins) = bin.predicate {
-                    assert_ne!(pred_ins, NodeId::dummy());
-                    if pred == NodeId::dummy() {
-                        pred_ins
-                    } else {
-                        let op = Operation::Binary(node::Binary {
-                            lhs: pred,
-                            rhs: pred_ins,
-                            operator: BinaryOp::Mul,
-                            predicate: None,
-                        });
-                        let cond = self.add_instruction(Instruction::new(
-                            op,
-                            ObjectType::boolean(),
-                            Some(stack.block),
-                        ));
-                        optimizations::simplify_id(self, cond).unwrap();
-                        stack.push(cond);
-                        cond
-                    }
-                } else {
-                    pred
-                };
-                bin.predicate = Some(cond);
-            }
-            Operation::Constrain(cond, _) => {
-                let operation =
-                    Operation::Cond { condition: pred, val_true: *cond, val_false: self.one() };
-                let c_ins = self.add_instruction(Instruction::new(
-                    operation,
-                    ObjectType::boolean(),
-                    Some(stack.block),
-                ));
-                stack.push(c_ins);
-                *cond = c_ins;
-            }
-            _ => unreachable!(),
-        }
-    }
-}
-
-impl std::ops::Index<BlockId> for SsaContext {
-    type Output = BasicBlock;
-
-    fn index(&self, index: BlockId) -> &Self::Output {
-        &self.blocks[index.0]
-    }
-}
-
-impl std::ops::IndexMut<BlockId> for SsaContext {
-    fn index_mut(&mut self, index: BlockId) -> &mut Self::Output {
-        &mut self.blocks[index.0]
-    }
-}
-
-impl std::ops::Index<NodeId> for SsaContext {
-    type Output = NodeObject;
-
-    fn index(&self, index: NodeId) -> &Self::Output {
-        &self.nodes[index.0]
-    }
-}
-
-impl std::ops::IndexMut<NodeId> for SsaContext {
-    fn index_mut(&mut self, index: NodeId) -> &mut Self::Output {
-        &mut self.nodes[index.0]
-    }
-}
-
-// Prints a list of ACIR opcodes.
-// This is only used for logging.
-fn print_acir_circuit(opcodes: &[acvm::acir::circuit::Opcode]) {
-    for opcode in opcodes {
-        println!("{opcode:?}");
-    }
-}
diff --git a/crates/noirc_evaluator/src/ssa/flatten.rs b/crates/noirc_evaluator/src/ssa/flatten.rs
deleted file mode 100644
index 66f90c72190..00000000000
--- a/crates/noirc_evaluator/src/ssa/flatten.rs
+++ /dev/null
@@ -1,385 +0,0 @@
-use crate::errors::RuntimeError;
-use crate::ssa::{
-    block::BlockId,
-    context::SsaContext,
-    node::{BinaryOp, Mark, Node, NodeEval, NodeId, NodeObject, Operation},
-    {block, node, optimizations},
-};
-use acvm::FieldElement;
-use std::collections::HashMap;
-
-//Unroll the CFG
-pub(super) fn unroll_tree(
-    ctx: &mut SsaContext,
-    block_id: BlockId,
-) -> Result<HashMap<NodeId, NodeEval>, RuntimeError> {
-    //call unroll_tree from the root
-    assert!(!ctx[block_id].is_join());
-    let mut unroll_ctx = UnrollContext {
-        deprecated: Vec::new(),
-        to_unroll: block_id,
-        unroll_into: block_id,
-        eval_map: HashMap::new(),
-    };
-    while !unroll_ctx.to_unroll.is_dummy() {
-        unroll_block(ctx, &mut unroll_ctx)?;
-    }
-    //clean-up
-    for b in unroll_ctx.deprecated {
-        assert!(b != ctx.first_block);
-        ctx.remove_block(b);
-    }
-    block::compute_dom(ctx);
-
-    Ok(unroll_ctx.eval_map)
-}
-
-//Update the block instruction list using the eval_map
-fn eval_block(block_id: BlockId, eval_map: &HashMap<NodeId, NodeEval>, ctx: &mut SsaContext) {
-    for i in &ctx[block_id].instructions.clone() {
-        if let Some(ins) = ctx.try_get_mut_instruction(*i) {
-            ins.operation = update_operator(&ins.operation, eval_map);
-            let ins_id = ins.id;
-            // We ignore RunTimeErrors at this stage because unrolling is done before conditionals
-            // While failures must be managed after handling conditionals: For instance if false { b } should not fail whatever b is doing.
-            optimizations::simplify_id(ctx, ins_id).ok();
-        }
-    }
-}
-
-fn update_operator(operator: &Operation, eval_map: &HashMap<NodeId, NodeEval>) -> Operation {
-    operator.map_id(|id| eval_map.get(&id).and_then(|value| value.into_node_id()).unwrap_or(id))
-}
-
-//Unroll from unroll_ctx.to_unroll until it reaches unroll_ctx.unroll_into
-pub(super) fn unroll_until(
-    ctx: &mut SsaContext,
-    unroll_ctx: &mut UnrollContext,
-    end: BlockId,
-) -> Result<BlockId, RuntimeError> {
-    let mut b = unroll_ctx.to_unroll;
-    let mut prev = BlockId::dummy();
-
-    while b != end {
-        assert!(!b.is_dummy(), "could not reach end block");
-        prev = b;
-        unroll_block(ctx, unroll_ctx)?;
-        b = unroll_ctx.to_unroll;
-    }
-    Ok(prev)
-}
-
-pub(super) fn unroll_block(
-    ctx: &mut SsaContext,
-    unroll_ctx: &mut UnrollContext,
-) -> Result<(), RuntimeError> {
-    match ctx[unroll_ctx.to_unroll].kind {
-        block::BlockType::ForJoin => {
-            unroll_join(ctx, unroll_ctx)?;
-        }
-        _ => {
-            if ctx[unroll_ctx.to_unroll].right.is_some() {
-                if unroll_ctx.unroll_into == BlockId::dummy() {
-                    unroll_ctx.unroll_into = unroll_ctx.to_unroll;
-                }
-                crate::ssa::conditional::unroll_if(ctx, unroll_ctx)?;
-            } else {
-                unroll_std_block(ctx, unroll_ctx)?;
-            }
-        }
-    }
-    Ok(())
-}
-
-//unroll a normal block by generating new instructions into the target block, or by updating its instructions if no target is specified, using and updating the eval_map
-pub(super) fn unroll_std_block(
-    ctx: &mut SsaContext,
-    unroll_ctx: &mut UnrollContext,
-) -> Result<Option<BlockId>, RuntimeError> // The left block
-{
-    if unroll_ctx.to_unroll == unroll_ctx.unroll_into {
-        //We update block instructions from the eval_map
-        eval_block(unroll_ctx.to_unroll, &unroll_ctx.eval_map, ctx);
-        let block = &ctx[unroll_ctx.to_unroll];
-        unroll_ctx.to_unroll = block.left.unwrap_or_else(BlockId::dummy);
-        return Ok(block.left);
-    }
-    let block = &ctx[unroll_ctx.to_unroll];
-    let b_instructions = block.instructions.clone();
-    let next = block.left.unwrap_or_else(BlockId::dummy);
-    ctx.current_block = unroll_ctx.unroll_into;
-
-    for i_id in &b_instructions {
-        match &ctx[*i_id] {
-            node::NodeObject::Instr(i) => {
-                let new_op = i.operation.map_id(|id| {
-                    get_current_value(id, &unroll_ctx.eval_map).into_node_id().unwrap()
-                });
-                let mut new_ins =
-                    node::Instruction::new(new_op, i.res_type, Some(unroll_ctx.unroll_into));
-                match i.operation {
-                    Operation::Binary(node::Binary { operator: BinaryOp::Assign, .. }) => {
-                        unreachable!("unsupported instruction type when unrolling: assign");
-                        //To support assignments, we should create a new variable and updates the eval_map with it
-                        //however assignments should have already been removed by copy propagation.
-                    }
-                    Operation::Jmp(block) => assert_eq!(block, next),
-                    Operation::Nop => (),
-                    _ => {
-                        optimizations::simplify(ctx, &mut new_ins).ok(); //ignore RuntimeErrors until conditionals are processed
-                        match new_ins.mark {
-                            Mark::None => {
-                                let id = ctx.push_instruction(new_ins);
-                                unroll_ctx.eval_map.insert(*i_id, NodeEval::VarOrInstruction(id));
-                            }
-                            Mark::Deleted => (),
-                            Mark::ReplaceWith(replacement) => {
-                                // TODO: Should we insert into unrolled_instructions as well?
-                                // If optimizations::simplify replaces with a constant then we should not,
-                                // otherwise it may make sense if it is not already inserted.
-                                unroll_ctx
-                                    .eval_map
-                                    .insert(*i_id, NodeEval::VarOrInstruction(replacement));
-                            }
-                        }
-                    }
-                }
-            }
-            _ => unreachable!("Block instruction list should only only contain instruction"),
-        }
-    }
-    if unroll_ctx.to_unroll != unroll_ctx.unroll_into
-        && !unroll_ctx.deprecated.contains(&unroll_ctx.to_unroll)
-    {
-        unroll_ctx.deprecated.push(unroll_ctx.to_unroll);
-    }
-    unroll_ctx.to_unroll = next;
-    Ok(Some(next))
-}
-
-pub(super) fn unroll_join(
-    ssa_ctx: &mut SsaContext,
-    unroll_ctx: &mut UnrollContext,
-) -> Result<BlockId, RuntimeError> {
-    let join_id = unroll_ctx.to_unroll;
-    let join = &ssa_ctx[unroll_ctx.to_unroll];
-
-    let r = join.right.unwrap();
-
-    let join_instructions = join.instructions.clone();
-    let join_left = join.left.unwrap();
-    let mut prev = *join.predecessor.first().unwrap();
-
-    let mut from = prev;
-    assert!(join.is_join());
-    let body_id = join.right.unwrap();
-    let end = unroll_ctx.to_unroll;
-    if !unroll_ctx.unroll_into.is_dummy() {
-        prev = unroll_ctx.unroll_into;
-    }
-    ssa_ctx.current_block = prev;
-    let new_body = block::new_sealed_block(ssa_ctx, block::BlockType::Normal, true);
-    let prev_block = ssa_ctx.try_get_block_mut(prev).unwrap();
-    prev_block.dominated = vec![new_body];
-    unroll_ctx.unroll_into = new_body;
-
-    while {
-        //evaluate the join  block:
-        evaluate_phi(&join_instructions, from, &mut unroll_ctx.eval_map, ssa_ctx)?;
-        evaluate_conditional_jump(
-            *join_instructions.last().unwrap(),
-            &unroll_ctx.eval_map,
-            ssa_ctx,
-        )?
-    } {
-        unroll_ctx.to_unroll = body_id;
-        from = unroll_until(ssa_ctx, unroll_ctx, end)?;
-    }
-    assert!(ssa_ctx.current_block == unroll_ctx.unroll_into);
-    let next_block = block::new_sealed_block(ssa_ctx, block::BlockType::Normal, true);
-    unroll_ctx.deprecate(join_id);
-    unroll_ctx.deprecate(r);
-
-    unroll_ctx.unroll_into = next_block;
-    unroll_ctx.to_unroll = join_left;
-    Ok(join_left)
-}
-
-#[derive(Debug)]
-pub(super) struct UnrollContext {
-    pub(super) deprecated: Vec<BlockId>,
-    pub(super) to_unroll: BlockId,
-    pub(super) unroll_into: BlockId,
-    pub(super) eval_map: HashMap<NodeId, NodeEval>,
-}
-
-impl UnrollContext {
-    pub(super) fn deprecate(&mut self, block_id: BlockId) {
-        if !self.deprecated.contains(&block_id) {
-            self.deprecated.push(block_id);
-        }
-    }
-}
-
-//evaluate phi instruction, coming from 'from' block; retrieve the argument corresponding to the block, evaluates it and update the evaluation map
-fn evaluate_phi(
-    instructions: &[NodeId],
-    from: BlockId,
-    to: &mut HashMap<NodeId, NodeEval>,
-    ctx: &mut SsaContext,
-) -> Result<(), RuntimeError> {
-    let mut to_process = Vec::new();
-    for i in instructions {
-        if let Some(ins) = ctx.try_get_instruction(*i) {
-            if let Operation::Phi { block_args, .. } = &ins.operation {
-                for (arg, block) in block_args {
-                    if *block == from {
-                        //we evaluate the phi instruction value
-                        let arg = *arg;
-                        let id = ins.id;
-                        to_process
-                            .push((id, evaluate_one(NodeEval::VarOrInstruction(arg), to, ctx)?));
-                    }
-                }
-            } else if ins.operation != node::Operation::Nop {
-                break; //phi instructions are placed at the beginning (and after the first dummy instruction)
-            }
-        }
-    }
-    //Update the evaluation map.
-    for obj in to_process {
-        to.insert(obj.0, NodeEval::VarOrInstruction(obj.1.to_index(ctx)));
-    }
-    Ok(())
-}
-
-//returns true if we should jump
-fn evaluate_conditional_jump(
-    jump: NodeId,
-    value_array: &HashMap<NodeId, NodeEval>,
-    ctx: &mut SsaContext,
-) -> Result<bool, RuntimeError> {
-    let jump_ins = ctx.try_get_instruction(jump).unwrap();
-
-    let (cond_id, should_jump): (_, fn(FieldElement) -> bool) = match jump_ins.operation {
-        Operation::Jeq(cond_id, _) => (cond_id, |field| !field.is_zero()),
-        Operation::Jne(cond_id, _) => (cond_id, |field| field.is_zero()),
-        Operation::Jmp(_) => return Ok(true),
-        _ => panic!("loop without conditional statement!"),
-    };
-
-    let cond = get_current_value(cond_id, value_array);
-    let cond = match evaluate_object(cond, value_array, ctx)?.into_const_value() {
-        Some(c) => c,
-        None => unreachable!(
-            "Conditional jump argument is non-const: {:?}",
-            evaluate_object(cond, value_array, ctx)
-        ),
-    };
-
-    Ok(should_jump(cond))
-}
-
-//Retrieve the NodeEval value of the index in the evaluation map
-fn get_current_value(id: NodeId, value_array: &HashMap<NodeId, NodeEval>) -> NodeEval {
-    *value_array.get(&id).unwrap_or(&NodeEval::VarOrInstruction(id))
-}
-
-//Same as get_current_value but for a NodeEval object instead of a NodeObject
-fn get_current_value_for_node_eval(
-    obj: NodeEval,
-    value_array: &HashMap<NodeId, NodeEval>,
-) -> NodeEval {
-    match obj {
-        NodeEval::VarOrInstruction(obj_id) => get_current_value(obj_id, value_array),
-        NodeEval::Const(..) | NodeEval::Function(..) => obj,
-    }
-}
-
-//evaluate the object without recursion, doing only one step of evaluation
-fn evaluate_one(
-    obj: NodeEval,
-    value_array: &HashMap<NodeId, NodeEval>,
-    ctx: &SsaContext,
-) -> Result<NodeEval, RuntimeError> {
-    let mut modified = false;
-    match get_current_value_for_node_eval(obj, value_array) {
-        NodeEval::Const(..) | NodeEval::Function(..) => Ok(obj),
-        NodeEval::VarOrInstruction(obj_id) => {
-            if ctx.try_get_node(obj_id).is_none() {
-                return Ok(obj);
-            }
-
-            match &ctx[obj_id] {
-                NodeObject::Instr(i) => {
-                    let new_id = optimizations::propagate(ctx, obj_id, &mut modified);
-                    if new_id != obj_id {
-                        return evaluate_one(NodeEval::VarOrInstruction(new_id), value_array, ctx);
-                    }
-                    if let Operation::Phi { .. } = i.operation {
-                        //n.b phi are handled before, else we should know which block we come from
-                        return Ok(NodeEval::VarOrInstruction(i.id));
-                    }
-
-                    let result =
-                        i.evaluate_with(ctx, |_, id| Ok(get_current_value(id, value_array)))?;
-
-                    if let NodeEval::VarOrInstruction(idx) = result {
-                        if ctx.try_get_node(idx).is_none() {
-                            return Ok(NodeEval::VarOrInstruction(obj_id));
-                        }
-                    }
-                    Ok(result)
-                }
-                NodeObject::Const(c) => {
-                    let value = FieldElement::from_be_bytes_reduce(&c.value.to_bytes_be());
-                    Ok(NodeEval::Const(value, c.get_type()))
-                }
-                NodeObject::Variable(_) => Ok(NodeEval::VarOrInstruction(obj_id)),
-                NodeObject::Function(f, id, _) => Ok(NodeEval::Function(*f, *id)),
-            }
-        }
-    }
-}
-
-//Evaluate an object recursively
-fn evaluate_object(
-    obj: NodeEval,
-    value_array: &HashMap<NodeId, NodeEval>,
-    ctx: &SsaContext,
-) -> Result<NodeEval, RuntimeError> {
-    match get_current_value_for_node_eval(obj, value_array) {
-        NodeEval::Const(_, _) | NodeEval::Function(..) => Ok(obj),
-        NodeEval::VarOrInstruction(obj_id) => {
-            if ctx.try_get_node(obj_id).is_none() {
-                return Ok(obj);
-            }
-
-            match &ctx[obj_id] {
-                NodeObject::Instr(i) => {
-                    if let Operation::Phi { .. } = i.operation {
-                        return Ok(NodeEval::VarOrInstruction(i.id));
-                    }
-
-                    //n.b phi are handled before, else we should know which block we come from
-                    let result = i.evaluate_with(ctx, |ctx, id| {
-                        evaluate_object(get_current_value(id, value_array), value_array, ctx)
-                    })?;
-
-                    if let NodeEval::VarOrInstruction(idx) = result {
-                        if ctx.try_get_node(idx).is_none() {
-                            return Ok(NodeEval::VarOrInstruction(obj_id));
-                        }
-                    }
-                    Ok(result)
-                }
-                NodeObject::Const(c) => {
-                    let value = FieldElement::from_be_bytes_reduce(&c.value.to_bytes_be());
-                    Ok(NodeEval::Const(value, c.get_type()))
-                }
-                NodeObject::Variable(_) => Ok(NodeEval::VarOrInstruction(obj_id)),
-                NodeObject::Function(f, id, _) => Ok(NodeEval::Function(*f, *id)),
-            }
-        }
-    }
-}
diff --git a/crates/noirc_evaluator/src/ssa/function.rs b/crates/noirc_evaluator/src/ssa/function.rs
deleted file mode 100644
index 33957998e7c..00000000000
--- a/crates/noirc_evaluator/src/ssa/function.rs
+++ /dev/null
@@ -1,415 +0,0 @@
-use crate::errors::RuntimeError;
-use crate::ssa::{
-    block::BlockId,
-    conditional::{AssumptionId, DecisionTree, TreeBuilder},
-    context::SsaContext,
-    mem::ArrayId,
-    node::{Node, NodeId, ObjectType, Opcode, Operation},
-    ssa_gen::IrGenerator,
-    {block, builtin, node, ssa_form},
-};
-use iter_extended::try_vecmap;
-use noirc_frontend::monomorphization::ast::{Call, Definition, FuncId, LocalId, Type};
-use std::collections::{HashMap, VecDeque};
-
-#[derive(Clone, Debug, PartialEq, Eq, Copy)]
-pub(crate) struct FuncIndex(pub(crate) usize);
-
-impl FuncIndex {
-    pub(crate) fn new(idx: usize) -> FuncIndex {
-        FuncIndex(idx)
-    }
-}
-
-#[derive(Clone, Debug)]
-pub(crate) struct SsaFunction {
-    pub(crate) entry_block: BlockId,
-    pub(crate) id: FuncId,
-    pub(crate) idx: FuncIndex,
-    pub(crate) node_id: NodeId,
-
-    //signature:
-    pub(crate) name: String,
-    pub(crate) arguments: Vec<(NodeId, bool)>,
-    pub(crate) result_types: Vec<ObjectType>,
-    pub(crate) decision: DecisionTree,
-}
-
-impl SsaFunction {
-    pub(crate) fn new(
-        id: FuncId,
-        name: &str,
-        block_id: BlockId,
-        idx: FuncIndex,
-        ctx: &mut SsaContext,
-    ) -> SsaFunction {
-        SsaFunction {
-            entry_block: block_id,
-            id,
-            node_id: ctx.push_function_id(id, name),
-            name: name.to_string(),
-            arguments: Vec::new(),
-            result_types: Vec::new(),
-            decision: DecisionTree::new(ctx),
-            idx,
-        }
-    }
-
-    pub(crate) fn compile(&self, ir_gen: &mut IrGenerator) -> Result<DecisionTree, RuntimeError> {
-        let function_cfg = block::bfs(self.entry_block, None, &ir_gen.context);
-        block::compute_sub_dom(&mut ir_gen.context, &function_cfg);
-        //Optimization
-        //catch the error because the function may not be called
-        super::optimizations::full_cse(&mut ir_gen.context, self.entry_block, false)?;
-        //Unrolling
-        super::flatten::unroll_tree(&mut ir_gen.context, self.entry_block)?;
-
-        //reduce conditionals
-        let mut decision = DecisionTree::new(&ir_gen.context);
-        let mut builder = TreeBuilder::new(self.entry_block);
-        for (arg, _) in &self.arguments {
-            if let ObjectType::ArrayPointer(a) = ir_gen.context.object_type(*arg) {
-                builder.stack.created_arrays.insert(a, self.entry_block);
-            }
-        }
-
-        let mut to_remove: VecDeque<BlockId> = VecDeque::new();
-
-        let result = decision.make_decision_tree(&mut ir_gen.context, builder);
-        if result.is_err() {
-            // we take the last block to ensure we have the return instruction
-            let exit = block::exit(&ir_gen.context, self.entry_block);
-            //short-circuit for function: false constraint and return 0
-            let instructions = &ir_gen.context[exit].instructions.clone();
-            let stack = block::short_circuit_instructions(
-                &mut ir_gen.context,
-                self.entry_block,
-                instructions,
-            );
-            if self.entry_block != exit {
-                for i in &stack {
-                    ir_gen.context.instruction_mut(*i).parent_block = self.entry_block;
-                }
-            }
-
-            let function_block = &mut ir_gen.context[self.entry_block];
-            function_block.instructions.clear();
-            function_block.instructions = stack;
-            function_block.left = None;
-            to_remove.extend(function_cfg.iter()); //let's remove all the other blocks
-        } else {
-            decision.reduce(&mut ir_gen.context, decision.root)?;
-        }
-
-        //merge blocks
-        to_remove =
-            block::merge_path(&mut ir_gen.context, self.entry_block, BlockId::dummy(), None)?;
-
-        ir_gen.context[self.entry_block].dominated.retain(|b| !to_remove.contains(b));
-        for i in to_remove {
-            if i != self.entry_block {
-                ir_gen.context.remove_block(i);
-            }
-        }
-        Ok(decision)
-    }
-
-    pub(crate) fn get_mapped_value(
-        var: Option<&NodeId>,
-        ctx: &mut SsaContext,
-        inline_map: &HashMap<NodeId, NodeId>,
-        block_id: BlockId,
-    ) -> NodeId {
-        let dummy = NodeId::dummy();
-        let node_id = var.unwrap_or(&dummy);
-        if node_id == &dummy {
-            return dummy;
-        }
-
-        let node_obj_opt = ctx.try_get_node(*node_id);
-        if let Some(node::NodeObject::Const(c)) = node_obj_opt {
-            ctx.get_or_create_const(c.get_value_field(), c.value_type)
-        } else if let Some(id) = inline_map.get(node_id) {
-            *id
-        } else {
-            ssa_form::get_current_value_in_block(ctx, *node_id, block_id)
-        }
-    }
-}
-
-impl IrGenerator {
-    /// Creates an ssa function and returns its type upon success
-    pub(crate) fn create_function(
-        &mut self,
-        func_id: FuncId,
-        index: FuncIndex,
-    ) -> Result<ObjectType, RuntimeError> {
-        let current_block = self.context.current_block;
-        let current_function = self.function_context;
-        let func_block = block::BasicBlock::create_cfg(&mut self.context);
-
-        let function = &mut self.program[func_id];
-        let mut func =
-            SsaFunction::new(func_id, &function.name, func_block, index, &mut self.context);
-
-        //arguments:
-        for (param_id, mutable, name, typ) in std::mem::take(&mut function.parameters) {
-            let node_ids = self.create_function_parameter(param_id, &typ, &name);
-            func.arguments.extend(node_ids.into_iter().map(|id| (id, mutable)));
-        }
-
-        // ensure return types are defined in case of recursion call cycle
-        let function = &mut self.program[func_id];
-        let return_types = function.return_type.flatten();
-        for typ in return_types {
-            func.result_types.push(match typ {
-                Type::Unit => ObjectType::NotAnObject,
-                Type::Array(_, _) => ObjectType::ArrayPointer(crate::ssa::mem::ArrayId::dummy()),
-                _ => self.context.convert_type(&typ),
-            });
-        }
-
-        self.function_context = Some(index);
-        self.context.functions.insert(func_id, func.clone());
-
-        let function_body = self.program.take_function_body(func_id);
-        let last_value = self.ssa_gen_expression(&function_body)?;
-        let return_values = last_value.to_node_ids();
-
-        func.result_types.clear();
-        let return_values = try_vecmap(return_values, |mut return_id| {
-            let node_opt = self.context.try_get_node(return_id);
-            let typ = node_opt.map_or(ObjectType::NotAnObject, |node| node.get_type());
-
-            if let Some(ins) = self.context.try_get_instruction(return_id) {
-                if ins.operation.opcode() == Opcode::Results {
-                    // n.b. this required for result instructions, but won't hurt if done for all i
-                    let new_var = node::Variable {
-                        id: NodeId::dummy(),
-                        obj_type: typ,
-                        name: format!("return_{}", return_id.0.into_raw_parts().0),
-                        root: None,
-                        def: None,
-                        witness: None,
-                        parent_block: self.context.current_block,
-                    };
-                    let b_id = self.context.add_variable(new_var, None);
-                    let b_id1 = self.context.handle_assign(b_id, None, return_id, None)?;
-                    return_id = ssa_form::get_current_value(&mut self.context, b_id1);
-                }
-            }
-            func.result_types.push(typ);
-            Ok::<NodeId, RuntimeError>(return_id)
-        })?;
-
-        self.context.new_instruction(
-            node::Operation::Return(return_values),
-            node::ObjectType::NotAnObject,
-        )?;
-        let decision = func.compile(self)?; //unroll the function
-        func.decision = decision;
-        self.context.functions.insert(func_id, func);
-        self.context.current_block = current_block;
-        self.function_context = current_function;
-
-        Ok(ObjectType::Function)
-    }
-
-    fn create_function_parameter(&mut self, id: LocalId, typ: &Type, name: &str) -> Vec<NodeId> {
-        //check if the variable is already created:
-        let def = Definition::Local(id);
-        let val = match self.find_variable(&def) {
-            Some(var) => self.get_current_value(&var.clone()),
-            None => self.create_new_value(typ, name, Some(def)),
-        };
-        val.to_node_ids()
-    }
-
-    //generates an instruction for calling the function
-    pub(super) fn call(&mut self, call: &Call) -> Result<Vec<NodeId>, RuntimeError> {
-        let func = self.ssa_gen_expression(&call.func)?.unwrap_id();
-        let arguments = self.ssa_gen_expression_list(&call.arguments);
-
-        if let Some(opcode) = self.context.get_builtin_opcode(func, &call.arguments) {
-            return self.call_low_level(opcode, arguments);
-        }
-
-        let predicate = AssumptionId::dummy();
-        let location = call.location;
-
-        let mut call_op = Operation::Call {
-            func,
-            arguments: arguments.clone(),
-            returned_arrays: vec![],
-            predicate,
-            location,
-        };
-
-        let call_instruction =
-            self.context.new_instruction(call_op.clone(), ObjectType::NotAnObject)?;
-
-        if let Some(id) = self.context.try_get_func_id(func) {
-            let callee = self.context.ssa_func(id).unwrap().idx;
-            if let Some(caller) = self.function_context {
-                update_call_graph(&mut self.context.call_graph, caller, callee);
-            }
-        }
-
-        // Temporary: this block is needed to fix a bug in 7_function
-        // where `foo` is incorrectly inferred to take an array of size 1 and
-        // return an array of size 0.
-        // we should check issue #628 again when this block is removed
-        // we should also see if the lca check in StackFrame.is_new_array() can be removed (cf. issue #661)
-        if let Some(func_id) = self.context.try_get_func_id(func) {
-            let rtt = self.context.functions[&func_id].result_types.clone();
-            let mut result = Vec::new();
-            for i in rtt.iter().enumerate() {
-                result.push(self.context.new_instruction(
-                    node::Operation::Result { call_instruction, index: i.0 as u32 },
-                    *i.1,
-                )?);
-            }
-            let ssa_func = self.context.ssa_func(func_id).unwrap();
-            let func_arguments = ssa_func.arguments.clone();
-            for (caller_arg, func_arg) in arguments.iter().zip(func_arguments) {
-                let mut is_array_result = false;
-                if let Some(node::Instruction {
-                    operation: node::Operation::Result { .. }, ..
-                }) = self.context.try_get_instruction(*caller_arg)
-                {
-                    is_array_result =
-                        super::mem::Memory::deref(&self.context, func_arg.0).is_some();
-                }
-                if is_array_result {
-                    self.context.handle_assign(func_arg.0, None, *caller_arg, None)?;
-                }
-            }
-
-            // If we have the function directly the ArrayIds in the Result types are correct
-            // and we don't need to set returned_arrays yet as they can be set later.
-            return Ok(result);
-        }
-
-        let returned_arrays = match &mut call_op {
-            Operation::Call { returned_arrays, .. } => returned_arrays,
-            _ => unreachable!(),
-        };
-
-        let result_ids = self.create_call_results(call, call_instruction, returned_arrays);
-
-        // Fixup the returned_arrays, they will be incorrectly tracked for higher order functions
-        // otherwise.
-        self.context.instruction_mut(call_instruction).operation = call_op;
-        result_ids
-    }
-
-    fn create_call_results(
-        &mut self,
-        call: &Call,
-        call_instruction: NodeId,
-        returned_arrays: &mut Vec<(ArrayId, u32)>,
-    ) -> Result<Vec<NodeId>, RuntimeError> {
-        let return_types = call.return_type.flatten().into_iter().enumerate();
-
-        try_vecmap(return_types, |(i, typ)| {
-            let result = Operation::Result { call_instruction, index: i as u32 };
-            let typ = match typ {
-                Type::Array(len, elem_type) => {
-                    let elem_type = self.context.convert_type(&elem_type);
-                    let array_id = self.context.new_array("", elem_type, len as u32, None).1;
-                    returned_arrays.push((array_id, i as u32));
-                    ObjectType::ArrayPointer(array_id)
-                }
-                other => self.context.convert_type(&other),
-            };
-
-            self.context.new_instruction(result, typ)
-        })
-    }
-
-    //Low-level functions with no more than 2 arguments
-    fn call_low_level(
-        &mut self,
-        op: builtin::Opcode,
-        args: Vec<NodeId>,
-    ) -> Result<Vec<NodeId>, RuntimeError> {
-        let (len, elem_type) = op.get_result_type(&args, &self.context);
-
-        let result_type = if len > 1 {
-            //We create an array that will contain the result and set the res_type to point to that array
-            let result_index = self.new_array(&format!("{op}_result"), elem_type, len, None).1;
-            node::ObjectType::ArrayPointer(result_index)
-        } else {
-            elem_type
-        };
-        //when the function returns an array, we use ins.res_type(array)
-        //else we map ins.id to the returned witness
-        let id = self.context.new_instruction(node::Operation::Intrinsic(op, args), result_type)?;
-        Ok(vec![id])
-    }
-}
-
-fn resize_graph(call_graph: &mut Vec<Vec<u8>>, size: usize) {
-    while call_graph.len() < size {
-        call_graph.push(vec![0; size]);
-    }
-
-    for i in call_graph.iter_mut() {
-        while i.len() < size {
-            i.push(0);
-        }
-    }
-}
-
-fn update_call_graph(call_graph: &mut Vec<Vec<u8>>, caller: FuncIndex, callee: FuncIndex) {
-    let a = caller.0;
-    let b = callee.0;
-    let max = a.max(b) + 1;
-    resize_graph(call_graph, max);
-
-    call_graph[a][b] = 1;
-}
-
-fn is_leaf(call_graph: &[Vec<u8>], i: FuncIndex) -> bool {
-    for j in 0..call_graph[i.0].len() {
-        if call_graph[i.0][j] == 1 {
-            return false;
-        }
-    }
-    true
-}
-
-fn get_new_leaf(ctx: &SsaContext, processed: &[FuncIndex]) -> (FuncIndex, FuncId) {
-    for f in ctx.functions.values() {
-        if !processed.contains(&(f.idx)) && is_leaf(&ctx.call_graph, f.idx) {
-            return (f.idx, f.id);
-        }
-    }
-    unimplemented!("Recursive function call is not supported");
-}
-
-//inline all functions of the call graph such that every inlining operates with a fully flattened function
-pub(super) fn inline_all(ctx: &mut SsaContext) -> Result<(), RuntimeError> {
-    resize_graph(&mut ctx.call_graph, ctx.functions.len());
-    let l = ctx.call_graph.len();
-    let mut processed = Vec::new();
-    while processed.len() < l {
-        let i = get_new_leaf(ctx, &processed);
-        if !processed.is_empty() {
-            super::optimizations::full_cse(ctx, ctx.functions[&i.1].entry_block, false)?;
-        }
-        let mut to_inline = Vec::new();
-        for f in ctx.functions.values() {
-            if ctx.call_graph[f.idx.0][i.0 .0] == 1 {
-                to_inline.push((f.id, f.idx));
-            }
-        }
-        for (func_id, func_idx) in to_inline {
-            super::inline::inline_cfg(ctx, func_id, Some(i.1))?;
-            ctx.call_graph[func_idx.0][i.0 .0] = 0;
-        }
-        processed.push(i.0);
-    }
-    ctx.call_graph.clear();
-    Ok(())
-}
diff --git a/crates/noirc_evaluator/src/ssa/inline.rs b/crates/noirc_evaluator/src/ssa/inline.rs
deleted file mode 100644
index 2cab6018f58..00000000000
--- a/crates/noirc_evaluator/src/ssa/inline.rs
+++ /dev/null
@@ -1,470 +0,0 @@
-use crate::errors::RuntimeError;
-use crate::ssa::{
-    block::BlockId,
-    conditional::DecisionTree,
-    context::SsaContext,
-    mem::{ArrayId, Memory},
-    node::{Instruction, Mark, Node, NodeId, ObjectType, Operation},
-    {block, function, node, optimizations},
-};
-use noirc_frontend::monomorphization::ast::FuncId;
-use std::collections::{hash_map::Entry, HashMap};
-
-// Number of allowed times for inlining function calls inside a code block.
-// If a function calls another function, the inlining of the first function will leave the second function call that needs to be inlined as well.
-// In case of recursive calls, this iterative inlining does not end so we arbitrarily limit it. 100 nested calls should already support very complex programs.
-const MAX_INLINE_TRIES: u32 = 100;
-
-//inline main
-pub(super) fn inline_tree(
-    ctx: &mut SsaContext,
-    block_id: BlockId,
-    decision: &DecisionTree,
-) -> Result<(), RuntimeError> {
-    //inline all function calls
-    let mut retry = MAX_INLINE_TRIES;
-    while retry > 0 && !inline_block(ctx, block_id, None, decision)? {
-        retry -= 1;
-    }
-    assert!(retry > 0, "Error - too many nested calls");
-    for b in ctx[block_id].dominated.clone() {
-        inline_tree(ctx, b, decision)?;
-    }
-    Ok(())
-}
-
-pub(super) fn inline_cfg(
-    ctx: &mut SsaContext,
-    func_id: FuncId,
-    to_inline: Option<FuncId>,
-) -> Result<bool, RuntimeError> {
-    let mut result = true;
-    let func = ctx.ssa_func(func_id).unwrap();
-    let func_cfg = block::bfs(func.entry_block, None, ctx);
-    let decision = func.decision.clone();
-    for block_id in func_cfg {
-        if !inline_block(ctx, block_id, to_inline, &decision)? {
-            result = false;
-        }
-    }
-    Ok(result)
-}
-
-//Return false if some inlined function performs a function call
-fn inline_block(
-    ctx: &mut SsaContext,
-    block_id: BlockId,
-    to_inline: Option<FuncId>,
-    decision: &DecisionTree,
-) -> Result<bool, RuntimeError> {
-    let mut call_ins = vec![];
-    for i in &ctx[block_id].instructions {
-        if let Some(ins) = ctx.try_get_instruction(*i) {
-            if !ins.is_deleted() {
-                if let Operation::Call { func, arguments, returned_arrays, .. } = &ins.operation {
-                    if to_inline.is_none() || to_inline == ctx.try_get_func_id(*func) {
-                        call_ins.push((
-                            ins.id,
-                            *func,
-                            arguments.clone(),
-                            returned_arrays.clone(),
-                            block_id,
-                        ));
-                    }
-                }
-            }
-        }
-    }
-    let mut result = true;
-    for (ins_id, f, args, arrays, parent_block) in call_ins {
-        if let Some(func_id) = ctx.try_get_func_id(f) {
-            let f_copy = ctx.ssa_func(func_id).unwrap().clone();
-            if !inline(ctx, &f_copy, &args, &arrays, parent_block, ins_id, decision)? {
-                result = false;
-            }
-        }
-    }
-
-    if to_inline.is_none() {
-        optimizations::simple_cse(ctx, block_id)?;
-    }
-    Ok(result)
-}
-
-pub(crate) struct StackFrame {
-    pub(crate) stack: Vec<NodeId>,
-    pub(crate) block: BlockId,
-    array_map: HashMap<ArrayId, ArrayId>,
-    pub(crate) created_arrays: HashMap<ArrayId, BlockId>,
-    zeros: HashMap<ObjectType, NodeId>,
-    pub(crate) return_arrays: Vec<ArrayId>,
-    lca_cache: HashMap<(BlockId, BlockId), BlockId>,
-}
-
-impl StackFrame {
-    pub(crate) fn new(block: BlockId) -> StackFrame {
-        StackFrame {
-            stack: Vec::new(),
-            block,
-            array_map: HashMap::new(),
-            created_arrays: HashMap::new(),
-            zeros: HashMap::new(),
-            return_arrays: Vec::new(),
-            lca_cache: HashMap::new(),
-        }
-    }
-
-    pub(crate) fn push(&mut self, ins_id: NodeId) {
-        self.stack.push(ins_id);
-    }
-
-    pub(crate) fn get_or_default(&self, array_idx: ArrayId) -> ArrayId {
-        if let Some(&b) = self.try_get(array_idx) {
-            b
-        } else {
-            array_idx
-        }
-    }
-
-    pub(crate) fn try_get(&self, array_idx: ArrayId) -> Option<&ArrayId> {
-        self.array_map.get(&array_idx)
-    }
-
-    // add instructions to target_block, after/before the provided instruction
-    pub(crate) fn apply(
-        &mut self,
-        ctx: &mut SsaContext,
-        block: BlockId,
-        ins_id: NodeId,
-        after: bool,
-    ) {
-        let mut pos = ctx[block].instructions.iter().position(|x| *x == ins_id).unwrap();
-        if after {
-            pos += 1;
-        }
-        let after = ctx[block].instructions.split_off(pos);
-        ctx[block].instructions.extend_from_slice(&self.stack);
-        ctx[block].instructions.extend_from_slice(&after);
-        self.stack.clear();
-    }
-
-    pub(crate) fn set_zero(&mut self, ctx: &mut SsaContext, o_type: ObjectType) {
-        self.zeros.entry(o_type).or_insert_with(|| ctx.zero_with_type(o_type));
-    }
-    pub(crate) fn get_zero(&self, o_type: ObjectType) -> NodeId {
-        self.zeros[&o_type]
-    }
-
-    // returns the lca of x and y, using a cache
-    pub(crate) fn lca(&mut self, ctx: &SsaContext, x: BlockId, y: BlockId) -> BlockId {
-        let ordered_blocks = if x.0 < y.0 { (x, y) } else { (y, x) };
-        *self.lca_cache.entry(ordered_blocks).or_insert_with(|| block::lca(ctx, x, y))
-    }
-
-    // returns true if the array_id is created in the block of the stack
-    pub(crate) fn is_new_array(&mut self, ctx: &SsaContext, array_id: &ArrayId) -> bool {
-        if self.return_arrays.contains(array_id) {
-            //array is defined by the caller
-            return false;
-        }
-        if self.created_arrays[array_id] != self.block {
-            let lca = self.lca(ctx, self.block, self.created_arrays[array_id]);
-            if lca != self.block && lca != self.created_arrays[array_id] {
-                //if the array is defined in a parallel branch, it is new in this branch
-                return true;
-            }
-            false
-        } else {
-            true
-        }
-    }
-
-    //assigns the arrays to the block where they are seen for the first time
-    pub(crate) fn new_array(&mut self, array_id: ArrayId) {
-        if let std::collections::hash_map::Entry::Vacant(e) = self.created_arrays.entry(array_id) {
-            e.insert(self.block);
-        }
-    }
-}
-
-//inline a function call
-//Return false if the inlined function performs a function call
-fn inline(
-    ctx: &mut SsaContext,
-    ssa_func: &function::SsaFunction,
-    args: &[NodeId],
-    arrays: &[(ArrayId, u32)],
-    block: BlockId,
-    call_id: NodeId,
-    decision: &DecisionTree,
-) -> Result<bool, RuntimeError> {
-    let func_arg = ssa_func.arguments.clone();
-
-    //map nodes from the function cfg to the caller cfg
-    let mut inline_map = HashMap::<NodeId, NodeId>::new();
-    let mut stack_frame = StackFrame::new(block);
-
-    //1. return arrays
-    for arg_caller in arrays.iter() {
-        if let node::ObjectType::ArrayPointer(a) = ssa_func.result_types[arg_caller.1 as usize] {
-            stack_frame.array_map.insert(a, arg_caller.0);
-            stack_frame.return_arrays.push(arg_caller.0);
-        }
-    }
-
-    //2. by copy parameters:
-    for (&arg_caller, &arg_function) in args.iter().zip(&func_arg) {
-        //pass by-ref const array arguments
-        if let node::ObjectType::ArrayPointer(x) = ctx.object_type(arg_function.0) {
-            if let node::ObjectType::ArrayPointer(y) = ctx.object_type(arg_caller) {
-                if !arg_function.1 && !stack_frame.array_map.contains_key(&x) {
-                    stack_frame.array_map.insert(x, y);
-                    continue;
-                }
-            }
-        }
-        ctx.handle_assign_inline(arg_function.0, arg_caller, &mut stack_frame, block);
-    }
-
-    let mut result = true;
-    //3. inline in the block: we assume the function cfg is already flattened.
-    let mut next_block = Some(ssa_func.entry_block);
-    while let Some(next_b) = next_block {
-        let mut nested_call = false;
-        next_block = inline_in_block(
-            next_b,
-            &mut inline_map,
-            &mut stack_frame,
-            call_id,
-            &mut nested_call,
-            ctx,
-            decision,
-        )?;
-        if result && nested_call {
-            result = false;
-        }
-    }
-    Ok(result)
-}
-
-//inline the given block of the function body into the target_block
-fn inline_in_block(
-    block_id: BlockId,
-    inline_map: &mut HashMap<NodeId, NodeId>,
-    stack_frame: &mut StackFrame,
-    call_id: NodeId,
-    nested_call: &mut bool,
-    ctx: &mut SsaContext,
-    decision: &DecisionTree,
-) -> Result<Option<BlockId>, RuntimeError> {
-    let block_func = &ctx[block_id];
-    let next_block = block_func.left;
-    let block_func_instructions = &block_func.instructions.clone();
-    let predicate = if let Operation::Call { predicate, .. } = &ctx.instruction(call_id).operation {
-        *predicate
-    } else {
-        unreachable!("invalid call id");
-    };
-    let mut short_circuit = false;
-
-    *nested_call = false;
-    for &i_id in block_func_instructions {
-        if let Some(ins) = ctx.try_get_instruction(i_id) {
-            if ins.is_deleted() {
-                continue;
-            }
-            let mut array_id = None;
-            let mut clone = ins.clone();
-
-            if let node::ObjectType::ArrayPointer(id) = ins.res_type {
-                //We collect data here for potential mapping using the array_map below.
-                array_id = Some(id);
-            }
-
-            clone.operation.map_values_for_inlining(
-                ctx,
-                inline_map,
-                stack_frame,
-                stack_frame.block,
-            );
-
-            match &clone.operation {
-                Operation::Nop => (),
-                //Return instruction:
-                Operation::Return(values) => {
-                    //we need to find the corresponding result instruction in the target block (using ins.rhs) and replace it by ins.lhs
-                    for (i, value) in values.iter().enumerate() {
-                        if let Some(result) =
-                            ctx.get_result_instruction_mut(stack_frame.block, call_id, i as u32)
-                        {
-                            result.mark = Mark::ReplaceWith(*value);
-                        }
-                    }
-                    let call_ins = ctx.instruction_mut(call_id);
-                    call_ins.mark = Mark::Deleted;
-                }
-                Operation::Call { .. } => {
-                    *nested_call = true;
-                    let new_ins = new_cloned_instruction(clone, stack_frame.block);
-                    push_instruction(ctx, new_ins, stack_frame, inline_map);
-                }
-                Operation::Load { array_id, index, location } => {
-                    //Compute the new address:
-                    let b = stack_frame.get_or_default(*array_id);
-                    let mut new_ins = Instruction::new(
-                        Operation::Load { array_id: b, index: *index, location: *location },
-                        clone.res_type,
-                        Some(stack_frame.block),
-                    );
-                    new_ins.id = clone.id;
-                    push_instruction(ctx, new_ins, stack_frame, inline_map);
-                }
-                Operation::Store { array_id, index, value, predicate, location } => {
-                    let b = stack_frame.get_or_default(*array_id);
-                    let mut new_ins = Instruction::new(
-                        Operation::Store {
-                            array_id: b,
-                            index: *index,
-                            value: *value,
-                            predicate: *predicate,
-                            location: *location,
-                        },
-                        clone.res_type,
-                        Some(stack_frame.block),
-                    );
-                    new_ins.id = clone.id;
-                    push_instruction(ctx, new_ins, stack_frame, inline_map);
-                }
-                Operation::Phi { .. } => {
-                    unreachable!("Phi instructions should have been simplified");
-                }
-                _ => {
-                    let mut new_ins = new_cloned_instruction(clone, stack_frame.block);
-                    if let Some(id) = array_id {
-                        let new_id = stack_frame.get_or_default(id);
-                        new_ins.res_type = node::ObjectType::ArrayPointer(new_id);
-                    }
-
-                    let err = optimizations::simplify(ctx, &mut new_ins);
-                    if err.is_err() {
-                        //add predicate if under condition, else short-circuit the target block.
-                        let ass_value = decision.get_assumption_value(predicate);
-                        if ass_value.map_or(false, |value| ctx.under_assumption(value)) {
-                            ctx.add_predicate(ass_value.unwrap(), &mut new_ins, stack_frame);
-                        } else {
-                            short_circuit = true;
-                            break;
-                        }
-                    }
-                    if let Mark::ReplaceWith(replacement) = new_ins.mark {
-                        if let Some(id) = array_id {
-                            if let Entry::Occupied(mut entry) = stack_frame.array_map.entry(id) {
-                                if let node::ObjectType::ArrayPointer(new_id) =
-                                    ctx[replacement].get_type()
-                                {
-                                    //we now map the array to rhs array
-                                    entry.insert(new_id);
-                                }
-                            }
-                        }
-
-                        if replacement != new_ins.id {
-                            inline_map.insert(i_id, replacement);
-                            assert!(stack_frame.stack.contains(&replacement));
-                        }
-                    } else {
-                        push_instruction(ctx, new_ins, stack_frame, inline_map);
-                    }
-                }
-            }
-        }
-    }
-
-    // we apply the `condition` to stack frame and place it into a new stack frame (to avoid ownership issues)
-    let mut stack2 = StackFrame::new(stack_frame.block);
-    stack2.return_arrays = stack_frame.return_arrays.clone();
-    if short_circuit {
-        super::block::short_circuit_inline(ctx, stack_frame.block);
-    } else {
-        decision.apply_condition_to_instructions(
-            ctx,
-            &stack_frame.stack,
-            &mut stack2,
-            predicate,
-        )?;
-        // we add the instructions which we have applied the conditions to, to the target_block, at proper location (really need a linked list!)
-        stack2.apply(ctx, stack_frame.block, call_id, false);
-    }
-
-    stack_frame.stack.clear();
-    Ok(next_block)
-}
-
-fn new_cloned_instruction(original: Instruction, block: BlockId) -> Instruction {
-    let mut clone = Instruction::new(original.operation, original.res_type, Some(block));
-    // Take the original's ID, it will be used to map it as a replacement in push_instruction later
-    clone.id = original.id;
-    clone
-}
-
-fn push_instruction(
-    ctx: &mut SsaContext,
-    instruction: Instruction,
-    stack_frame: &mut StackFrame,
-    inline_map: &mut HashMap<NodeId, NodeId>,
-) {
-    let old_id = instruction.id;
-    let new_id = ctx.add_instruction(instruction);
-    stack_frame.push(new_id);
-    inline_map.insert(old_id, new_id);
-}
-
-impl node::Operation {
-    fn map_values_for_inlining(
-        &mut self,
-        ctx: &mut SsaContext,
-        inline_map: &HashMap<NodeId, NodeId>,
-        stack_frame: &StackFrame,
-        block_id: BlockId,
-    ) {
-        match self {
-            //default way to handle arrays during inlining; we map arrays using the stack_frame
-            Operation::Binary(_) | Operation::Constrain(..) | Operation::Intrinsic(_,_)
-            => {
-                self.map_id_mut(|id| {
-                    if let Some(a) = Memory::deref(ctx, id) {
-                        let b = stack_frame.get_or_default(a);
-                        if b != a {
-                            let new_var = node::Variable {
-                                id: NodeId::dummy(),
-                                obj_type: node::ObjectType::ArrayPointer(b),
-                                name: String::new(),
-                                root: None,
-                                def: None,
-                                witness: None,
-                                parent_block: block_id,
-                            };
-                            return ctx.add_variable(new_var, None);
-                        } else {
-                            return id;
-                        }
-                    }
-                    function::SsaFunction::get_mapped_value(Some(&id), ctx, inline_map, block_id)
-                });
-            }
-            //However we deliberately not use the default case to force review of the behavior if a new type of operation is added.
-            //These types do not handle arrays:
-            Operation::Cast(_) | Operation::Truncate { .. } | Operation::Not(_) | Operation::Nop
-            | Operation::Jne(_,_) | Operation::Jeq(_,_) | Operation::Jmp(_) |  Operation::Phi { .. } | Operation::Cond { .. }
-            //These types handle arrays via their return type (done in inline_in_block)
-            |  Operation::Result { .. }
-            //These types handle arrays in a specific way (done in inline_in_block)
-            | Operation::Return(_) | Operation::Load {.. } | Operation::Store { .. } | Operation::Call { .. }
-            => {
-                self.map_id_mut(|id| {
-                    function::SsaFunction::get_mapped_value(Some(&id), ctx, inline_map, block_id)
-                });
-            }
-        }
-    }
-}
diff --git a/crates/noirc_evaluator/src/ssa/integer.rs b/crates/noirc_evaluator/src/ssa/integer.rs
deleted file mode 100644
index 2bdbf80c9e8..00000000000
--- a/crates/noirc_evaluator/src/ssa/integer.rs
+++ /dev/null
@@ -1,566 +0,0 @@
-use crate::errors::RuntimeError;
-use crate::ssa::{
-    block::BlockId,
-    context::SsaContext,
-    mem::{ArrayId, Memory},
-    node::{BinaryOp, Instruction, Mark, Node, NodeId, NodeObject, ObjectType, Operation},
-    {node, optimizations},
-};
-use acvm::FieldElement;
-use iter_extended::vecmap;
-use num_bigint::BigUint;
-use num_traits::{One, Zero};
-use std::{
-    collections::{BTreeMap, HashMap},
-    ops::Neg,
-};
-
-//Returns the maximum bit size of short integers
-pub(super) fn short_integer_max_bit_size() -> u32 {
-    //TODO: it should be FieldElement::max_num_bits()/2, but for now we do not support more than 128 bits as well
-    //This allows us to do use u128 to represent integer constant values
-    u32::min(FieldElement::max_num_bits() / 2, 128)
-}
-
-//Gets the maximum value of the instruction result
-fn get_instruction_max(
-    ctx: &SsaContext,
-    ins: &Instruction,
-    max_map: &mut HashMap<NodeId, BigUint>,
-    value_map: &HashMap<NodeId, NodeId>,
-) -> BigUint {
-    assert_ne!(
-        ins.operation.opcode(),
-        node::Opcode::Phi,
-        "Phi instructions must have been simplified"
-    );
-    ins.operation.for_each_id(|id| {
-        get_obj_max_value(ctx, id, max_map, value_map);
-    });
-    get_instruction_max_operand(ctx, ins, max_map, value_map)
-}
-
-//Gets the maximum value of the instruction result using the provided operand maximum
-fn get_instruction_max_operand(
-    ctx: &SsaContext,
-    ins: &Instruction,
-    max_map: &mut HashMap<NodeId, BigUint>,
-    value_map: &HashMap<NodeId, NodeId>,
-) -> BigUint {
-    match &ins.operation {
-        Operation::Load { array_id, index, .. } => {
-            get_load_max(ctx, *index, max_map, value_map, *array_id)
-        }
-        Operation::Binary(node::Binary { operator, lhs, rhs, .. }) => {
-            if let BinaryOp::Sub { .. } = operator {
-                //TODO uses interval analysis instead
-                // Note that a boolean is also handled as an unsigned integer
-                if ins.res_type.is_unsigned_integer() {
-                    if let Some(lhs_const) = ctx.get_as_constant(*lhs) {
-                        let lhs_big = BigUint::from_bytes_be(&lhs_const.to_be_bytes());
-                        if max_map[rhs] <= lhs_big {
-                            //TODO unsigned
-                            return lhs_big;
-                        }
-                    }
-                }
-            }
-            get_max_value(ins, max_map)
-        }
-        // Operation::Constrain(_) => {
-        //ConstrainOp::Eq :
-        //TODO... we should update the max_map AFTER the truncate is processed (else it breaks it)
-        // let min = BigUint::min(left_max.clone(), right_max.clone());
-        // max_map.insert(ins.lhs, min.clone());
-        // max_map.insert(ins.rhs, min);
-        _ => get_max_value(ins, max_map),
-    }
-}
-
-// Retrieve max possible value of a node; from the max_map if it was already computed
-// or else we compute it.
-// we use the value array (get_current_value2) in order to handle truncate instructions
-// we need to do it because rust did not allow to modify the instruction in block_overflow..
-fn get_obj_max_value(
-    ctx: &SsaContext,
-    id: NodeId,
-    max_map: &mut HashMap<NodeId, BigUint>,
-    value_map: &HashMap<NodeId, NodeId>,
-) -> BigUint {
-    let id = get_value_from_map(id, value_map);
-    if max_map.contains_key(&id) {
-        return max_map[&id].clone();
-    }
-    if id == NodeId::dummy() {
-        max_map.insert(id, BigUint::zero());
-        return BigUint::zero(); //a non-argument has no max
-    }
-    let obj = &ctx[id];
-
-    let result = match obj {
-        NodeObject::Variable(v) => (BigUint::one() << v.size_in_bits()) - BigUint::one(), //TODO check for signed type
-        NodeObject::Instr(i) => get_instruction_max(ctx, i, max_map, value_map),
-        NodeObject::Const(c) => c.value.clone(), //TODO panic for string constants
-        NodeObject::Function(..) => BigUint::zero(),
-    };
-    max_map.insert(id, result.clone());
-    result
-}
-
-//Creates a truncate instruction for obj_id
-fn truncate(
-    ctx: &mut SsaContext,
-    obj_id: NodeId,
-    bit_size: u32,
-    max_map: &mut HashMap<NodeId, BigUint>,
-) -> Option<NodeId> {
-    // get type
-    let obj = &ctx[obj_id];
-    let obj_type = obj.get_type();
-    let obj_name = format!("{obj}");
-    //ensure truncate is needed:
-    let v_max = &max_map[&obj_id];
-
-    if *v_max >= BigUint::one() << bit_size {
-        //TODO is max_bit_size leaking some info????
-        //Create a new truncate instruction '(idx): obj truncate bit_size'
-        //set current value of obj to idx
-        let max_bit_size = v_max.bits() as u32;
-
-        let mut i = Instruction::new(
-            Operation::Truncate { value: obj_id, bit_size, max_bit_size },
-            obj_type,
-            None,
-        );
-
-        if i.res_name.ends_with("_t") {
-            //TODO we should use %t so that we can check for this substring (% is not a valid char for a variable name) in the name and then write name%t[number+1]
-        }
-        i.res_name = obj_name + "_t";
-        let i_id = ctx.add_instruction(i);
-        max_map.insert(i_id, BigUint::from((1_u128 << bit_size) - 1));
-        Some(i_id)
-        //we now need to call fix_truncate(), it is done in a separate function in order to not overwhelm the arguments list.
-    } else {
-        None
-    }
-}
-
-//Set the id and parent block of the truncate instruction
-//This is needed because the instruction is inserted into a block and not added in the current block like regular instructions
-//We also update the value array
-fn fix_truncate(
-    eval: &mut SsaContext,
-    id: NodeId,
-    prev_id: NodeId,
-    block_idx: BlockId,
-    value_map: &mut HashMap<NodeId, NodeId>,
-) {
-    if let Some(ins) = eval.try_get_mut_instruction(id) {
-        ins.parent_block = block_idx;
-        value_map.insert(prev_id, id);
-    }
-}
-
-//Adds the variable to the list of variables that need to be truncated
-fn add_to_truncate(
-    ctx: &SsaContext,
-    obj_id: NodeId,
-    bit_size: u32,
-    to_truncate: &mut BTreeMap<NodeId, u32>,
-    max_map: &HashMap<NodeId, BigUint>,
-) {
-    let v_max = &max_map[&obj_id];
-    if *v_max >= BigUint::one() << bit_size {
-        if let Some(NodeObject::Const(_)) = &ctx.try_get_node(obj_id) {
-            return; //a constant cannot be truncated, so we exit the function gracefully
-        }
-        let truncate_bits = match to_truncate.get(&obj_id) {
-            Some(value) => u32::min(*value, bit_size),
-            None => bit_size,
-        };
-        to_truncate.insert(obj_id, truncate_bits);
-    }
-}
-
-//Truncate the 'to_truncate' list
-fn process_to_truncate(
-    ctx: &mut SsaContext,
-    new_list: &mut Vec<NodeId>,
-    to_truncate: &mut BTreeMap<NodeId, u32>,
-    max_map: &mut HashMap<NodeId, BigUint>,
-    block_idx: BlockId,
-    value_map: &mut HashMap<NodeId, NodeId>,
-) {
-    for (id, bit_size) in to_truncate.iter() {
-        if let Some(truncate_idx) = truncate(ctx, *id, *bit_size, max_map) {
-            //TODO properly handle signed arithmetic...
-            fix_truncate(ctx, truncate_idx, *id, block_idx, value_map);
-            new_list.push(truncate_idx);
-        }
-    }
-    to_truncate.clear();
-}
-
-//Add required truncate instructions on all blocks
-pub(super) fn overflow_strategy(ctx: &mut SsaContext) -> Result<(), RuntimeError> {
-    let mut max_map: HashMap<NodeId, BigUint> = HashMap::new();
-    let mut memory_map = HashMap::new();
-    tree_overflow(ctx, ctx.first_block, &mut max_map, &mut memory_map)
-}
-
-//implement overflow strategy following the dominator tree
-fn tree_overflow(
-    ctx: &mut SsaContext,
-    b_idx: BlockId,
-    max_map: &mut HashMap<NodeId, BigUint>,
-    memory_map: &mut HashMap<u32, NodeId>,
-) -> Result<(), RuntimeError> {
-    block_overflow(ctx, b_idx, max_map, memory_map)?;
-    for b in ctx[b_idx].dominated.clone() {
-        tree_overflow(ctx, b, &mut max_map.clone(), &mut memory_map.clone())?;
-    }
-    Ok(())
-}
-
-//overflow strategy for one block
-fn block_overflow(
-    ctx: &mut SsaContext,
-    block_id: BlockId,
-    max_map: &mut HashMap<NodeId, BigUint>,
-    memory_map: &mut HashMap<u32, NodeId>,
-) -> Result<(), RuntimeError> {
-    //for each instruction, we compute the resulting max possible value (in term of the field representation of the operation)
-    //when it is over the field characteristic, or if the instruction requires it, then we insert truncate instructions
-    // The instructions are inserted in a duplicate list( because of rust ownership..), which we use for
-    // processing another cse round for the block because the truncates may be duplicated.
-    let mut new_list = Vec::new();
-
-    // This needs to be a BTreeMap and not a HashMap so that it can have a deterministic order
-    // when we collect it into a Vec later on
-    let mut truncate_map = BTreeMap::new();
-
-    let mut modified = false;
-    let instructions =
-        vecmap(&ctx[block_id].instructions, |id| ctx.try_get_instruction(*id).unwrap().clone());
-
-    //since we process the block from the start, the block value map is not relevant
-    let mut value_map = HashMap::new();
-    for mut ins in instructions {
-        if matches!(
-            ins.operation,
-            Operation::Nop | Operation::Call { .. } | Operation::Result { .. }
-        ) {
-            //For now we skip completely functions from overflow; that means arguments are NOT truncated.
-            //The reasoning is that this is handled by doing the overflow strategy after the function has been inlined
-            continue;
-        }
-
-        ins.operation.map_id_mut(|id| {
-            let id = optimizations::propagate(ctx, id, &mut modified);
-            get_value_from_map(id, &value_map)
-        });
-
-        //we propagate optimized loads - todo check if it is needed because there is cse at the end
-        //We retrieve get_current_value() in case a previous truncate has updated the value map
-        let should_truncate_ins = ins.truncate_required(ctx);
-        let ins_max_bits = get_instruction_max(ctx, &ins, max_map, &value_map).bits();
-        let res_type = ins.res_type;
-
-        let too_many_bits =
-            ins_max_bits > FieldElement::max_num_bits() as u64 && !res_type.is_native_field();
-
-        ins.operation.for_each_id(|id| {
-            get_obj_max_value(ctx, id, max_map, &value_map);
-            let arg = ctx.try_get_node(id);
-            let should_truncate_arg =
-                should_truncate_ins && arg.is_some() && !get_type(arg).is_native_field();
-
-            if should_truncate_arg || too_many_bits {
-                add_to_truncate(ctx, id, get_size_in_bits(arg), &mut truncate_map, max_map);
-            }
-        });
-
-        match ins.operation {
-            Operation::Load { array_id, index, .. } => {
-                if let Some(val) = ctx.get_indexed_value(array_id, index) {
-                    //optimize static load
-                    ins.mark = Mark::ReplaceWith(*val);
-                }
-            }
-            Operation::Store { array_id, index, value, predicate, .. } => {
-                if let Some(idx) = Memory::to_u32(ctx, index) {
-                    if ctx.is_one(crate::ssa::conditional::DecisionTree::unwrap_predicate(
-                        ctx, &predicate,
-                    )) {
-                        let absolute_adr = ctx.mem[array_id].absolute_adr(idx);
-                        //optimize static store
-                        memory_map.insert(absolute_adr, value);
-                    }
-                }
-            }
-            Operation::Binary(node::Binary { operator: BinaryOp::Shl, lhs, rhs, .. }) => {
-                if let Some(r_const) = ctx.get_as_constant(rhs) {
-                    let r_type = ctx[rhs].get_type();
-                    let rhs =
-                        ctx.get_or_create_const(FieldElement::from(2_i128).pow(&r_const), r_type);
-                    ins.operation = Operation::Binary(node::Binary {
-                        lhs,
-                        rhs,
-                        operator: BinaryOp::Mul,
-                        predicate: None,
-                    });
-                }
-            }
-            Operation::Binary(node::Binary { operator: BinaryOp::Shr(loc), lhs, rhs, .. }) => {
-                if !ins.res_type.is_unsigned_integer() {
-                    todo!("Right shift is only implemented for unsigned integers");
-                }
-                if let Some(r_const) = ctx.get_as_constant(rhs) {
-                    let r_type = ctx[rhs].get_type();
-                    if r_const.to_u128() > r_type.bits() as u128 {
-                        ins.mark = Mark::ReplaceWith(ctx.zero_with_type(ins.res_type));
-                    } else {
-                        let rhs = ctx
-                            .get_or_create_const(FieldElement::from(2_i128).pow(&r_const), r_type);
-                        ins.operation = Operation::Binary(node::Binary {
-                            lhs,
-                            rhs,
-                            operator: BinaryOp::Udiv(loc),
-                            predicate: None,
-                        });
-                    }
-                }
-            }
-            Operation::Cast(value_id) => {
-                // For now the types we support here are only all integer types (field, signed, unsigned, bool)
-                // so a cast would normally translate to a truncate.
-                // if res_type and lhs have the same bit size (in a large sense, which includes field elements)
-                // then either they have the same type and should have been simplified
-                // or they don't have the same sign so we keep the cast operator
-                // if res_type is smaller than lhs bit size, we look if lhs can hold directly into res_type
-                // if not, we need to truncate lhs to a res_type. We modify directly the cast instruction into a truncate
-                // in other cases we can keep the cast instruction
-                // for instance if res_type is greater than lhs bit size, we need to truncate lhs to its bit size and use the truncate
-                // result in the cast, but this is handled by the truncate_required
-                // after this function, all cast instructions refer to casting lhs into a bigger (or equal) type
-                // any other case has been transformed into the latter using truncates.
-                let obj = ctx.try_get_node(value_id);
-
-                if ins.res_type == get_type(obj) {
-                    ins.mark = Mark::ReplaceWith(value_id);
-                } else {
-                    let max = get_obj_max_value(ctx, value_id, max_map, &value_map);
-                    let max_bits = max.bits() as u32;
-
-                    if ins.res_type.bits() < get_size_in_bits(obj) && max_bits > ins.res_type.bits()
-                    {
-                        //we need to truncate
-                        ins.operation = Operation::Truncate {
-                            value: value_id,
-                            bit_size: ins.res_type.bits(),
-                            max_bit_size: max_bits,
-                        };
-                    }
-                }
-            }
-            _ => (),
-        }
-
-        process_to_truncate(
-            ctx,
-            &mut new_list,
-            &mut truncate_map,
-            max_map,
-            block_id,
-            &mut value_map,
-        );
-
-        let id = match ins.mark {
-            Mark::None => ins.id,
-            Mark::Deleted => continue,
-            Mark::ReplaceWith(new_id) => new_id,
-        };
-
-        new_list.push(id);
-        ins.operation.map_id_mut(|id| get_value_from_map(id, &value_map));
-
-        if let Operation::Binary(node::Binary {
-            rhs,
-            operator: BinaryOp::Sub { max_rhs_value } | BinaryOp::SafeSub { max_rhs_value },
-            ..
-        }) = &mut ins.operation
-        {
-            //for now we pass the max value to the instruction, we could also keep the max_map e.g in the block (or max in each node object)
-            //sub operations require the max value to ensure it does not underflow
-            *max_rhs_value = max_map[rhs].clone();
-            //we may do that in future when the max_map becomes more used elsewhere (for other optimizations)
-        }
-
-        let old_ins = ctx.try_get_mut_instruction(ins.id).unwrap();
-        *old_ins = ins;
-    }
-
-    update_value_array(ctx, block_id, &value_map);
-
-    //We run another round of CSE for the block in order to remove possible duplicated truncates, this will assign 'new_list' to the block instructions
-    let mut modified = false;
-    optimizations::cse_block(ctx, block_id, &mut new_list, &mut modified)?;
-    Ok(())
-}
-
-fn update_value_array(
-    ctx: &mut SsaContext,
-    block_id: BlockId,
-    value_map: &HashMap<NodeId, NodeId>,
-) {
-    let block = &mut ctx[block_id];
-    for (old, new) in value_map {
-        block.value_map.insert(*old, *new); //TODO we must merge rather than update
-    }
-}
-
-//Get current value using the provided value map
-fn get_value_from_map(id: NodeId, value_map: &HashMap<NodeId, NodeId>) -> NodeId {
-    *value_map.get(&id).unwrap_or(&id)
-}
-
-fn get_size_in_bits(obj: Option<&NodeObject>) -> u32 {
-    if let Some(v) = obj {
-        v.size_in_bits()
-    } else {
-        0
-    }
-}
-
-fn get_type(obj: Option<&NodeObject>) -> ObjectType {
-    if let Some(v) = obj {
-        v.get_type()
-    } else {
-        ObjectType::NotAnObject
-    }
-}
-
-fn get_load_max(
-    ctx: &SsaContext,
-    address: NodeId,
-    max_map: &mut HashMap<NodeId, BigUint>,
-    value_map: &HashMap<NodeId, NodeId>,
-    array: ArrayId,
-) -> BigUint {
-    if let Some(&value) = ctx.get_indexed_value(array, address) {
-        return get_obj_max_value(ctx, value, max_map, value_map);
-    };
-    ctx.mem[array].max.clone() //return array max
-}
-
-//Returns the max value of an operation from an upper bound of left and right hand sides
-//Function is used to check for overflows over the field size, this is why we use BigUint.
-fn get_max_value(ins: &Instruction, max_map: &mut HashMap<NodeId, BigUint>) -> BigUint {
-    let max_value = match &ins.operation {
-        Operation::Binary(binary) => get_binary_max_value(binary, ins.res_type, max_map),
-        Operation::Not(_) => ins.res_type.max_size(),
-        Operation::Constrain(..) => BigUint::zero(),
-        //'a cast a' means we cast a into res_type of the instruction
-        Operation::Cast(value_id) => {
-            let type_max = ins.res_type.max_size();
-            BigUint::min(max_map[value_id].clone(), type_max)
-        }
-        Operation::Truncate { value, max_bit_size, .. } => BigUint::min(
-            max_map[value].clone(),
-            BigUint::from(2_u32).pow(*max_bit_size) - BigUint::from(1_u32),
-        ),
-        Operation::Nop | Operation::Jne(..) | Operation::Jeq(..) | Operation::Jmp(_) => {
-            unreachable!()
-        }
-        Operation::Phi { root, block_args } => {
-            let mut max = max_map[root].clone();
-            for (id, _block) in block_args {
-                max = BigUint::max(max, max_map[id].clone());
-            }
-            max
-        }
-        Operation::Cond { condition: _, val_true: lhs, val_false: rhs } => {
-            let lhs_max = &max_map[lhs];
-            let rhs_max = &max_map[rhs];
-            lhs_max.max(rhs_max).clone()
-        }
-        Operation::Load { .. } => unreachable!(),
-        Operation::Store { .. } => BigUint::zero(),
-        Operation::Call { .. } => ins.res_type.max_size(), //n.b. functions should have been inlined
-        Operation::Return(_) => ins.res_type.max_size(),
-        Operation::Result { .. } => {
-            unreachable!("Functions must have been inlined before checking for overflows")
-        }
-        Operation::Intrinsic(opcode, _) => opcode.get_max_value(),
-    };
-
-    if ins.res_type.is_native_field() {
-        let field_max = BigUint::from_bytes_be(&FieldElement::one().neg().to_be_bytes());
-
-        //Native Field operations cannot overflow so they will not be truncated
-        if max_value >= field_max {
-            return field_max;
-        }
-    }
-    max_value
-}
-
-fn get_binary_max_value(
-    binary: &node::Binary,
-    res_type: ObjectType,
-    max_map: &mut HashMap<NodeId, BigUint>,
-) -> BigUint {
-    let lhs_max = &max_map[&binary.lhs];
-    let rhs_max = &max_map[&binary.rhs];
-
-    match &binary.operator {
-        BinaryOp::Add => lhs_max + rhs_max,
-        BinaryOp::SafeAdd => todo!(),
-        BinaryOp::Sub { .. } => {
-            let r_mod = BigUint::one() << res_type.bits();
-            let mut k = rhs_max / &r_mod;
-            if rhs_max % &r_mod != BigUint::zero() {
-                k += BigUint::one();
-            }
-            assert!(&k * &r_mod >= *rhs_max);
-            lhs_max + k * r_mod
-        }
-        BinaryOp::SafeSub { .. } => todo!(),
-        BinaryOp::Mul => lhs_max * rhs_max,
-        BinaryOp::SafeMul => todo!(),
-        BinaryOp::Udiv(_) => lhs_max.clone(),
-        BinaryOp::Sdiv(_) => todo!(),
-        BinaryOp::Urem(_) => rhs_max - BigUint::one(),
-        BinaryOp::Srem(_) => todo!(),
-        BinaryOp::Div(_) => FieldElement::modulus() - BigUint::one(),
-        BinaryOp::Eq => BigUint::one(),
-        BinaryOp::Ne => BigUint::one(),
-        BinaryOp::Ult => BigUint::one(),
-        BinaryOp::Ule => BigUint::one(),
-        BinaryOp::Slt => BigUint::one(),
-        BinaryOp::Sle => BigUint::one(),
-        BinaryOp::Lt => BigUint::one(),
-        BinaryOp::Lte => BigUint::one(),
-        BinaryOp::And => {
-            BigUint::from(2_u32).pow(u64::min(lhs_max.bits(), rhs_max.bits()) as u32)
-                - BigUint::one()
-        }
-        BinaryOp::Or | BinaryOp::Xor => {
-            BigUint::from(2_u32).pow(u64::max(lhs_max.bits(), rhs_max.bits()) as u32)
-                - BigUint::one()
-        }
-        BinaryOp::Assign => rhs_max.clone(),
-        BinaryOp::Shl => BigUint::min(
-            BigUint::from(2_u32).pow((lhs_max.bits() + 1) as u32) - BigUint::one(),
-            res_type.max_size(),
-        ),
-        BinaryOp::Shr(_) => {
-            if lhs_max.bits() >= 1 {
-                BigUint::from(2_u32).pow((lhs_max.bits() - 1) as u32) - BigUint::one()
-            } else {
-                BigUint::zero()
-            }
-        }
-    }
-}
diff --git a/crates/noirc_evaluator/src/ssa/mem.rs b/crates/noirc_evaluator/src/ssa/mem.rs
deleted file mode 100644
index 09fdc33b704..00000000000
--- a/crates/noirc_evaluator/src/ssa/mem.rs
+++ /dev/null
@@ -1,147 +0,0 @@
-use crate::ssa::{
-    context::SsaContext,
-    node,
-    node::{Node, NodeId},
-};
-use acvm::FieldElement;
-use noirc_frontend::monomorphization::ast::{Definition, LocalId};
-use num_bigint::BigUint;
-use num_traits::ToPrimitive;
-use std::collections::HashMap;
-
-#[derive(Default)]
-pub(crate) struct Memory {
-    arrays: Vec<MemArray>,
-    pub(crate) last_adr: u32,                    //last address in 'memory'
-    pub(crate) memory_map: HashMap<u32, NodeId>, //maps memory address to expression
-}
-
-#[derive(Debug, Copy, Clone, PartialEq, Eq, PartialOrd, Ord, Hash)]
-pub(crate) struct ArrayId(u32);
-
-impl ArrayId {
-    pub(crate) fn dummy() -> ArrayId {
-        ArrayId(std::u32::MAX)
-    }
-
-    pub(crate) fn as_u32(&self) -> u32 {
-        self.0
-    }
-}
-
-/// MemArray represents a contiguous array of elements of the same type.
-#[derive(Debug, Clone)]
-pub(crate) struct MemArray {
-    /// The unique identifier of a `MemArray` instance.
-    pub(crate) id: ArrayId,
-    /// The type of each array element. All elements of a `MemArray` are of
-    /// the same type.
-    pub(crate) element_type: node::ObjectType,
-    /// The name of the variable to which the array is assigned.
-    pub(crate) name: String,
-    /// A reference to where the array is defined.
-    pub(crate) def: Definition,
-    /// The number of elements in the array.
-    pub(crate) len: u32,
-    /// The base address of the array.
-    pub(crate) adr: u32,
-    /// The max possible value of each element.
-    pub(crate) max: BigUint,
-}
-
-impl MemArray {
-    fn new(
-        id: ArrayId,
-        definition: Definition,
-        name: &str,
-        of: node::ObjectType,
-        len: u32,
-    ) -> MemArray {
-        assert!(len > 0);
-        MemArray {
-            id,
-            element_type: of,
-            name: name.to_string(),
-            def: definition,
-            len,
-            adr: 0,
-            max: of.max_size(),
-        }
-    }
-
-    pub(super) fn absolute_adr(&self, idx: u32) -> u32 {
-        self.adr + idx
-    }
-}
-
-impl Memory {
-    /// Retrieves the ArrayId of the last array in Memory.
-    /// Panics if self does not contain at least 1 array.
-    pub(super) fn last_id(&self) -> ArrayId {
-        ArrayId(self.arrays.len() as u32 - 1)
-    }
-
-    //dereference a pointer
-    pub(super) fn deref(ctx: &SsaContext, id: NodeId) -> Option<ArrayId> {
-        ctx.try_get_node(id).and_then(|var| match var.get_type() {
-            node::ObjectType::ArrayPointer(a) => Some(a),
-            _ => None,
-        })
-    }
-
-    pub(super) fn create_new_array(
-        &mut self,
-        len: u32,
-        el_type: node::ObjectType,
-        arr_name: &str,
-    ) -> ArrayId {
-        let id = ArrayId(self.arrays.len() as u32);
-        let dummy_id = Definition::Local(LocalId(u32::MAX));
-        let mut new_array = MemArray::new(id, dummy_id, arr_name, el_type, len);
-        new_array.adr = self.last_adr;
-        self.arrays.push(new_array);
-        self.last_adr += len;
-        id
-    }
-    /// Coerces a FieldElement into a u32
-    /// By taking its value modulo 2^32
-    ///
-    /// See issue #785 on whether this is safe
-    pub(super) fn as_u32(value: FieldElement) -> u32 {
-        let big_v = BigUint::from_bytes_be(&value.to_be_bytes());
-        let mut modulus = BigUint::from(2_u32);
-        modulus = modulus.pow(32);
-        let result = big_v % modulus;
-        result.to_u32().unwrap()
-    }
-
-    pub(super) fn to_u32(ctx: &SsaContext, id: NodeId) -> Option<u32> {
-        if let Some(index_as_constant) = ctx.get_as_constant(id) {
-            if let Ok(address) = index_as_constant.to_u128().try_into() {
-                return Some(address);
-            }
-            //Invalid memory address
-        }
-        None //Not a constant object
-    }
-
-    //returns the value of the element array[index], if it exists in the memory_map
-    pub(super) fn get_value_from_map(&self, array_id: ArrayId, index: u32) -> Option<&NodeId> {
-        let adr = self[array_id].absolute_adr(index);
-        self.memory_map.get(&adr)
-    }
-}
-
-impl std::ops::Index<ArrayId> for Memory {
-    type Output = MemArray;
-
-    fn index(&self, index: ArrayId) -> &Self::Output {
-        &self.arrays[index.0 as usize]
-    }
-}
-
-impl std::ops::IndexMut<ArrayId> for Memory {
-    fn index_mut(&mut self, index: ArrayId) -> &mut Self::Output {
-        &mut self.arrays[index.0 as usize]
-    }
-}
diff --git a/crates/noirc_evaluator/src/ssa/mod.rs b/crates/noirc_evaluator/src/ssa/mod.rs
deleted file mode 100644
index a605bf73740..00000000000
--- a/crates/noirc_evaluator/src/ssa/mod.rs
+++ /dev/null
@@ -1,16 +0,0 @@
-pub(crate) mod acir_gen;
-mod anchor;
-mod block;
-mod builtin;
-mod conditional;
-mod context;
-mod flatten;
-mod function;
-mod inline;
-mod integer;
-mod mem;
-pub(crate) mod node;
-mod optimizations;
-mod ssa_form;
-pub(crate) mod ssa_gen;
-mod value;
diff --git a/crates/noirc_evaluator/src/ssa/node.rs b/crates/noirc_evaluator/src/ssa/node.rs
deleted file mode 100644
index b964743b370..00000000000
--- a/crates/noirc_evaluator/src/ssa/node.rs
+++ /dev/null
@@ -1,1404 +0,0 @@
-use crate::errors::{RuntimeError, RuntimeErrorKind};
-use crate::ssa::{block::BlockId, builtin, conditional, context::SsaContext, mem::ArrayId};
-use acvm::{acir::native_types::Witness, FieldElement};
-use iter_extended::vecmap;
-use noirc_errors::Location;
-use noirc_frontend::{
-    monomorphization::ast::{Definition, FuncId},
-    BinaryOpKind,
-};
-use num_bigint::BigUint;
-use num_traits::{FromPrimitive, One};
-use std::ops::{Add, BitAnd, BitOr, BitXor, Mul, Shl, Shr, Sub};
-
-pub(super) trait Node: std::fmt::Display {
-    fn get_type(&self) -> ObjectType;
-    fn id(&self) -> NodeId;
-    fn size_in_bits(&self) -> u32;
-}
-
-impl std::fmt::Display for Variable {
-    fn fmt(&self, f: &mut std::fmt::Formatter) -> std::fmt::Result {
-        write!(f, "{}", self.name)
-    }
-}
-
-impl std::fmt::Display for NodeObject {
-    fn fmt(&self, f: &mut std::fmt::Formatter) -> std::fmt::Result {
-        use FunctionKind::*;
-        match self {
-            NodeObject::Variable(o) => write!(f, "{o}"),
-            NodeObject::Instr(i) => write!(f, "{i}"),
-            NodeObject::Const(c) => write!(f, "{c}"),
-            NodeObject::Function(Normal(id), ..) => write!(f, "f{}", id.0),
-            NodeObject::Function(Builtin(opcode), ..) => write!(f, "{opcode}"),
-        }
-    }
-}
-
-impl std::fmt::Display for Constant {
-    fn fmt(&self, f: &mut std::fmt::Formatter) -> std::fmt::Result {
-        write!(f, "{}", self.value)
-    }
-}
-
-impl Node for Variable {
-    fn get_type(&self) -> ObjectType {
-        self.obj_type
-    }
-
-    fn size_in_bits(&self) -> u32 {
-        self.get_type().bits()
-    }
-
-    fn id(&self) -> NodeId {
-        self.id
-    }
-}
-
-impl Node for NodeObject {
-    fn get_type(&self) -> ObjectType {
-        match self {
-            NodeObject::Variable(o) => o.get_type(),
-            NodeObject::Instr(i) => i.res_type,
-            NodeObject::Const(o) => o.value_type,
-            NodeObject::Function(..) => ObjectType::Function,
-        }
-    }
-
-    fn size_in_bits(&self) -> u32 {
-        match self {
-            NodeObject::Variable(o) => o.size_in_bits(),
-            NodeObject::Instr(i) => i.res_type.bits(),
-            NodeObject::Const(c) => c.size_in_bits(),
-            NodeObject::Function(..) => 0,
-        }
-    }
-
-    fn id(&self) -> NodeId {
-        match self {
-            NodeObject::Variable(o) => o.id(),
-            NodeObject::Instr(i) => i.id,
-            NodeObject::Const(c) => c.id(),
-            NodeObject::Function(_, id, _) => *id,
-        }
-    }
-}
-
-impl Node for Constant {
-    fn get_type(&self) -> ObjectType {
-        self.value_type
-    }
-
-    fn size_in_bits(&self) -> u32 {
-        self.value.bits().try_into().unwrap()
-    }
-
-    fn id(&self) -> NodeId {
-        self.id
-    }
-}
-
-#[derive(Debug, Clone, Copy, PartialEq, Eq, PartialOrd, Ord, Hash)]
-pub(crate) struct NodeId(pub(crate) arena::Index);
-
-impl NodeId {
-    pub(crate) fn dummy() -> NodeId {
-        NodeId(SsaContext::dummy_id())
-    }
-    pub(crate) fn is_dummy(&self) -> bool {
-        self.0 == SsaContext::dummy_id()
-    }
-}
-
-#[derive(Debug)]
-pub(crate) enum NodeObject {
-    Variable(Variable),
-    Instr(Instruction),
-    Const(Constant),
-    Function(FunctionKind, NodeId, /*name:*/ String),
-}
-
-#[derive(Debug, Copy, Clone)]
-pub(crate) enum FunctionKind {
-    Normal(FuncId),
-    Builtin(builtin::Opcode),
-}
-
-#[derive(Debug)]
-pub(crate) struct Constant {
-    pub(crate) id: NodeId,
-    pub(crate) value: BigUint, //TODO use FieldElement instead
-    #[allow(dead_code)]
-    pub(crate) value_str: String, //TODO ConstStr subtype
-    pub(crate) value_type: ObjectType,
-}
-
-impl Constant {
-    pub(super) fn get_value_field(&self) -> FieldElement {
-        FieldElement::from_be_bytes_reduce(&self.value.to_bytes_be())
-    }
-}
-
-#[derive(Debug)]
-pub(crate) struct Variable {
-    pub(crate) id: NodeId,
-    pub(crate) obj_type: ObjectType,
-    pub(crate) name: String,
-    pub(crate) root: Option<NodeId>, //when generating SSA, assignment of an object creates a new one which is linked to the original one
-    pub(crate) def: Option<Definition>, //AST definition of the variable
-    pub(crate) witness: Option<Witness>,
-    #[allow(dead_code)]
-    pub(crate) parent_block: BlockId,
-}
-
-impl Variable {
-    pub(crate) fn root(&self) -> NodeId {
-        self.root.unwrap_or(self.id)
-    }
-
-    pub(crate) fn new(
-        obj_type: ObjectType,
-        name: String,
-        def: Option<Definition>,
-        parent_block: BlockId,
-    ) -> Variable {
-        Variable {
-            id: NodeId::dummy(),
-            obj_type,
-            name,
-            root: None,
-            def,
-            witness: None,
-            parent_block,
-        }
-    }
-}
-
-#[derive(Copy, Clone, Debug, PartialEq, Eq, Hash)]
-pub(crate) enum ObjectType {
-    Numeric(NumericType),
-    ArrayPointer(ArrayId),
-    Function,
-    NotAnObject, //not an object
-}
-
-#[derive(Copy, Clone, Debug, PartialEq, Eq, Hash)]
-pub(crate) enum NumericType {
-    Signed(u32),   // bit size
-    Unsigned(u32), // bit size
-    NativeField,
-}
-
-impl From<ObjectType> for NumericType {
-    fn from(object_type: ObjectType) -> NumericType {
-        match object_type {
-            ObjectType::Numeric(numeric_type) => numeric_type,
-            _ => unreachable!("failed to convert an object type into a numeric type"),
-        }
-    }
-}
-
-impl ObjectType {
-    pub(crate) fn bits(&self) -> u32 {
-        match self {
-            ObjectType::NotAnObject => 0,
-            ObjectType::ArrayPointer(_) => 0,
-            ObjectType::Function => 0,
-            ObjectType::Numeric(numeric_type) => match numeric_type {
-                NumericType::Signed(c) | NumericType::Unsigned(c) => *c,
-                NumericType::NativeField => FieldElement::max_num_bits(),
-            },
-        }
-    }
-
-    /// Returns the type that represents
-    /// a field element.
-    /// The most basic/fundamental type in the language
-    pub(crate) fn native_field() -> ObjectType {
-        ObjectType::Numeric(NumericType::NativeField)
-    }
-    /// Returns a type that represents an unsigned integer
-    pub(crate) fn unsigned_integer(bit_size: u32) -> ObjectType {
-        ObjectType::Numeric(NumericType::Unsigned(bit_size))
-    }
-    /// Returns a type that represents an boolean
-    /// Booleans are just seen as an unsigned integer
-    /// with a bit size of 1.
-    pub(crate) fn boolean() -> ObjectType {
-        ObjectType::unsigned_integer(1)
-    }
-    /// Returns a type that represents an signed integer
-    pub(crate) fn signed_integer(bit_size: u32) -> ObjectType {
-        ObjectType::Numeric(NumericType::Signed(bit_size))
-    }
-
-    /// Returns true, if the `ObjectType`
-    /// represents a field element
-    pub(crate) fn is_native_field(&self) -> bool {
-        matches!(self, ObjectType::Numeric(NumericType::NativeField))
-    }
-    /// Returns true, if the `ObjectType`
-    /// represents an unsigned integer
-    pub(crate) fn is_unsigned_integer(&self) -> bool {
-        matches!(self, ObjectType::Numeric(NumericType::Unsigned(_)))
-    }
-
-    //maximum size of the representation (e.g. signed(8).max_size() return 255, not 128.)
-    pub(crate) fn max_size(&self) -> BigUint {
-        match self {
-            ObjectType::Numeric(NumericType::NativeField) => {
-                BigUint::from_bytes_be(&FieldElement::from(-1_i128).to_be_bytes())
-            }
-            _ => (BigUint::one() << self.bits()) - BigUint::one(),
-        }
-    }
-
-    // TODO: the name of this function is misleading
-    // TODO since the type is not being returned
-    pub(crate) fn field_to_type(&self, f: FieldElement) -> FieldElement {
-        match self {
-            // TODO: document why this is unreachable
-            ObjectType::NotAnObject | ObjectType::ArrayPointer(_) => {
-                unreachable!()
-            }
-            ObjectType::Numeric(NumericType::NativeField) => f,
-            // TODO: document why this is a TODO and create an issue
-            ObjectType::Numeric(NumericType::Signed(_)) => todo!(),
-            ObjectType::Function | ObjectType::Numeric(NumericType::Unsigned(_)) => {
-                // TODO: document where this 128 comes from
-                assert!(self.bits() < 128);
-                FieldElement::from(f.to_u128() % (1_u128 << self.bits()))
-            }
-        }
-    }
-}
-
-#[derive(Clone, Debug)]
-pub(crate) struct Instruction {
-    pub(crate) id: NodeId,
-    pub(crate) operation: Operation,
-    pub(crate) res_type: ObjectType, //result type
-    pub(crate) parent_block: BlockId,
-    pub(crate) res_name: String,
-    pub(crate) mark: Mark,
-}
-
-#[derive(Copy, Clone, Debug, PartialEq, Eq)]
-pub(crate) enum Mark {
-    None,
-    Deleted,
-    ReplaceWith(NodeId),
-}
-
-impl std::fmt::Display for Instruction {
-    fn fmt(&self, f: &mut std::fmt::Formatter) -> std::fmt::Result {
-        if self.res_name.is_empty() {
-            write!(f, "({:?})", self.id.0.into_raw_parts().0)
-        } else {
-            write!(f, "{}", self.res_name.clone())
-        }
-    }
-}
-
-#[derive(Debug, Copy, Clone)]
-pub(super) enum NodeEval {
-    Const(FieldElement, ObjectType),
-    VarOrInstruction(NodeId),
-    Function(FunctionKind, NodeId),
-}
-
-impl NodeEval {
-    pub(super) fn into_const_value(self) -> Option<FieldElement> {
-        match self {
-            NodeEval::Const(c, _) => Some(c),
-            _ => None,
-        }
-    }
-
-    pub(super) fn into_node_id(self) -> Option<NodeId> {
-        match self {
-            NodeEval::VarOrInstruction(i) => Some(i),
-            NodeEval::Const(_, _) => None,
-            NodeEval::Function(_, id) => Some(id),
-        }
-    }
-
-    //returns the NodeObject index of a NodeEval object
-    //if NodeEval is a constant, it may creates a new NodeObject corresponding to the constant value
-    pub(super) fn to_index(self, ctx: &mut SsaContext) -> NodeId {
-        match self {
-            NodeEval::Const(c, t) => ctx.get_or_create_const(c, t),
-            NodeEval::VarOrInstruction(i) => i,
-            NodeEval::Function(_, id) => id,
-        }
-    }
-
-    pub(super) fn from_id(ctx: &SsaContext, id: NodeId) -> NodeEval {
-        match &ctx[id] {
-            NodeObject::Const(c) => {
-                let value = FieldElement::from_be_bytes_reduce(&c.value.to_bytes_be());
-                NodeEval::Const(value, c.get_type())
-            }
-            NodeObject::Function(f, id, _name) => NodeEval::Function(*f, *id),
-            NodeObject::Variable(_) | NodeObject::Instr(_) => NodeEval::VarOrInstruction(id),
-        }
-    }
-
-    fn from_u128(value: u128, typ: ObjectType) -> NodeEval {
-        NodeEval::Const(value.into(), typ)
-    }
-}
-
-impl Instruction {
-    pub(super) fn new(
-        op_code: Operation,
-        r_type: ObjectType,
-        parent_block: Option<BlockId>,
-    ) -> Instruction {
-        let id = NodeId::dummy();
-        let p_block = parent_block.unwrap_or_else(BlockId::dummy);
-
-        Instruction {
-            id,
-            operation: op_code,
-            res_type: r_type,
-            res_name: String::new(),
-            parent_block: p_block,
-            mark: Mark::None,
-        }
-    }
-
-    /// Indicates whether the left and/or right operand of the instruction is required to be truncated to its bit-width
-    pub(super) fn truncate_required(&self, ctx: &SsaContext) -> bool {
-        match &self.operation {
-            Operation::Binary(binary) => binary.truncate_required(),
-            Operation::Not(..) => true,
-            Operation::Constrain(..) => true,
-            Operation::Cast(value_id) => {
-                let obj = ctx.try_get_node(*value_id);
-                let bits = obj.map_or(0, |obj| obj.size_in_bits());
-                self.res_type.bits() > bits
-            }
-            Operation::Truncate { .. } | Operation::Phi { .. } => false,
-            Operation::Nop
-            | Operation::Jne(..)
-            | Operation::Jeq(..)
-            | Operation::Jmp(..)
-            | Operation::Cond { .. } => false,
-            Operation::Load { .. } => false,
-            Operation::Store { .. } => true,
-            Operation::Intrinsic(_, _) => true,
-            Operation::Call { .. } => true, //return values are in the return statement
-            Operation::Return(_) => true,
-            Operation::Result { .. } => false,
-        }
-    }
-
-    pub(super) fn evaluate(&self, ctx: &SsaContext) -> Result<NodeEval, RuntimeError> {
-        self.evaluate_with(ctx, |ctx, id| Ok(NodeEval::from_id(ctx, id)))
-    }
-
-    //Evaluate the instruction value when its operands are constant (constant folding)
-    pub(super) fn evaluate_with<F>(
-        &self,
-        ctx: &SsaContext,
-        mut eval_fn: F,
-    ) -> Result<NodeEval, RuntimeError>
-    where
-        F: FnMut(&SsaContext, NodeId) -> Result<NodeEval, RuntimeError>,
-    {
-        match &self.operation {
-            Operation::Binary(binary) => {
-                return binary.evaluate(ctx, self.id, self.res_type, eval_fn)
-            }
-            Operation::Cast(value) => {
-                if let Some(l_const) = eval_fn(ctx, *value)?.into_const_value() {
-                    if self.res_type.is_native_field() {
-                        return Ok(NodeEval::Const(l_const, self.res_type));
-                    } else if let Some(l_const) = l_const.try_into_u128() {
-                        return Ok(NodeEval::Const(
-                            FieldElement::from(l_const % (1_u128 << self.res_type.bits())),
-                            self.res_type,
-                        ));
-                    }
-                }
-            }
-            Operation::Not(value) => {
-                if let Some(l_const) = eval_fn(ctx, *value)?.into_const_value() {
-                    let l = self.res_type.field_to_type(l_const).to_u128();
-                    let max = (1_u128 << self.res_type.bits()) - 1;
-                    return Ok(NodeEval::Const(FieldElement::from((!l) & max), self.res_type));
-                }
-            }
-            Operation::Constrain(value, location) => {
-                if let Some(obj) = eval_fn(ctx, *value)?.into_const_value() {
-                    if obj.is_one() {
-                        // Delete the constrain, it is always true
-                        return Ok(NodeEval::VarOrInstruction(NodeId::dummy()));
-                    } else if obj.is_zero() {
-                        if let Some(location) = *location {
-                            return Err(RuntimeError::new(
-                                RuntimeErrorKind::UnstructuredError {
-                                    message: "Constraint is always false".into(),
-                                },
-                                Some(location),
-                            ));
-                        } else {
-                            return Err(RuntimeErrorKind::Spanless(
-                                "Constraint is always false".into(),
-                            )
-                            .into());
-                        }
-                    }
-                }
-            }
-            Operation::Cond { condition, val_true, val_false } => {
-                if let Some(cond) = eval_fn(ctx, *condition)?.into_const_value() {
-                    if cond.is_zero() {
-                        return Ok(NodeEval::VarOrInstruction(*val_false));
-                    } else {
-                        return Ok(NodeEval::VarOrInstruction(*val_true));
-                    }
-                }
-                if *val_true == *val_false {
-                    return Ok(NodeEval::VarOrInstruction(*val_false));
-                }
-            }
-            Operation::Phi { .. } => (), //Phi are simplified by simply_phi() later on; they must not be simplified here
-            _ => (),
-        }
-        Ok(NodeEval::VarOrInstruction(self.id))
-    }
-
-    // Simplifies trivial Phi instructions by returning:
-    // None, if the instruction is unreachable or in the root block and can be safely deleted
-    // Some(id), if the instruction can be replaced by the node id
-    // Some(ins_id), if the instruction is not trivial
-    pub(super) fn simplify_phi(
-        ins_id: NodeId,
-        phi_arguments: &[(NodeId, BlockId)],
-    ) -> Option<NodeId> {
-        let mut same = None;
-        for op in phi_arguments {
-            if Some(op.0) == same || op.0 == ins_id {
-                continue;
-            }
-            if same.is_some() {
-                //no simplification
-                return Some(ins_id);
-            }
-
-            same = Some(op.0);
-        }
-        //if same.is_none()  => unreachable phi or in root block, can be replaced by ins.lhs (i.e the root) then.
-        same
-    }
-
-    pub(super) fn is_deleted(&self) -> bool {
-        !matches!(self.mark, Mark::None)
-    }
-
-    pub(super) fn standard_form(&mut self) {
-        if let Operation::Binary(binary) = &mut self.operation {
-            if binary.operator.is_commutative() && binary.rhs < binary.lhs {
-                std::mem::swap(&mut binary.rhs, &mut binary.lhs);
-            }
-        }
-    }
-
-    pub(crate) fn get_location(&self) -> Option<Location> {
-        match &self.operation {
-            Operation::Binary(bin) => match bin.operator {
-                BinaryOp::Udiv(location)
-                | BinaryOp::Sdiv(location)
-                | BinaryOp::Urem(location)
-                | BinaryOp::Srem(location)
-                | BinaryOp::Div(location)
-                | BinaryOp::Shr(location) => Some(location),
-                _ => None,
-            },
-            Operation::Call { location, .. } => Some(*location),
-            Operation::Load { location, .. }
-            | Operation::Store { location, .. }
-            | Operation::Constrain(_, location) => *location,
-            Operation::Cast(_)
-            | Operation::Truncate { .. }
-            | Operation::Not(_)
-            | Operation::Jne(_, _)
-            | Operation::Jeq(_, _)
-            | Operation::Jmp(_)
-            | Operation::Phi { .. }
-            | Operation::Return(_)
-            | Operation::Result { .. }
-            | Operation::Cond { .. }
-            | Operation::Intrinsic(_, _)
-            | Operation::Nop => None,
-        }
-    }
-}
-
-//adapted from LLVM IR
-#[allow(dead_code)] //Some enums are not used yet, allow dead_code should be removed once they are all implemented.
-#[derive(Debug, PartialEq, Eq, Hash, Clone)]
-pub(crate) enum Operation {
-    Binary(Binary),
-    Cast(NodeId), //convert type
-    Truncate {
-        value: NodeId,
-        bit_size: u32,
-        max_bit_size: u32,
-    }, //truncate
-
-    Not(NodeId), //(!) Bitwise Not
-    Constrain(NodeId, Option<Location>),
-
-    //control flow
-    Jne(NodeId, BlockId), //jump on not equal
-    Jeq(NodeId, BlockId), //jump on equal
-    Jmp(BlockId),         //unconditional jump
-    Phi {
-        root: NodeId,
-        block_args: Vec<(NodeId, BlockId)>,
-    },
-    Call {
-        func: NodeId,
-        arguments: Vec<NodeId>,
-        returned_arrays: Vec<(super::mem::ArrayId, u32)>,
-        predicate: conditional::AssumptionId,
-        location: Location,
-    },
-    Return(Vec<NodeId>), //Return value(s) from a function block
-    Result {
-        call_instruction: NodeId,
-        index: u32,
-    }, //Get result index n from a function call
-    Cond {
-        condition: NodeId,
-        val_true: NodeId,
-        val_false: NodeId,
-    },
-
-    Load {
-        array_id: ArrayId,
-        index: NodeId,
-        location: Option<Location>,
-    },
-    Store {
-        array_id: ArrayId,
-        index: NodeId,
-        value: NodeId,
-        predicate: Option<NodeId>,
-        location: Option<Location>,
-    },
-
-    Intrinsic(builtin::Opcode, Vec<NodeId>), //Custom implementation of useful primitives which are more performant with Aztec backend
-
-    Nop, // no op
-}
-
-#[derive(Copy, Clone, Hash, PartialEq, Eq, Debug)]
-pub(super) enum Opcode {
-    Add,
-    SafeAdd,
-    Sub,
-    SafeSub,
-    Mul,
-    SafeMul,
-    Udiv,
-    Sdiv,
-    Urem,
-    Srem,
-    Div,
-    Eq,
-    Ne,
-    Ult,
-    Ule,
-    Slt,
-    Sle,
-    Lt,
-    Lte,
-    And,
-    Or,
-    Xor,
-    Shl,
-    Shr,
-    Assign,
-    Cond,
-    Constrain,
-    Cast,     //convert type
-    Truncate, //truncate
-    Not,      //(!) Bitwise Not
-
-    //control flow
-    Jne, //jump on not equal
-    Jeq, //jump on equal
-    Jmp, //unconditional jump
-    Phi,
-
-    Call(NodeId), //Call a function
-    Return,       //Return value(s) from a function block
-    Results,      //Get result(s) from a function call
-
-    //memory
-    Load(ArrayId),
-    Store(ArrayId),
-    Intrinsic(builtin::Opcode), //Custom implementation of useful primitives
-    Nop,                        // no op
-}
-
-#[derive(Debug, PartialEq, Eq, Hash, Clone)]
-pub(crate) struct Binary {
-    pub(crate) lhs: NodeId,
-    pub(crate) rhs: NodeId,
-    pub(crate) operator: BinaryOp,
-    pub(crate) predicate: Option<NodeId>,
-}
-
-#[derive(Debug, PartialEq, Eq, Hash, Clone)]
-pub(crate) enum BinaryOp {
-    Add, //(+)
-    #[allow(dead_code)]
-    SafeAdd, //(+) safe addition
-    Sub {
-        max_rhs_value: BigUint,
-    }, //(-)
-    #[allow(dead_code)]
-    SafeSub {
-        max_rhs_value: BigUint,
-    }, //(-) safe subtraction
-    Mul, //(*)
-    #[allow(dead_code)]
-    SafeMul, //(*) safe multiplication
-    Udiv(Location), //(/) unsigned division
-    Sdiv(Location), //(/) signed division
-    Urem(Location), //(%) modulo; remainder of unsigned division
-    Srem(Location), //(%) remainder of signed division
-    Div(Location), //(/) field division
-    Eq,  //(==) equal
-    Ne,  //(!=) not equal
-    Ult, //(<) unsigned less than
-    Ule, //(<=) unsigned less or equal
-    Slt, //(<) signed less than
-    Sle, //(<=) signed less or equal
-    Lt,  //(<) field less
-    Lte, //(<=) field less or equal
-    And, //(&) Bitwise And
-    Or,  //(|) Bitwise Or
-    Xor, //(^) Bitwise Xor
-    Shl, //(<<) Shift left
-    Shr(Location), //(>>) Shift right
-
-    Assign,
-}
-
-impl std::fmt::Display for BinaryOp {
-    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
-        let op = match &self {
-            BinaryOp::Add => "add",
-            BinaryOp::SafeAdd => "safe_add",
-            BinaryOp::Sub { .. } => "sub",
-            BinaryOp::SafeSub { .. } => "safe_sub",
-            BinaryOp::Mul => "mul",
-            BinaryOp::SafeMul => "safe_mul",
-            BinaryOp::Udiv(_) => "udiv",
-            BinaryOp::Sdiv(_) => "sdiv",
-            BinaryOp::Urem(_) => "urem",
-            BinaryOp::Srem(_) => "srem",
-            BinaryOp::Div(_) => "div",
-            BinaryOp::Eq => "eq",
-            BinaryOp::Ne => "ne",
-            BinaryOp::Ult => "ult",
-            BinaryOp::Ule => "ule",
-            BinaryOp::Slt => "slt",
-            BinaryOp::Sle => "sle",
-            BinaryOp::Lt => "lt",
-            BinaryOp::Lte => "lte",
-            BinaryOp::And => "and",
-            BinaryOp::Or => "or",
-            BinaryOp::Xor => "xor",
-            BinaryOp::Assign => "assign",
-            BinaryOp::Shl => "shl",
-            BinaryOp::Shr(_) => "shr",
-        };
-        write!(f, "{op}")
-    }
-}
-
-impl Binary {
-    fn new(operator: BinaryOp, lhs: NodeId, rhs: NodeId) -> Binary {
-        Binary { operator, lhs, rhs, predicate: None }
-    }
-
-    pub(super) fn from_ast(
-        op_kind: BinaryOpKind,
-        op_type: ObjectType,
-        lhs: NodeId,
-        rhs: NodeId,
-        location: Location,
-    ) -> Binary {
-        let operator = match op_kind {
-            BinaryOpKind::Add => BinaryOp::Add,
-            BinaryOpKind::Subtract => BinaryOp::Sub { max_rhs_value: BigUint::from_u8(0).unwrap() },
-            BinaryOpKind::Multiply => BinaryOp::Mul,
-            BinaryOpKind::Equal => BinaryOp::Eq,
-            BinaryOpKind::NotEqual => BinaryOp::Ne,
-            BinaryOpKind::And => BinaryOp::And,
-            BinaryOpKind::Or => BinaryOp::Or,
-            BinaryOpKind::Xor => BinaryOp::Xor,
-            BinaryOpKind::Divide => {
-                let num_type: NumericType = op_type.into();
-                match num_type {
-                    NumericType::Signed(_) => BinaryOp::Sdiv(location),
-                    NumericType::Unsigned(_) => BinaryOp::Udiv(location),
-                    NumericType::NativeField => BinaryOp::Div(location),
-                }
-            }
-            BinaryOpKind::Less => {
-                let num_type: NumericType = op_type.into();
-                match num_type {
-                    NumericType::Signed(_) => BinaryOp::Slt,
-                    NumericType::Unsigned(_) => BinaryOp::Ult,
-                    NumericType::NativeField => BinaryOp::Lt,
-                }
-            }
-            BinaryOpKind::LessEqual => {
-                let num_type: NumericType = op_type.into();
-                match num_type {
-                    NumericType::Signed(_) => BinaryOp::Sle,
-                    NumericType::Unsigned(_) => BinaryOp::Ule,
-                    NumericType::NativeField => BinaryOp::Lte,
-                }
-            }
-            BinaryOpKind::Greater => {
-                let num_type: NumericType = op_type.into();
-                match num_type {
-                    NumericType::Signed(_) => return Binary::new(BinaryOp::Slt, rhs, lhs),
-                    NumericType::Unsigned(_) => return Binary::new(BinaryOp::Ult, rhs, lhs),
-                    NumericType::NativeField => return Binary::new(BinaryOp::Lt, rhs, lhs),
-                }
-            }
-            BinaryOpKind::GreaterEqual => {
-                let num_type: NumericType = op_type.into();
-                match num_type {
-                    NumericType::Signed(_) => return Binary::new(BinaryOp::Sle, rhs, lhs),
-                    NumericType::Unsigned(_) => return Binary::new(BinaryOp::Ule, rhs, lhs),
-                    NumericType::NativeField => return Binary::new(BinaryOp::Lte, rhs, lhs),
-                }
-            }
-            BinaryOpKind::ShiftLeft => BinaryOp::Shl,
-            BinaryOpKind::ShiftRight => BinaryOp::Shr(location),
-            BinaryOpKind::Modulo => {
-                let num_type: NumericType = op_type.into();
-                match num_type {
-                    NumericType::Signed(_) => {
-                        return Binary::new(BinaryOp::Srem(location), lhs, rhs)
-                    }
-                    NumericType::Unsigned(_) => {
-                        return Binary::new(BinaryOp::Urem(location), lhs, rhs)
-                    }
-                    NumericType::NativeField => {
-                        unimplemented!("Modulo operation with Field elements is not supported")
-                    }
-                }
-            }
-        };
-
-        Binary::new(operator, lhs, rhs)
-    }
-
-    fn zero_div_error(&self, location: &Location) -> Result<(), RuntimeError> {
-        if self.predicate.is_none() {
-            Err(RuntimeError {
-                location: Some(*location),
-                kind: RuntimeErrorKind::UnstructuredError {
-                    message: "Panic - division by zero".to_string(),
-                },
-            })
-        } else {
-            Ok(())
-        }
-    }
-
-    fn evaluate<F>(
-        &self,
-        ctx: &SsaContext,
-        id: NodeId,
-        res_type: ObjectType,
-        mut eval_fn: F,
-    ) -> Result<NodeEval, RuntimeError>
-    where
-        F: FnMut(&SsaContext, NodeId) -> Result<NodeEval, RuntimeError>,
-    {
-        let l_eval = eval_fn(ctx, self.lhs)?;
-        let r_eval = eval_fn(ctx, self.rhs)?;
-        let l_type = ctx.object_type(self.lhs);
-        let r_type = ctx.object_type(self.rhs);
-
-        let lhs = l_eval.into_const_value();
-        let rhs = r_eval.into_const_value();
-
-        let l_is_zero = lhs.map_or(false, |x| x.is_zero());
-        let r_is_zero = rhs.map_or(false, |x| x.is_zero());
-
-        match &self.operator {
-            BinaryOp::Add | BinaryOp::SafeAdd => {
-                if l_is_zero {
-                    return Ok(r_eval);
-                } else if r_is_zero {
-                    return Ok(l_eval);
-                }
-                assert_eq!(l_type, r_type);
-                if let (Some(lhs), Some(rhs)) = (lhs, rhs) {
-                    return Ok(wrapping(lhs, rhs, l_type, u128::add, Add::add));
-                }
-                //if only one is const, we could try to do constant propagation but this will be handled by the arithmetization step anyways
-                //so it is probably not worth it.
-                //same for x+x vs 2*x
-            }
-            BinaryOp::Sub { .. } | BinaryOp::SafeSub { .. } => {
-                if r_is_zero {
-                    return Ok(l_eval);
-                }
-                if self.lhs == self.rhs {
-                    return Ok(NodeEval::from_u128(0, res_type));
-                }
-                //constant folding
-                if let (Some(lhs), Some(rhs)) = (lhs, rhs) {
-                    return Ok(wrapping(lhs, rhs, res_type, u128::wrapping_sub, Sub::sub));
-                }
-            }
-            BinaryOp::Mul | BinaryOp::SafeMul => {
-                let l_is_one = lhs.map_or(false, |x| x.is_one());
-                let r_is_one = rhs.map_or(false, |x| x.is_one());
-                assert_eq!(l_type, r_type);
-                if l_is_zero || r_is_one {
-                    return Ok(l_eval);
-                } else if r_is_zero || l_is_one {
-                    return Ok(r_eval);
-                } else if let (Some(lhs), Some(rhs)) = (lhs, rhs) {
-                    return Ok(wrapping(lhs, rhs, res_type, u128::mul, Mul::mul));
-                }
-                //if only one is const, we could try to do constant propagation but this will be handled by the arithmetization step anyways
-                //so it is probably not worth it.
-            }
-
-            BinaryOp::Udiv(loc) => {
-                if r_is_zero {
-                    self.zero_div_error(loc)?;
-                } else if l_is_zero {
-                    return Ok(l_eval); //TODO should we ensure rhs != 0 ???
-                }
-                //constant folding
-                else if let (Some(lhs), Some(rhs)) = (lhs, rhs) {
-                    let lhs = res_type.field_to_type(lhs).to_u128();
-                    let rhs = res_type.field_to_type(rhs).to_u128();
-                    return Ok(NodeEval::Const(FieldElement::from(lhs / rhs), res_type));
-                }
-            }
-            BinaryOp::Div(loc) => {
-                if r_is_zero {
-                    self.zero_div_error(loc)?;
-                } else if l_is_zero {
-                    return Ok(l_eval); //TODO should we ensure rhs != 0 ???
-                } else if let (Some(lhs), Some(rhs)) = (lhs, rhs) {
-                    return Ok(NodeEval::Const(lhs / rhs, res_type));
-                }
-            }
-            BinaryOp::Sdiv(loc) => {
-                if r_is_zero {
-                    self.zero_div_error(loc)?;
-                } else if l_is_zero {
-                    return Ok(l_eval); //TODO should we ensure rhs != 0 ???
-                } else if let (Some(lhs), Some(rhs)) = (lhs, rhs) {
-                    let a = field_to_signed(lhs, res_type.bits());
-                    let b = field_to_signed(rhs, res_type.bits());
-                    return Ok(NodeEval::Const(signed_to_field(a / b, res_type.bits())?, res_type));
-                }
-            }
-            BinaryOp::Urem(loc) => {
-                if r_is_zero {
-                    self.zero_div_error(loc)?;
-                } else if l_is_zero {
-                    return Ok(l_eval); //TODO what is the correct result?
-                } else if let (Some(lhs), Some(rhs)) = (lhs, rhs) {
-                    let lhs = res_type.field_to_type(lhs).to_u128();
-                    let rhs = res_type.field_to_type(rhs).to_u128();
-                    let result = lhs - rhs * (lhs / rhs);
-                    return Ok(NodeEval::Const(FieldElement::from(result), res_type));
-                }
-            }
-            BinaryOp::Srem(loc) => {
-                if r_is_zero {
-                    self.zero_div_error(loc)?;
-                } else if l_is_zero {
-                    return Ok(l_eval); //TODO what is the correct result?
-                } else if let (Some(lhs), Some(rhs)) = (lhs, rhs) {
-                    let a = field_to_signed(lhs, res_type.bits());
-                    let b = field_to_signed(rhs, res_type.bits());
-                    return Ok(NodeEval::Const(
-                        signed_to_field(a - b + (a / b), res_type.bits())?,
-                        res_type,
-                    ));
-                }
-            }
-            BinaryOp::Ult => {
-                if r_is_zero {
-                    return Ok(NodeEval::Const(FieldElement::zero(), ObjectType::boolean()));
-                    //n.b we assume the type of lhs and rhs is unsigned because of the opcode, we could also verify this
-                } else if let (Some(lhs), Some(rhs)) = (lhs, rhs) {
-                    assert!(
-                        !res_type.is_native_field(),
-                        "ICE: comparisons are not implemented for field elements"
-                    );
-                    return Ok(NodeEval::Const(
-                        FieldElement::from(lhs < rhs),
-                        ObjectType::boolean(),
-                    ));
-                }
-            }
-            BinaryOp::Ule => {
-                if l_is_zero {
-                    return Ok(NodeEval::Const(FieldElement::one(), ObjectType::boolean()));
-                    //n.b we assume the type of lhs and rhs is unsigned because of the opcode, we could also verify this
-                } else if let (Some(lhs), Some(rhs)) = (lhs, rhs) {
-                    assert!(
-                        !res_type.is_native_field(),
-                        "ICE: comparisons are not implemented for field elements"
-                    );
-                    return Ok(NodeEval::Const(
-                        FieldElement::from(lhs <= rhs),
-                        ObjectType::boolean(),
-                    ));
-                }
-            }
-            BinaryOp::Slt => (),
-            BinaryOp::Sle => (),
-            BinaryOp::Lt => {
-                if r_is_zero {
-                    return Ok(NodeEval::Const(FieldElement::zero(), ObjectType::boolean()));
-                    //n.b we assume the type of lhs and rhs is unsigned because of the opcode, we could also verify this
-                } else if let (Some(lhs), Some(rhs)) = (lhs, rhs) {
-                    return Ok(NodeEval::Const(
-                        FieldElement::from(lhs < rhs),
-                        ObjectType::boolean(),
-                    ));
-                }
-            }
-            BinaryOp::Lte => {
-                if l_is_zero {
-                    return Ok(NodeEval::Const(FieldElement::one(), ObjectType::boolean()));
-                    //n.b we assume the type of lhs and rhs is unsigned because of the opcode, we could also verify this
-                } else if let (Some(lhs), Some(rhs)) = (lhs, rhs) {
-                    return Ok(NodeEval::Const(
-                        FieldElement::from(lhs <= rhs),
-                        ObjectType::boolean(),
-                    ));
-                }
-            }
-            BinaryOp::Eq => {
-                if self.lhs == self.rhs {
-                    return Ok(NodeEval::Const(FieldElement::one(), ObjectType::boolean()));
-                } else if let (Some(lhs), Some(rhs)) = (lhs, rhs) {
-                    return Ok(NodeEval::Const(
-                        FieldElement::from(lhs == rhs),
-                        ObjectType::boolean(),
-                    ));
-                }
-            }
-            BinaryOp::Ne => {
-                if self.lhs == self.rhs {
-                    return Ok(NodeEval::Const(FieldElement::zero(), ObjectType::boolean()));
-                } else if let (Some(lhs), Some(rhs)) = (lhs, rhs) {
-                    return Ok(NodeEval::Const(
-                        FieldElement::from(lhs != rhs),
-                        ObjectType::boolean(),
-                    ));
-                }
-            }
-            BinaryOp::And => {
-                //Bitwise AND
-                if l_is_zero || self.lhs == self.rhs {
-                    return Ok(l_eval);
-                } else if r_is_zero {
-                    return Ok(r_eval);
-                } else if let (Some(lhs), Some(rhs)) = (lhs, rhs) {
-                    return Ok(wrapping(lhs, rhs, res_type, u128::bitand, field_op_not_allowed));
-                } else {
-                    let n = res_type.bits();
-                    let max = FieldElement::from(2_u128.pow(n) - 1);
-                    if lhs == Some(max) {
-                        return Ok(r_eval);
-                    } else if rhs == Some(max) {
-                        return Ok(l_eval);
-                    }
-                }
-            }
-            BinaryOp::Or => {
-                //Bitwise OR
-                if l_is_zero || self.lhs == self.rhs {
-                    return Ok(r_eval);
-                } else if r_is_zero {
-                    return Ok(l_eval);
-                } else if let (Some(lhs), Some(rhs)) = (lhs, rhs) {
-                    return Ok(wrapping(lhs, rhs, res_type, u128::bitor, field_op_not_allowed));
-                } else {
-                    let n = res_type.bits();
-                    let max = FieldElement::from(2_u128.pow(n) - 1);
-                    if lhs == Some(max) || rhs == Some(max) {
-                        return Ok(NodeEval::Const(max, res_type));
-                    }
-                }
-            }
-            BinaryOp::Xor => {
-                if self.lhs == self.rhs {
-                    return Ok(NodeEval::Const(FieldElement::zero(), res_type));
-                } else if l_is_zero {
-                    return Ok(r_eval);
-                } else if r_is_zero {
-                    return Ok(l_eval);
-                } else if let (Some(lhs), Some(rhs)) = (lhs, rhs) {
-                    return Ok(wrapping(lhs, rhs, res_type, u128::bitxor, field_op_not_allowed));
-                }
-            }
-            BinaryOp::Shl => {
-                if l_is_zero {
-                    return Ok(l_eval);
-                }
-                if r_is_zero {
-                    return Ok(l_eval);
-                }
-                if let (Some(lhs), Some(rhs)) = (lhs, rhs) {
-                    return Ok(wrapping(lhs, rhs, res_type, u128::shl, field_op_not_allowed));
-                }
-            }
-            BinaryOp::Shr(_) => {
-                if l_is_zero {
-                    return Ok(l_eval);
-                }
-                if r_is_zero {
-                    return Ok(l_eval);
-                }
-                if let (Some(lhs), Some(rhs)) = (lhs, rhs) {
-                    return Ok(wrapping(lhs, rhs, res_type, u128::shr, field_op_not_allowed));
-                }
-            }
-            BinaryOp::Assign => (),
-        }
-        Ok(NodeEval::VarOrInstruction(id))
-    }
-
-    fn truncate_required(&self) -> bool {
-        match &self.operator {
-            BinaryOp::Add => false,
-            BinaryOp::SafeAdd => false,
-            BinaryOp::Sub { .. } => false,
-            BinaryOp::SafeSub { .. } => false,
-            BinaryOp::Mul => false,
-            BinaryOp::SafeMul => false,
-            BinaryOp::Udiv(_) => true,
-            BinaryOp::Sdiv(_) => true,
-            BinaryOp::Urem(_) => true,
-            BinaryOp::Srem(_) => true,
-            BinaryOp::Div(_) => false,
-            BinaryOp::Eq => true,
-            BinaryOp::Ne => true,
-            BinaryOp::Ult => true,
-            BinaryOp::Ule => true,
-            BinaryOp::Slt => true,
-            BinaryOp::Sle => true,
-            BinaryOp::Lt => true,
-            BinaryOp::Lte => true,
-            BinaryOp::And => true,
-            BinaryOp::Or => true,
-            BinaryOp::Xor => true,
-            BinaryOp::Assign => false,
-            BinaryOp::Shl => true,
-            BinaryOp::Shr(_) => true,
-        }
-    }
-
-    pub(super) fn opcode(&self) -> Opcode {
-        match &self.operator {
-            BinaryOp::Add => Opcode::Add,
-            BinaryOp::SafeAdd => Opcode::SafeAdd,
-            BinaryOp::Sub { .. } => Opcode::Sub,
-            BinaryOp::SafeSub { .. } => Opcode::SafeSub,
-            BinaryOp::Mul => Opcode::Mul,
-            BinaryOp::SafeMul => Opcode::SafeMul,
-            BinaryOp::Udiv(_) => Opcode::Udiv,
-            BinaryOp::Sdiv(_) => Opcode::Sdiv,
-            BinaryOp::Urem(_) => Opcode::Urem,
-            BinaryOp::Srem(_) => Opcode::Srem,
-            BinaryOp::Div(_) => Opcode::Div,
-            BinaryOp::Eq => Opcode::Eq,
-            BinaryOp::Ne => Opcode::Ne,
-            BinaryOp::Ult => Opcode::Ult,
-            BinaryOp::Ule => Opcode::Ule,
-            BinaryOp::Slt => Opcode::Slt,
-            BinaryOp::Sle => Opcode::Sle,
-            BinaryOp::Lt => Opcode::Lt,
-            BinaryOp::Lte => Opcode::Lte,
-            BinaryOp::And => Opcode::And,
-            BinaryOp::Or => Opcode::Or,
-            BinaryOp::Xor => Opcode::Xor,
-            BinaryOp::Shl => Opcode::Shl,
-            BinaryOp::Shr(_) => Opcode::Shr,
-            BinaryOp::Assign => Opcode::Assign,
-        }
-    }
-}
-
-/// Perform the given numeric operation and modulo the result by the max value for the given bit count
-/// if the res_type is not a NativeField.
-fn wrapping(
-    lhs: FieldElement,
-    rhs: FieldElement,
-    res_type: ObjectType,
-    u128_op: impl FnOnce(u128, u128) -> u128,
-    field_op: impl FnOnce(FieldElement, FieldElement) -> FieldElement,
-) -> NodeEval {
-    if !res_type.is_native_field() {
-        let type_modulo = 1_u128 << res_type.bits();
-        let lhs = lhs.to_u128() % type_modulo;
-        let rhs = rhs.to_u128() % type_modulo;
-        let mut x = u128_op(lhs, rhs);
-        x %= type_modulo;
-        NodeEval::from_u128(x, res_type)
-    } else {
-        NodeEval::Const(field_op(lhs, rhs), res_type)
-    }
-}
-
-fn field_op_not_allowed(_lhs: FieldElement, _rhs: FieldElement) -> FieldElement {
-    unreachable!("operation not allowed for FieldElement");
-}
-
-impl Operation {
-    pub(super) fn binary(op: BinaryOp, lhs: NodeId, rhs: NodeId) -> Self {
-        Operation::Binary(Binary::new(op, lhs, rhs))
-    }
-
-    pub(super) fn is_dummy_store(&self) -> bool {
-        match self {
-            Operation::Store { index, value, .. } => {
-                *index == NodeId::dummy() && *value == NodeId::dummy()
-            }
-            _ => false,
-        }
-    }
-
-    pub(super) fn map_id(&self, mut f: impl FnMut(NodeId) -> NodeId) -> Operation {
-        use Operation::*;
-        match self {
-            Binary(self::Binary { lhs, rhs, operator, predicate }) => Binary(self::Binary {
-                lhs: f(*lhs),
-                rhs: f(*rhs),
-                operator: operator.clone(),
-                predicate: predicate.as_ref().map(|pred| f(*pred)),
-            }),
-            Cast(value) => Cast(f(*value)),
-            Truncate { value, bit_size, max_bit_size } => {
-                Truncate { value: f(*value), bit_size: *bit_size, max_bit_size: *max_bit_size }
-            }
-            Not(id) => Not(f(*id)),
-            Constrain(id, loc) => Constrain(f(*id), *loc),
-            Jne(id, block) => Jne(f(*id), *block),
-            Jeq(id, block) => Jeq(f(*id), *block),
-            Jmp(block) => Jmp(*block),
-            Phi { root, block_args } => Phi {
-                root: f(*root),
-                block_args: vecmap(block_args, |(id, block)| (f(*id), *block)),
-            },
-            Cond { condition, val_true: lhs, val_false: rhs } => {
-                Cond { condition: f(*condition), val_true: f(*lhs), val_false: f(*rhs) }
-            }
-            Load { array_id: array, index, location } => {
-                Load { array_id: *array, index: f(*index), location: *location }
-            }
-            Store { array_id: array, index, value, predicate, location } => Store {
-                array_id: *array,
-                index: f(*index),
-                value: f(*value),
-                predicate: predicate.as_ref().map(|pred| f(*pred)),
-                location: *location,
-            },
-            Intrinsic(i, args) => Intrinsic(*i, vecmap(args.iter().copied(), f)),
-            Nop => Nop,
-            Call { func: func_id, arguments, returned_arrays, predicate, location } => Call {
-                func: f(*func_id),
-                arguments: vecmap(arguments.iter().copied(), f),
-                returned_arrays: returned_arrays.clone(),
-                predicate: *predicate,
-                location: *location,
-            },
-            Return(values) => Return(vecmap(values.iter().copied(), f)),
-            Result { call_instruction, index } => {
-                Result { call_instruction: f(*call_instruction), index: *index }
-            }
-        }
-    }
-
-    /// Mutate each contained NodeId in place using the given function f
-    pub(super) fn map_id_mut(&mut self, mut f: impl FnMut(NodeId) -> NodeId) {
-        use Operation::*;
-        match self {
-            Binary(self::Binary { lhs, rhs, predicate, .. }) => {
-                *lhs = f(*lhs);
-                *rhs = f(*rhs);
-                *predicate = predicate.as_mut().map(|pred| f(*pred));
-            }
-            Cast(value) => *value = f(*value),
-            Truncate { value, .. } => *value = f(*value),
-            Not(id) => *id = f(*id),
-            Constrain(id, ..) => *id = f(*id),
-            Jne(id, _) => *id = f(*id),
-            Jeq(id, _) => *id = f(*id),
-            Jmp(_) => (),
-            Phi { root, block_args } => {
-                f(*root);
-                for (id, _block) in block_args {
-                    *id = f(*id);
-                }
-            }
-            Cond { condition, val_true: lhs, val_false: rhs } => {
-                *condition = f(*condition);
-                *lhs = f(*lhs);
-                *rhs = f(*rhs);
-            }
-            Load { index, .. } => *index = f(*index),
-            Store { index, value, predicate, .. } => {
-                *index = f(*index);
-                *value = f(*value);
-                *predicate = predicate.as_mut().map(|pred| f(*pred));
-            }
-            Intrinsic(_, args) => {
-                for arg in args {
-                    *arg = f(*arg);
-                }
-            }
-            Nop => (),
-            Call { func, arguments, .. } => {
-                *func = f(*func);
-                for arg in arguments {
-                    *arg = f(*arg);
-                }
-            }
-            Return(values) => {
-                for value in values {
-                    *value = f(*value);
-                }
-            }
-            Result { call_instruction, index: _ } => {
-                *call_instruction = f(*call_instruction);
-            }
-        }
-    }
-
-    /// This is the same as map_id but doesn't return a new Operation
-    pub(super) fn for_each_id(&self, mut f: impl FnMut(NodeId)) {
-        use Operation::*;
-        match self {
-            Binary(self::Binary { lhs, rhs, .. }) => {
-                f(*lhs);
-                f(*rhs);
-            }
-            Cast(value) => f(*value),
-            Truncate { value, .. } => f(*value),
-            Not(id) => f(*id),
-            Constrain(id, ..) => f(*id),
-            Jne(id, _) => f(*id),
-            Jeq(id, _) => f(*id),
-            Jmp(_) => (),
-            Phi { root, block_args } => {
-                f(*root);
-                for (id, _block) in block_args {
-                    f(*id);
-                }
-            }
-            Cond { condition, val_true: lhs, val_false: rhs } => {
-                f(*condition);
-                f(*lhs);
-                f(*rhs);
-            }
-            Load { index, .. } => f(*index),
-            Store { index, value, .. } => {
-                f(*index);
-                f(*value);
-            }
-            Intrinsic(_, args) => args.iter().copied().for_each(f),
-            Nop => (),
-            Call { func, arguments, .. } => {
-                f(*func);
-                arguments.iter().copied().for_each(f);
-            }
-            Return(values) => values.iter().copied().for_each(f),
-            Result { call_instruction, .. } => {
-                f(*call_instruction);
-            }
-        }
-    }
-
-    pub(super) fn opcode(&self) -> Opcode {
-        match self {
-            Operation::Binary(binary) => binary.opcode(),
-            Operation::Cast(_) => Opcode::Cast,
-            Operation::Truncate { .. } => Opcode::Truncate,
-            Operation::Not(_) => Opcode::Not,
-            Operation::Constrain(..) => Opcode::Constrain,
-            Operation::Jne(_, _) => Opcode::Jne,
-            Operation::Jeq(_, _) => Opcode::Jeq,
-            Operation::Jmp(_) => Opcode::Jmp,
-            Operation::Phi { .. } => Opcode::Phi,
-            Operation::Cond { .. } => Opcode::Cond,
-            Operation::Call { func, .. } => Opcode::Call(*func),
-            Operation::Return(_) => Opcode::Return,
-            Operation::Result { .. } => Opcode::Results,
-            Operation::Load { array_id, .. } => Opcode::Load(*array_id),
-            Operation::Store { array_id, .. } => Opcode::Store(*array_id),
-            Operation::Intrinsic(opcode, _) => Opcode::Intrinsic(*opcode),
-            Operation::Nop => Opcode::Nop,
-        }
-    }
-}
-
-impl BinaryOp {
-    fn is_commutative(&self) -> bool {
-        matches!(
-            self,
-            BinaryOp::Add
-                | BinaryOp::SafeAdd
-                | BinaryOp::Mul
-                | BinaryOp::SafeMul
-                | BinaryOp::And
-                | BinaryOp::Or
-                | BinaryOp::Xor
-        )
-    }
-}
-// TODO: We should create a constant and explain where the 127 and 126 constants
-// TODO are from
-fn field_to_signed(f: FieldElement, n: u32) -> i128 {
-    assert!(n < 127);
-    let a = f.to_u128();
-    let pow_2 = 2_u128.pow(n);
-    if a < pow_2 {
-        a as i128
-    } else {
-        (a - 2 * pow_2) as i128
-    }
-}
-
-fn signed_to_field(a: i128, n: u32) -> Result<FieldElement, RuntimeError> {
-    if n >= 126 {
-        return Err(RuntimeErrorKind::UnstructuredError {
-            message: "ICE: cannot convert signed {n} bit size into field".to_string(),
-        })?;
-    }
-    if a >= 0 {
-        Ok(FieldElement::from(a))
-    } else {
-        let b = (a + 2_i128.pow(n + 1)) as u128;
-        Ok(FieldElement::from(b))
-    }
-}
diff --git a/crates/noirc_evaluator/src/ssa/optimizations.rs b/crates/noirc_evaluator/src/ssa/optimizations.rs
deleted file mode 100644
index 55756c76e8a..00000000000
--- a/crates/noirc_evaluator/src/ssa/optimizations.rs
+++ /dev/null
@@ -1,596 +0,0 @@
-use crate::errors::{RuntimeError, RuntimeErrorKind};
-use crate::ssa::{
-    anchor::{Anchor, CseAction},
-    block::BlockId,
-    builtin,
-    context::SsaContext,
-    node::{
-        Binary, BinaryOp, Instruction, Mark, Node, NodeEval, NodeId, ObjectType, Opcode, Operation,
-    },
-};
-use acvm::FieldElement;
-use num_bigint::BigUint;
-
-pub(super) fn simplify_id(ctx: &mut SsaContext, ins_id: NodeId) -> Result<(), RuntimeError> {
-    let mut ins = ctx.instruction(ins_id).clone();
-    simplify(ctx, &mut ins)?;
-    ctx[ins_id] = super::node::NodeObject::Instr(ins);
-    Ok(())
-}
-
-// Performs constant folding, arithmetic simplifications and move to standard form
-// Modifies ins.mark with whether the instruction should be deleted, replaced, or neither
-pub(super) fn simplify(ctx: &mut SsaContext, ins: &mut Instruction) -> Result<(), RuntimeError> {
-    if ins.is_deleted() {
-        return Ok(());
-    }
-    //1. constant folding
-    let new_id = ins.evaluate(ctx)?.to_index(ctx);
-
-    if new_id != ins.id {
-        use Mark::*;
-        ins.mark = if new_id == NodeId::dummy() { Deleted } else { ReplaceWith(new_id) };
-        return Ok(());
-    }
-
-    //2. standard form
-    ins.standard_form();
-    if let Operation::Cast(value_id) = ins.operation {
-        if let Some(value) = ctx.try_get_node(value_id) {
-            if value.get_type() == ins.res_type {
-                ins.mark = Mark::ReplaceWith(value_id);
-                return Ok(());
-            }
-        }
-    }
-
-    //3. left-overs (it requires &mut ctx)
-    if ins.is_deleted() {
-        return Ok(());
-    }
-
-    if let Operation::Binary(binary) = &mut ins.operation {
-        if let NodeEval::Const(r_const, r_type) = NodeEval::from_id(ctx, binary.rhs) {
-            if binary.opcode() == Opcode::Div && !r_const.is_zero() {
-                binary.rhs = ctx.get_or_create_const(r_const.inverse(), r_type);
-                binary.operator = BinaryOp::Mul;
-            }
-        }
-    }
-    if let Operation::Binary(binary) = &ins.operation {
-        if binary.operator == BinaryOp::Xor && ins.res_type.bits() < 128 {
-            let max = FieldElement::from(2_u128.pow(ins.res_type.bits()) - 1);
-            if NodeEval::from_id(ctx, binary.rhs).into_const_value() == Some(max) {
-                ins.operation = Operation::Not(binary.lhs);
-            } else if NodeEval::from_id(ctx, binary.lhs).into_const_value() == Some(max) {
-                ins.operation = Operation::Not(binary.rhs);
-            }
-        }
-    }
-
-    Ok(())
-}
-
-fn evaluate_intrinsic(
-    ctx: &mut SsaContext,
-    op: builtin::Opcode,
-    args: Vec<FieldElement>,
-    res_type: &ObjectType,
-    block_id: BlockId,
-) -> Result<Vec<NodeId>, RuntimeErrorKind> {
-    match op {
-        builtin::Opcode::ToBits(endian) => {
-            let bit_count = args[1].to_u128() as u32;
-            let mut result = Vec::new();
-            let mut bits = args[0].bits();
-            bits.reverse();
-            bits.resize(bit_count as usize, false);
-            if endian == builtin::Endian::Big {
-                bits.reverse();
-            }
-
-            if let ObjectType::ArrayPointer(a) = res_type {
-                for i in 0..bit_count {
-                    let index = ctx.get_or_create_const(
-                        FieldElement::from(i as i128),
-                        ObjectType::native_field(),
-                    );
-                    let op = if i < bits.len() as u32 && bits[i as usize] {
-                        Operation::Store {
-                            array_id: *a,
-                            index,
-                            value: ctx.one(),
-                            predicate: None,
-                            location: None,
-                        }
-                    } else {
-                        Operation::Store {
-                            array_id: *a,
-                            index,
-                            value: ctx.zero(),
-                            predicate: None,
-                            location: None,
-                        }
-                    };
-                    let i = Instruction::new(op, ObjectType::NotAnObject, Some(block_id));
-                    result.push(ctx.add_instruction(i));
-                }
-                return Ok(result);
-            }
-            unreachable!(
-                "compiler error: to bits should have a Pointer result type and be decomposed."
-            );
-        }
-        builtin::Opcode::ToRadix(endian) => {
-            let mut element = BigUint::from_bytes_be(&args[0].to_be_bytes())
-                .to_radix_le(args[1].to_u128() as u32);
-            let byte_count = args[2].to_u128() as u32;
-            let diff = if byte_count >= element.len() as u32 {
-                byte_count - element.len() as u32
-            } else {
-                return Err(RuntimeErrorKind::ArrayOutOfBounds {
-                    index: element.len() as u128,
-                    bound: byte_count as u128,
-                });
-            };
-            element.extend(vec![0; diff as usize]);
-            if endian == builtin::Endian::Big {
-                element.reverse();
-            }
-            let mut result = Vec::new();
-
-            if let ObjectType::ArrayPointer(a) = res_type {
-                for (i, item) in element.iter().enumerate() {
-                    let index = ctx.get_or_create_const(
-                        FieldElement::from(i as i128),
-                        ObjectType::native_field(),
-                    );
-                    let value = ctx.get_or_create_const(
-                        FieldElement::from(*item as i128),
-                        ObjectType::native_field(),
-                    );
-                    let op = Operation::Store {
-                        array_id: *a,
-                        index,
-                        value,
-                        predicate: None,
-                        location: None,
-                    };
-
-                    let i = Instruction::new(op, ObjectType::NotAnObject, Some(block_id));
-                    result.push(ctx.add_instruction(i));
-                }
-                return Ok(result);
-            }
-            unreachable!(
-                "compiler error: to radix should have a Pointer result type and be decomposed."
-            );
-        }
-        _ => todo!(),
-    }
-}
-
-//
-// The following code will be concerned with Common Subexpression Elimination (CSE)
-//
-
-pub(super) fn propagate(ctx: &SsaContext, id: NodeId, modified: &mut bool) -> NodeId {
-    if let Some(obj) = ctx.try_get_instruction(id) {
-        if let Mark::ReplaceWith(replacement) = obj.mark {
-            *modified = true;
-            return replacement;
-        } else if let Operation::Binary(Binary { operator: BinaryOp::Assign, rhs, .. }) =
-            &obj.operation
-        {
-            *modified = true;
-            return *rhs;
-        }
-    }
-    id
-}
-
-//common subexpression elimination, starting from the root
-pub(super) fn cse(
-    ir_gen: &mut SsaContext,
-    first_block: BlockId,
-    stop_on_error: bool,
-) -> Result<Option<NodeId>, RuntimeError> {
-    let mut anchor = Anchor::default();
-    let mut modified = false;
-    cse_tree(ir_gen, first_block, &mut anchor, &mut modified, stop_on_error)
-}
-
-//Perform CSE for the provided block and then process its children following the dominator tree, passing around the anchor list.
-fn cse_tree(
-    ir_gen: &mut SsaContext,
-    block_id: BlockId,
-    anchor: &mut Anchor,
-    modified: &mut bool,
-    stop_on_error: bool,
-) -> Result<Option<NodeId>, RuntimeError> {
-    let mut instructions = Vec::new();
-    let mut res = cse_block_with_anchor(
-        ir_gen,
-        block_id,
-        &mut instructions,
-        anchor,
-        modified,
-        stop_on_error,
-    )?;
-    for b in ir_gen[block_id].dominated.clone() {
-        let sub_res = cse_tree(ir_gen, b, &mut anchor.clone(), modified, stop_on_error)?;
-        if sub_res.is_some() {
-            res = sub_res;
-        }
-    }
-    Ok(res)
-}
-
-//perform common subexpression elimination until there is no more change
-pub(super) fn full_cse(
-    ir_gen: &mut SsaContext,
-    first_block: BlockId,
-    report_error: bool,
-) -> Result<Option<NodeId>, RuntimeError> {
-    let mut modified = true;
-    let mut result = None;
-    while modified {
-        modified = false;
-        let mut anchor = Anchor::default();
-        result = cse_tree(ir_gen, first_block, &mut anchor, &mut modified, report_error)?;
-    }
-    Ok(result)
-}
-
-pub(super) fn simple_cse(
-    ctx: &mut SsaContext,
-    block_id: BlockId,
-) -> Result<Option<NodeId>, RuntimeError> {
-    let mut modified = false;
-    let mut instructions = Vec::new();
-    cse_block(ctx, block_id, &mut instructions, &mut modified)
-}
-
-pub(super) fn cse_block(
-    ctx: &mut SsaContext,
-    block_id: BlockId,
-    instructions: &mut Vec<NodeId>,
-    modified: &mut bool,
-) -> Result<Option<NodeId>, RuntimeError> {
-    cse_block_with_anchor(ctx, block_id, instructions, &mut Anchor::default(), modified, false)
-}
-
-//Performs common subexpression elimination and copy propagation on a block
-fn cse_block_with_anchor(
-    ctx: &mut SsaContext,
-    block_id: BlockId,
-    instructions: &mut Vec<NodeId>,
-    anchor: &mut Anchor,
-    modified: &mut bool,
-    stop_on_error: bool,
-) -> Result<Option<NodeId>, RuntimeError> {
-    let mut new_list = Vec::new();
-    let bb = &ctx[block_id];
-    let is_join = bb.predecessor.len() > 1;
-    if instructions.is_empty() {
-        instructions.append(&mut bb.instructions.clone());
-    }
-
-    for ins_id in instructions {
-        if let Some(ins) = ctx.try_get_instruction(*ins_id) {
-            if ins.is_deleted() {
-                continue;
-            }
-            let mut operator = ins.operation.map_id(|id| propagate(ctx, id, modified));
-
-            let mut new_mark = Mark::None;
-
-            match &operator {
-                Operation::Binary(binary) => {
-                    if let ObjectType::ArrayPointer(a) = ctx.object_type(binary.lhs) {
-                        //No CSE for arrays because they are not in SSA form
-                        //We could improve this in future by checking if the arrays are immutable or not modified in-between
-                        let id = ctx.get_dummy_load(a);
-                        anchor.push_mem_instruction(ctx, id)?;
-
-                        if let ObjectType::ArrayPointer(a) = ctx.object_type(binary.rhs) {
-                            let id = ctx.get_dummy_load(a);
-                            anchor.push_mem_instruction(ctx, id)?;
-                        }
-
-                        new_list.push(*ins_id);
-                    } else if let Some(similar) = anchor.find_similar_instruction(&operator) {
-                        assert_ne!(similar, ins.id);
-                        *modified = true;
-                        new_mark = Mark::ReplaceWith(similar);
-                    } else if binary.operator == BinaryOp::Assign {
-                        *modified = true;
-                        new_mark = Mark::ReplaceWith(binary.rhs);
-                    } else {
-                        new_list.push(*ins_id);
-                        anchor.push_front(&ins.operation, *ins_id);
-                    }
-                }
-                Operation::Result { .. } => {
-                    if let Some(similar) = anchor.find_similar_instruction(&operator) {
-                        assert_ne!(similar, ins.id);
-                        *modified = true;
-                        new_mark = Mark::ReplaceWith(similar);
-                    } else {
-                        new_list.push(*ins_id);
-                        anchor.push_front(&ins.operation, *ins_id);
-                    }
-                }
-                Operation::Load { array_id: x, location, .. }
-                | Operation::Store { array_id: x, location, .. } => {
-                    if !is_join && ins.operation.is_dummy_store() {
-                        continue;
-                    }
-                    anchor.use_array(*x, ctx.mem[*x].len as usize);
-                    let prev_ins = anchor.get_mem_all(*x);
-                    let into_runtime_error =
-                        |err: RuntimeErrorKind| RuntimeError { location: *location, kind: err };
-                    match anchor.find_similar_mem_instruction(ctx, &operator, prev_ins) {
-                        Ok(CseAction::Keep) => {
-                            anchor
-                                .push_mem_instruction(ctx, *ins_id)
-                                .map_err(into_runtime_error)?;
-                            new_list.push(*ins_id);
-                        }
-                        Ok(CseAction::ReplaceWith(new_id)) => {
-                            *modified = true;
-                            new_mark = Mark::ReplaceWith(new_id);
-                        }
-                        Ok(CseAction::Remove(id_to_remove)) => {
-                            anchor
-                                .push_mem_instruction(ctx, *ins_id)
-                                .map_err(into_runtime_error)?;
-                            // TODO if not found, it should be removed from other blocks; we could keep a list of instructions to remove
-                            if let Some(id) = new_list.iter().position(|x| *x == id_to_remove) {
-                                *modified = true;
-                                new_list.remove(id);
-                            }
-                            // Store with predicate must be merged with the previous store
-                            if let Operation::Store {
-                                index: idx,
-                                value: value2,
-                                predicate: Some(predicate2),
-                                location: location1,
-                                ..
-                            } = operator
-                            {
-                                if let Operation::Store {
-                                    value: value1,
-                                    predicate: predicate1,
-                                    location: location2,
-                                    ..
-                                } = ctx.instruction(id_to_remove).operation
-                                {
-                                    let (merge, pred) = if let Some(predicate1) = predicate1 {
-                                        if predicate1 != predicate2 {
-                                            let or_op = Operation::Binary(Binary {
-                                                lhs: predicate1,
-                                                rhs: predicate2,
-                                                operator: BinaryOp::Or,
-                                                predicate: None,
-                                            });
-                                            let pred_id = ctx.add_instruction(Instruction::new(
-                                                or_op,
-                                                ObjectType::boolean(),
-                                                Some(block_id),
-                                            ));
-                                            new_list.push(pred_id);
-                                            (true, Some(pred_id))
-                                        } else {
-                                            (false, None)
-                                        }
-                                    } else {
-                                        (true, None)
-                                    };
-                                    if merge {
-                                        *modified = true;
-                                        let cond_op = Operation::Cond {
-                                            condition: predicate2,
-                                            val_true: value2,
-                                            val_false: value1,
-                                        };
-                                        let cond_id = ctx.add_instruction(Instruction::new(
-                                            cond_op,
-                                            ctx.object_type(value2),
-                                            Some(block_id),
-                                        ));
-                                        new_list.push(cond_id);
-                                        operator = Operation::Store {
-                                            array_id: *x,
-                                            index: idx,
-                                            value: cond_id,
-                                            predicate: pred,
-                                            location: RuntimeError::merge_location(
-                                                location1, location2,
-                                            ),
-                                        };
-                                    }
-                                } else {
-                                    unreachable!("ICE: expected store instruction")
-                                }
-                            }
-                            new_list.push(*ins_id);
-                        }
-                        Err(err) => {
-                            return Err(RuntimeError { location: *location, kind: err });
-                        }
-                    }
-                }
-                Operation::Phi { block_args, .. } => {
-                    // propagate phi arguments
-                    if let Some(first) = Instruction::simplify_phi(ins.id, block_args) {
-                        if first == ins.id {
-                            new_list.push(*ins_id);
-                        } else {
-                            *modified = true;
-                            new_mark = Mark::ReplaceWith(first);
-                        }
-                    } else {
-                        new_mark = Mark::Deleted;
-                    }
-                }
-                Operation::Cast(_) => {
-                    //Similar cast must have same type
-                    if let Some(similar) = anchor.find_similar_cast(ctx, &operator, ins.res_type) {
-                        new_mark = Mark::ReplaceWith(similar);
-                        *modified = true;
-                    } else {
-                        new_list.push(*ins_id);
-                        anchor.push_cast_front(&operator, *ins_id, ins.res_type);
-                    }
-                }
-                Operation::Call { func, arguments, returned_arrays, .. } => {
-                    //No CSE for function calls because of possible side effect - TODO checks if a function has side effect when parsed and do cse for these.
-                    //Add dummy store for functions that modify arrays
-                    for a in returned_arrays {
-                        let id = ctx.get_dummy_store(a.0);
-                        anchor.push_mem_instruction(ctx, id)?;
-                    }
-                    if let Some(f) = ctx.try_get_ssa_func(*func) {
-                        for typ in &f.result_types {
-                            if let ObjectType::ArrayPointer(a) = typ {
-                                let id = ctx.get_dummy_store(*a);
-                                anchor.push_mem_instruction(ctx, id)?;
-                            }
-                        }
-                    }
-                    //Add dummy load for function arguments:
-                    for arg in arguments {
-                        if let Some(obj) = ctx.try_get_node(*arg) {
-                            if let ObjectType::ArrayPointer(a) = obj.get_type() {
-                                let id = ctx.get_dummy_load(a);
-                                anchor.push_mem_instruction(ctx, id)?;
-                            }
-                        }
-                    }
-                    new_list.push(*ins_id);
-                }
-                Operation::Return(..) => new_list.push(*ins_id),
-                Operation::Intrinsic(opcode, args) => {
-                    //Add dummy load for function arguments and enable CSE only if no array in argument
-                    let mut activate_cse = true;
-                    // We do not want to replace any print intrinsics as we want them to remain in order and unchanged
-                    if let builtin::Opcode::Println(_) = opcode {
-                        activate_cse = false;
-                    }
-
-                    for arg in args {
-                        if let Some(obj) = ctx.try_get_node(*arg) {
-                            if let ObjectType::ArrayPointer(a) = obj.get_type() {
-                                let id = ctx.get_dummy_load(a);
-                                anchor.push_mem_instruction(ctx, id)?;
-                                activate_cse = false;
-                            }
-                        }
-                    }
-                    if let ObjectType::ArrayPointer(a) = ins.res_type {
-                        let id = ctx.get_dummy_store(a);
-                        anchor.push_mem_instruction(ctx, id)?;
-                        activate_cse = false;
-                    }
-
-                    if activate_cse {
-                        if let Some(similar) = anchor.find_similar_instruction(&operator) {
-                            *modified = true;
-                            new_mark = Mark::ReplaceWith(similar);
-                        } else {
-                            new_list.push(*ins_id);
-                            anchor.push_front(&operator, *ins_id);
-                        }
-                    } else {
-                        new_list.push(*ins_id);
-                    }
-                }
-                Operation::Nop => {
-                    if new_list.is_empty() {
-                        new_list.push(*ins_id);
-                    }
-                }
-                Operation::Constrain(condition, location) => {
-                    if let Some(similar) = anchor.find_similar_instruction(&operator) {
-                        assert_ne!(similar, ins.id);
-                        *modified = true;
-                        let similar_ins = ctx
-                            .try_get_mut_instruction(similar)
-                            .expect("Similar instructions are instructions");
-                        if location.is_some() && similar_ins.get_location().is_none() {
-                            similar_ins.operation = Operation::Constrain(*condition, *location);
-                        }
-                        new_mark = Mark::ReplaceWith(similar);
-                    } else {
-                        new_list.push(*ins_id);
-                        anchor.push_front(&ins.operation, *ins_id);
-                    }
-                }
-                _ => {
-                    //TODO: checks we do not need to propagate res arguments
-                    new_list.push(*ins_id);
-                }
-            }
-
-            let update = ctx.instruction_mut(*ins_id);
-
-            update.operation = operator;
-            update.mark = new_mark;
-            if new_mark == Mark::Deleted {
-                update.operation = Operation::Nop;
-            }
-            update.parent_block = block_id;
-
-            let mut update2 = update.clone();
-
-            let result = simplify(ctx, &mut update2);
-            if stop_on_error {
-                result?;
-            }
-
-            //cannot simplify to_le_bits() in the previous call because it get replaced with multiple instructions
-            if let Operation::Intrinsic(opcode, args) = &update2.operation {
-                match opcode {
-                    // We do not simplify print statements
-                    builtin::Opcode::Println(_) => (),
-                    _ => {
-                        let args =
-                            args.iter().map(|arg| NodeEval::from_id(ctx, *arg).into_const_value());
-
-                        if let Some(args) = args.collect() {
-                            update2.mark = Mark::Deleted;
-                            new_list.extend(evaluate_intrinsic(
-                                ctx,
-                                *opcode,
-                                args,
-                                &update2.res_type,
-                                block_id,
-                            )?);
-                        }
-                    }
-                }
-            }
-            let update3 = ctx.instruction_mut(*ins_id);
-            *update3 = update2;
-        }
-    }
-
-    let last = new_list.iter().copied().rev().find(|id| is_some(ctx, *id));
-    ctx[block_id].instructions = new_list;
-    Ok(last)
-}
-
-fn is_some(ctx: &SsaContext, id: NodeId) -> bool {
-    if id == NodeId::dummy() {
-        return false;
-    }
-    if let Some(ins) = ctx.try_get_instruction(id) {
-        if ins.operation != Operation::Nop {
-            return true;
-        }
-    } else if ctx.try_get_node(id).is_some() {
-        return true;
-    }
-    false
-}
diff --git a/crates/noirc_evaluator/src/ssa/ssa_form.rs b/crates/noirc_evaluator/src/ssa/ssa_form.rs
deleted file mode 100644
index 09ed7810483..00000000000
--- a/crates/noirc_evaluator/src/ssa/ssa_form.rs
+++ /dev/null
@@ -1,125 +0,0 @@
-use crate::ssa::{
-    block::BlockId,
-    context::SsaContext,
-    node::{Mark, NodeId, Operation},
-    {block, node},
-};
-use std::collections::HashSet;
-
-// create phi arguments from the predecessors of the block (containing phi)
-fn write_phi(ctx: &mut SsaContext, predecessors: &[BlockId], var: NodeId, phi: NodeId) {
-    let mut result = Vec::new();
-    for b in predecessors {
-        let v = get_current_value_in_block(ctx, var, *b);
-        result.push((v, *b));
-    }
-    let s2 = node::Instruction::simplify_phi(phi, &result);
-    if let Some(phi_ins) = ctx.try_get_mut_instruction(phi) {
-        let phi_args = match &mut phi_ins.operation {
-            Operation::Phi { block_args, .. } => block_args,
-            _ => unreachable!(),
-        };
-
-        assert_eq!(phi_args.len(), 0);
-        if let Some(s_phi) = s2 {
-            if s_phi != phi {
-                phi_ins.mark = Mark::ReplaceWith(s_phi);
-                //eventually simplify recursively: if a phi instruction is in phi use list, call simplify_phi() on it
-                //but cse should deal with most of it.
-            } else {
-                //s2 == phi
-                *phi_args = result;
-            }
-        } else {
-            //s2 is None
-            phi_ins.mark = Mark::Deleted;
-        }
-    }
-}
-
-pub(super) fn seal_block(ctx: &mut SsaContext, block_id: BlockId, entry_block: BlockId) {
-    let block = &ctx[block_id];
-    let pred = block.predecessor.clone();
-    let instructions = block.instructions.clone();
-    for i in instructions {
-        if let Some(ins) = ctx.try_get_instruction(i) {
-            if let Operation::Phi { root, .. } = &ins.operation {
-                let root = *root;
-                write_phi(ctx, &pred, root, i);
-            }
-        }
-    }
-    add_dummy_store(ctx, entry_block, block_id);
-    ctx.sealed_blocks.insert(block_id);
-}
-
-// write dummy store for join block
-fn add_dummy_store(ctx: &mut SsaContext, entry: BlockId, join: BlockId) {
-    //retrieve modified arrays
-    let mut modified = HashSet::new();
-    if entry == join {
-        block::written_along(ctx, ctx[entry].right.unwrap(), join, &mut modified);
-    } else {
-        block::written_along(ctx, ctx[entry].left.unwrap(), join, &mut modified);
-        block::written_along(ctx, ctx[entry].right.unwrap(), join, &mut modified);
-    }
-
-    //add dummy store
-    for a in modified {
-        let store = node::Operation::Store {
-            array_id: a,
-            index: NodeId::dummy(),
-            value: NodeId::dummy(),
-            predicate: None,
-            location: None,
-        };
-        let i = node::Instruction::new(store, node::ObjectType::NotAnObject, Some(join));
-        ctx.insert_instruction_after_phi(i, join);
-    }
-}
-
-//look-up recursively into predecessors
-fn get_block_value(ctx: &mut SsaContext, root: NodeId, block_id: BlockId) -> NodeId {
-    let result = if !ctx.sealed_blocks.contains(&block_id) {
-        //incomplete CFG
-        ctx.generate_empty_phi(block_id, root)
-    } else {
-        let block = &ctx[block_id];
-        if let Some(idx) = block.get_current_value(root) {
-            return idx;
-        }
-        let pred = block.predecessor.clone();
-        if pred.is_empty() {
-            return root;
-        }
-        if pred.len() == 1 {
-            get_block_value(ctx, root, pred[0])
-        } else {
-            let result = ctx.generate_empty_phi(block_id, root);
-            ctx[block_id].update_variable(root, result);
-            write_phi(ctx, &pred, root, result);
-            result
-        }
-    };
-
-    ctx[block_id].update_variable(root, result);
-    result
-}
-
-//Returns the current SSA value of a variable in a (filled) block.
-pub(super) fn get_current_value_in_block(
-    ctx: &mut SsaContext,
-    var_id: NodeId,
-    block_id: BlockId,
-) -> NodeId {
-    let root = ctx.root_value(var_id);
-
-    ctx[block_id]
-        .get_current_value(root) //Local value numbering
-        .unwrap_or_else(|| get_block_value(ctx, root, block_id)) //Global value numbering
-}
-
-//Returns the current SSA value of a variable, recursively
-pub(super) fn get_current_value(ctx: &mut SsaContext, var_id: NodeId) -> NodeId {
-    get_current_value_in_block(ctx, var_id, ctx.current_block)
-}
diff --git a/crates/noirc_evaluator/src/ssa/ssa_gen.rs b/crates/noirc_evaluator/src/ssa/ssa_gen.rs
deleted file mode 100644
index 11fc134215d..00000000000
--- a/crates/noirc_evaluator/src/ssa/ssa_gen.rs
+++ /dev/null
@@ -1,814 +0,0 @@
-use crate::{
-    errors::{RuntimeError, RuntimeErrorKind},
-    ssa::{
-        block::BlockType,
-        context::SsaContext,
-        function::FuncIndex,
-        mem::ArrayId,
-        node::{Binary, BinaryOp, NodeId, ObjectType, Operation, Variable},
-        value::Value,
-        {block, builtin, node, ssa_form},
-    },
-};
-use acvm::{acir::native_types::Witness, FieldElement};
-use iter_extended::vecmap;
-use noirc_errors::Location;
-use noirc_frontend::{
-    monomorphization::ast::{
-        ArrayLiteral, Definition, Expression, For, Ident, If, LValue, Let, Literal, LocalId,
-        Program, Type,
-    },
-    BinaryOpKind, UnaryOp,
-};
-use num_bigint::BigUint;
-use num_traits::Zero;
-use std::collections::{BTreeMap, HashMap};
-
-pub(crate) struct IrGenerator {
-    pub(crate) context: SsaContext,
-    pub(crate) function_context: Option<FuncIndex>,
-
-    /// The current value of a variable. Used for flattening structs
-    /// into multiple variables/values
-    variable_values: HashMap<Definition, Value>,
-
-    pub(crate) program: Program,
-}
-
-impl IrGenerator {
-    pub(crate) fn new(program: Program) -> IrGenerator {
-        IrGenerator {
-            context: SsaContext::default(),
-            variable_values: HashMap::new(),
-            function_context: None,
-            program,
-        }
-    }
-
-    pub(crate) fn ssa_gen_main(&mut self) -> Result<(), RuntimeError> {
-        let main_body = self.program.take_main_body();
-        let value = self.ssa_gen_expression(&main_body)?;
-        let node_ids = value.to_node_ids();
-
-        if self.program.main().return_type != Type::Unit {
-            self.context.new_instruction(Operation::Return(node_ids), ObjectType::NotAnObject)?;
-        }
-        Ok(())
-    }
-
-    pub(crate) fn find_variable(&self, variable_def: &Definition) -> Option<&Value> {
-        self.variable_values.get(variable_def)
-    }
-
-    /// Returns the ssa value of a variable
-    /// This method constructs the ssa value of a variable, while parsing the AST, using value numbering
-    /// This is why it requires a mutable SsaContext
-    pub(crate) fn get_current_value(&mut self, value: &Value) -> Value {
-        match value {
-            Value::Node(id) => Value::Node(ssa_form::get_current_value(&mut self.context, *id)),
-            Value::Tuple(fields) => {
-                Value::Tuple(vecmap(fields, |value| self.get_current_value(value)))
-            }
-        }
-    }
-
-    pub(crate) fn get_object_type_from_abi(&self, el_type: &noirc_abi::AbiType) -> ObjectType {
-        match el_type {
-            noirc_abi::AbiType::Field => ObjectType::native_field(),
-            noirc_abi::AbiType::Integer { sign, width, .. } => match sign {
-                noirc_abi::Sign::Unsigned => ObjectType::unsigned_integer(*width),
-                noirc_abi::Sign::Signed => ObjectType::signed_integer(*width),
-            },
-            noirc_abi::AbiType::Boolean => ObjectType::boolean(),
-            noirc_abi::AbiType::Array { .. } => {
-                unreachable!("array of arrays are not supported for now")
-            }
-            noirc_abi::AbiType::Struct { .. } => {
-                unreachable!("array of structs are not supported for now")
-            }
-            noirc_abi::AbiType::String { .. } => {
-                unreachable!("array of strings are not supported for now")
-            }
-        }
-    }
-
-    pub(crate) fn abi_array(
-        &mut self,
-        name: &str,
-        ident_def: Option<Definition>,
-        el_type: &noirc_abi::AbiType,
-        len: u64,
-        witness: &[Witness],
-    ) -> NodeId {
-        let element_type = self.get_object_type_from_abi(el_type);
-        let (v_id, array_idx) = self.new_array(name, element_type, len as u32, ident_def);
-        let values = vecmap(witness.iter().enumerate(), |(i, w)| {
-            let mut var = Variable::new(
-                element_type,
-                format!("{name}_{i}"),
-                None,
-                self.context.current_block,
-            );
-            var.witness = Some(*w);
-            self.context.add_variable(var, None)
-        });
-        let mut stack_frame = crate::ssa::inline::StackFrame::new(self.context.current_block);
-        self.context.init_array_from_values(array_idx, values, &mut stack_frame);
-        let block = self.context.get_current_block_mut();
-        block.instructions.extend_from_slice(&stack_frame.stack);
-        block.update_variable(v_id, v_id);
-        v_id
-    }
-
-    pub(crate) fn abi_struct(
-        &mut self,
-        struct_name: &str,
-        ident_def: Option<Definition>,
-        fields: &[(String, noirc_abi::AbiType)],
-        witnesses: &BTreeMap<String, Vec<Witness>>,
-    ) -> Value {
-        let values = vecmap(fields, |(name, field_typ)| {
-            let new_name = format!("{struct_name}.{name}");
-            match field_typ {
-                noirc_abi::AbiType::Array { length, typ } => {
-                    let v_id = self.abi_array(&new_name, None, typ, *length, &witnesses[&new_name]);
-                    Value::Node(v_id)
-                }
-                noirc_abi::AbiType::Struct { fields, .. } => {
-                    let new_name = format!("{struct_name}.{name}");
-                    self.abi_struct(&new_name, None, fields, witnesses)
-                }
-                noirc_abi::AbiType::String { length } => {
-                    let typ =
-                        noirc_abi::AbiType::Integer { sign: noirc_abi::Sign::Unsigned, width: 8 };
-                    let v_id =
-                        self.abi_array(&new_name, None, &typ, *length, &witnesses[&new_name]);
-                    Value::Node(v_id)
-                }
-                _ => {
-                    let obj_type = self.get_object_type_from_abi(field_typ);
-                    let v_id = self.create_new_variable(
-                        new_name.clone(),
-                        None,
-                        obj_type,
-                        Some(witnesses[&new_name][0]),
-                    );
-                    Value::Node(v_id)
-                }
-            }
-        });
-        self.insert_new_struct(ident_def, values)
-    }
-
-    fn ssa_gen_identifier(&mut self, ident: &Ident) -> Result<Value, RuntimeError> {
-        // Check if we have already code-gen'd the definition of this variable
-        if let Some(value) = self.variable_values.get(&ident.definition) {
-            Ok(self.get_current_value(&value.clone()))
-        } else {
-            // If we haven't, it must be a global value, like a function or builtin
-            match &ident.definition {
-                Definition::Local(id) => unreachable!(
-                    "Local variable encountered before its definition was compiled: {:?}",
-                    id
-                ),
-                Definition::Function(id) => {
-                    let id = *id;
-                    if !self.context.function_already_compiled(id) {
-                        let index = self.context.get_function_index();
-                        self.create_function(id, index)?;
-                    }
-
-                    let expect_msg = "Expected called function to already be ssa_gen'd";
-                    let function_node_id = self.context.get_function_node_id(id).expect(expect_msg);
-                    Ok(Value::Node(function_node_id))
-                }
-                Definition::Builtin(opcode) | Definition::LowLevel(opcode) => {
-                    let opcode = builtin::Opcode::lookup(opcode).unwrap_or_else(|| {
-                        unreachable!("Unknown builtin/low level opcode '{}'", opcode)
-                    });
-                    let function_node_id = self.context.get_or_create_opcode_node_id(opcode);
-                    Ok(Value::Node(function_node_id))
-                }
-                Definition::Oracle(_) => unimplemented!("oracles not supported by deprecated SSA"),
-            }
-        }
-    }
-
-    fn ssa_gen_prefix_expression(
-        &mut self,
-        rhs: NodeId,
-        op: UnaryOp,
-    ) -> Result<NodeId, RuntimeError> {
-        let rhs_type = self.context.object_type(rhs);
-        match op {
-            UnaryOp::Minus => {
-                let lhs = self.context.zero_with_type(rhs_type);
-                let operator = BinaryOp::Sub { max_rhs_value: BigUint::zero() };
-                let op = Operation::Binary(node::Binary { operator, lhs, rhs, predicate: None });
-                self.context.new_instruction(op, rhs_type)
-            }
-            UnaryOp::Not => self.context.new_instruction(Operation::Not(rhs), rhs_type),
-            UnaryOp::MutableReference | UnaryOp::Dereference => {
-                unimplemented!("Mutable references are unimplemented in the old ssa backend")
-            }
-        }
-    }
-
-    fn ssa_gen_infix_expression(
-        &mut self,
-        lhs: NodeId,
-        rhs: NodeId,
-        op: BinaryOpKind,
-        location: Location,
-    ) -> Result<NodeId, RuntimeError> {
-        let lhs_type = self.context.object_type(lhs);
-        // Get the opcode from the infix operator
-        let opcode = Operation::Binary(Binary::from_ast(op, lhs_type, lhs, rhs, location));
-        let op_type = self.context.get_result_type(&opcode, lhs_type);
-        self.context.new_instruction(opcode, op_type)
-    }
-
-    fn ssa_gen_indexed_value(
-        &mut self,
-        array: &LValue,
-        index: &Expression,
-        location: Location,
-    ) -> Result<(NodeId, NodeId, Location), RuntimeError> {
-        let value = self.lvalue_to_value(array);
-        let lhs = value.unwrap_id();
-        let index = self.ssa_gen_expression(index)?.unwrap_id();
-        Ok((lhs, index, location))
-    }
-
-    fn lvalue_to_value(&self, lvalue: &LValue) -> &Value {
-        match lvalue {
-            LValue::Ident(ident) => self.find_variable(&ident.definition).unwrap(),
-            LValue::Index { array, .. } => {
-                self.find_variable(Self::lvalue_ident_def(array.as_ref())).unwrap()
-            }
-            LValue::MemberAccess { object, field_index, .. } => {
-                let ident_def = Self::lvalue_ident_def(object.as_ref());
-                let val = self.find_variable(ident_def).unwrap();
-                val.get_field_member(*field_index)
-            }
-            LValue::Dereference { .. } => {
-                unreachable!("Mutable references are unsupported in the old ssa backend")
-            }
-        }
-    }
-
-    fn lvalue_ident_def(lvalue: &LValue) -> &Definition {
-        match lvalue {
-            LValue::Ident(ident) => &ident.definition,
-            LValue::Index { array, .. } => Self::lvalue_ident_def(array.as_ref()),
-            LValue::MemberAccess { object, .. } => Self::lvalue_ident_def(object.as_ref()),
-            LValue::Dereference { reference, .. } => Self::lvalue_ident_def(reference.as_ref()),
-        }
-    }
-
-    pub(crate) fn create_new_variable(
-        &mut self,
-        var_name: String,
-        def: Option<Definition>,
-        obj_type: node::ObjectType,
-        witness: Option<acvm::acir::native_types::Witness>,
-    ) -> NodeId {
-        let new_var = node::Variable {
-            id: NodeId::dummy(),
-            obj_type,
-            name: var_name,
-            root: None,
-            def: def.clone(),
-            witness,
-            parent_block: self.context.current_block,
-        };
-        let v_id = self.context.add_variable(new_var, None);
-        let v_value = Value::Node(v_id);
-        if let Some(def) = def {
-            self.variable_values.insert(def, v_value);
-        }
-        v_id
-    }
-
-    //Helper function for create_new_value()
-    fn insert_new_struct(&mut self, def: Option<Definition>, values: Vec<Value>) -> Value {
-        let result = Value::Tuple(values);
-        if let Some(def_id) = def {
-            self.variable_values.insert(def_id, result.clone());
-        }
-        result
-    }
-
-    pub(crate) fn create_new_value(
-        &mut self,
-        typ: &Type,
-        base_name: &str,
-        def: Option<Definition>,
-    ) -> Value {
-        match typ {
-            Type::Tuple(fields) => {
-                let values = vecmap(fields.iter().enumerate(), |(i, field)| {
-                    let name = format!("{base_name}.{i}");
-                    self.create_new_value(field, &name, None)
-                });
-                self.insert_new_struct(def, values)
-            }
-            Type::Array(len, elem) => {
-                //TODO support array of structs
-                let obj_type = self.context.convert_type(elem);
-                let len = *len;
-                let (v_id, _) = self.new_array(base_name, obj_type, len.try_into().unwrap(), def);
-                Value::Node(v_id)
-            }
-            Type::String(len) => {
-                // Strings are a packed array of utf-8 encoded bytes
-                let obj_type = ObjectType::unsigned_integer(8);
-                let len = *len;
-                let (v_id, _) = self.new_array(base_name, obj_type, len.try_into().unwrap(), def);
-                Value::Node(v_id)
-            }
-            _ => {
-                let obj_type = self.context.convert_type(typ);
-                let v_id = self.create_new_variable(base_name.to_string(), def, obj_type, None);
-                self.context.get_current_block_mut().update_variable(v_id, v_id);
-                Value::Node(v_id)
-            }
-        }
-    }
-
-    pub(crate) fn new_array(
-        &mut self,
-        name: &str,
-        element_type: ObjectType,
-        len: u32,
-        def: Option<Definition>,
-    ) -> (NodeId, ArrayId) {
-        let (id, array_id) = self.context.new_array(name, element_type, len, def.clone());
-        if let Some(def) = def {
-            self.variable_values.insert(def, super::ssa_gen::Value::Node(id));
-        }
-        (id, array_id)
-    }
-
-    // Add a constraint to constrain two expression together
-    fn ssa_gen_constrain(
-        &mut self,
-        expr: &Expression,
-        location: noirc_errors::Location,
-    ) -> Result<Value, RuntimeError> {
-        let cond = self.ssa_gen_expression(expr)?.unwrap_id();
-        let operation = Operation::Constrain(cond, Some(location));
-        self.context.new_instruction(operation, ObjectType::NotAnObject)?;
-        Ok(Value::dummy())
-    }
-
-    /// Bind the given Definition to the given Value. This will flatten the Value as needed,
-    /// expanding each field of the value to a new variable.
-    fn bind_id(&mut self, id: LocalId, value: Value, name: &str) -> Result<(), RuntimeError> {
-        let definition = Definition::Local(id);
-        match value {
-            Value::Node(node_id) => {
-                let object_type = self.context.object_type(node_id);
-                let value = self.bind_variable(
-                    name.to_owned(),
-                    Some(definition.clone()),
-                    object_type,
-                    node_id,
-                )?;
-                self.variable_values.insert(definition, value);
-            }
-            value @ Value::Tuple(_) => {
-                let value = self.bind_fresh_pattern(name, value)?;
-                self.variable_values.insert(definition, value);
-            }
-        }
-        Ok(())
-    }
-
-    /// This function is a recursive helper for bind_pattern which takes care
-    /// of creating fresh variables to expand `ident = (a, b, ...)` to `(i_a, i_b, ...) = (a, b, ...)`
-    ///
-    /// This function could use a clearer name
-    fn bind_fresh_pattern(&mut self, basename: &str, value: Value) -> Result<Value, RuntimeError> {
-        match value {
-            Value::Node(node_id) => {
-                let object_type = self.context.object_type(node_id);
-                self.bind_variable(basename.to_owned(), None, object_type, node_id)
-            }
-            Value::Tuple(field_values) => {
-                let values = field_values
-                    .into_iter()
-                    .enumerate()
-                    .map(|(i, value)| {
-                        let name = format!("{basename}.{i}");
-                        self.bind_fresh_pattern(&name, value)
-                    })
-                    .collect::<Result<Vec<_>, _>>()?;
-
-                Ok(Value::Tuple(values))
-            }
-        }
-    }
-
-    fn bind_variable(
-        &mut self,
-        variable_name: String,
-        definition_id: Option<Definition>,
-        obj_type: node::ObjectType,
-        value_id: NodeId,
-    ) -> Result<Value, RuntimeError> {
-        let id = if let node::ObjectType::ArrayPointer(a) = obj_type {
-            let len = self.context.mem[a].len;
-            let el_type = self.context.mem[a].element_type;
-            self.context.new_array(&variable_name, el_type, len, definition_id).0
-        } else {
-            let new_var =
-                Variable::new(obj_type, variable_name, definition_id, self.context.current_block);
-            self.context.add_variable(new_var, None)
-        };
-        //Assign rhs to lhs
-        Ok(Value::Node(self.context.handle_assign(id, None, value_id, None)?))
-    }
-
-    //same as update_variable but using the var index instead of var
-    pub(crate) fn update_variable_id(
-        &mut self,
-        var_id: NodeId,
-        new_var: NodeId,
-        new_value: NodeId,
-    ) {
-        self.context.update_variable_id(var_id, new_var, new_value);
-    }
-
-    fn ssa_gen_assign(
-        &mut self,
-        lvalue: &LValue,
-        expression: &Expression,
-    ) -> Result<Value, RuntimeError> {
-        let ident_def = Self::lvalue_ident_def(lvalue);
-        let rhs = self.ssa_gen_expression(expression)?;
-
-        match lvalue {
-            LValue::Ident(_) => {
-                let lhs = self.find_variable(ident_def).unwrap();
-                // We may be able to avoid cloning here if we change find_variable
-                // and assign_pattern to use only fields of self instead of `self` itself.
-                let lhs = lhs.clone();
-                let result = self.assign_pattern(&lhs, rhs)?;
-                self.variable_values.insert(ident_def.clone(), result);
-            }
-            LValue::Index { array, index, location, .. } => {
-                let (lhs_id, array_idx, loc) =
-                    self.ssa_gen_indexed_value(array.as_ref(), index, *location)?;
-                let rhs_id = rhs.unwrap_id();
-                self.context.handle_assign(lhs_id, Some(array_idx), rhs_id, Some(loc))?;
-            }
-            LValue::MemberAccess { object: _, field_index } => {
-                // TODO: This is incorrect for nested structs
-                let val = self.find_variable(ident_def).unwrap();
-                let value = val.get_field_member(*field_index).clone();
-                self.assign_pattern(&value, rhs)?;
-            }
-            LValue::Dereference { .. } => {
-                unreachable!("Mutable references are unsupported in the old ssa backend")
-            }
-        }
-        Ok(Value::dummy())
-    }
-
-    /// Similar to bind_pattern but recursively creates Assignment instructions for
-    /// each value rather than defining new variables.
-    fn assign_pattern(&mut self, lhs: &Value, rhs: Value) -> Result<Value, RuntimeError> {
-        match (lhs, rhs) {
-            (Value::Node(lhs_id), Value::Node(rhs_id)) => {
-                Ok(Value::Node(self.context.handle_assign(*lhs_id, None, rhs_id, None)?))
-            }
-            (Value::Tuple(lhs_fields), Value::Tuple(rhs_fields)) => {
-                assert_eq!(lhs_fields.len(), rhs_fields.len());
-                let fields = lhs_fields.iter().zip(rhs_fields).map(|(lhs_field, rhs_field)| {
-                    self.assign_pattern(lhs_field, rhs_field)
-                }).collect::<Result<Vec<_>, _>>()?;
-
-                Ok(Value::Tuple(fields))
-            }
-            (Value::Node(_), Value::Tuple(_)) => unreachable!("variables with tuple/struct types should already be decomposed into multiple variables"),
-            (Value::Tuple(_), Value::Node(_)) => unreachable!("Uncaught type error, tried to assign a single value to a tuple/struct type"),
-        }
-    }
-
-    // Let statements are used to declare higher level objects
-    fn ssa_gen_let(&mut self, let_expr: &Let) -> Result<Value, RuntimeError> {
-        let rhs = self.ssa_gen_expression(&let_expr.expression)?;
-        self.bind_id(let_expr.id, rhs, &let_expr.name)?;
-        Ok(Value::dummy())
-    }
-
-    pub(crate) fn ssa_gen_expression(&mut self, expr: &Expression) -> Result<Value, RuntimeError> {
-        match expr {
-            Expression::Ident(ident) => self.ssa_gen_identifier(ident),
-            Expression::Binary(binary) => {
-                // Note: we disallow structs/tuples in infix expressions.
-                // The type checker currently disallows this as well but not if they come from a generic type
-                // We could allow some in the future, e.g. struct == struct
-                let lhs = self.ssa_gen_expression(&binary.lhs)?.to_node_ids();
-                let rhs = self.ssa_gen_expression(&binary.rhs)?.to_node_ids();
-                if lhs.len() != 1 || rhs.len() != 1 {
-                    return Err(RuntimeError {
-                        location: Some(binary.location),
-                        kind: RuntimeErrorKind::UnsupportedOp {
-                            op: binary.operator.to_string(),
-                            first_type: "struct/tuple".to_string(),
-                            second_type: "struct/tuple".to_string(),
-                        },
-                    });
-                }
-                Ok(Value::Node(self.ssa_gen_infix_expression(
-                    lhs[0],
-                    rhs[0],
-                    binary.operator,
-                    binary.location,
-                )?))
-            }
-            Expression::Cast(cast_expr) => {
-                let lhs = self.ssa_gen_expression(&cast_expr.lhs)?.unwrap_id();
-                let object_type = self.context.convert_type(&cast_expr.r#type);
-
-                Ok(Value::Node(self.context.new_instruction(Operation::Cast(lhs), object_type)?))
-            }
-            Expression::Index(indexed_expr) => {
-                // Evaluate the 'array' expression
-                let expr_node = self.ssa_gen_expression(&indexed_expr.collection)?.unwrap_id();
-                let array = match self.context.object_type(expr_node) {
-                    ObjectType::ArrayPointer(array_id) => &self.context.mem[array_id],
-                    other => unreachable!("Expected Pointer type, found {:?}", other),
-                };
-                let array_id = array.id;
-                let e_type = array.element_type;
-                // Evaluate the index expression
-                let index_as_obj = self.ssa_gen_expression(&indexed_expr.index)?.unwrap_id();
-                let load = Operation::Load {
-                    array_id,
-                    index: index_as_obj,
-                    location: Some(indexed_expr.location),
-                };
-                Ok(Value::Node(self.context.new_instruction(load, e_type)?))
-            }
-            Expression::Call(call_expr) => {
-                let results = self.call(call_expr)?;
-                Ok(Value::from_slice(&call_expr.return_type, &results))
-            }
-            Expression::For(for_expr) => self.ssa_gen_for(for_expr),
-            Expression::Tuple(fields) => self.ssa_gen_tuple(fields),
-            Expression::If(if_expr) => self.handle_if_expr(if_expr),
-            Expression::Unary(prefix) => {
-                let rhs = self.ssa_gen_expression(&prefix.rhs)?.unwrap_id();
-                self.ssa_gen_prefix_expression(rhs, prefix.operator).map(Value::Node)
-            }
-            Expression::Literal(l) => self.ssa_gen_literal(l),
-            Expression::Block(block) => self.ssa_gen_block(block),
-            Expression::ExtractTupleField(expr, field) => {
-                let tuple = self.ssa_gen_expression(expr.as_ref())?;
-                Ok(tuple.into_field_member(*field))
-            }
-            Expression::Let(let_expr) => self.ssa_gen_let(let_expr),
-            Expression::Constrain(expr, location) => {
-                self.ssa_gen_constrain(expr.as_ref(), *location)
-            }
-            Expression::Assign(assign) => {
-                self.ssa_gen_assign(&assign.lvalue, assign.expression.as_ref())
-            }
-            Expression::Semi(expr) => {
-                self.ssa_gen_expression(expr.as_ref())?;
-                Ok(Value::dummy())
-            }
-        }
-    }
-
-    fn ssa_gen_literal(&mut self, l: &Literal) -> Result<Value, RuntimeError> {
-        match l {
-            Literal::Integer(x, typ) => {
-                let typ = self.context.convert_type(typ);
-                Ok(Value::Node(self.context.get_or_create_const(*x, typ)))
-            }
-            Literal::Array(arr_lit) => {
-                let element_type = self.context.convert_type(&arr_lit.element_type);
-
-                let (new_var, array_id) =
-                    self.context.new_array("", element_type, arr_lit.contents.len() as u32, None);
-
-                let elements = self.ssa_gen_expression_list(&arr_lit.contents);
-                for (pos, object) in elements.into_iter().enumerate() {
-                    let lhs_adr = self.context.get_or_create_const(
-                        FieldElement::from((pos as u32) as u128),
-                        ObjectType::native_field(),
-                    );
-                    let store = Operation::Store {
-                        array_id,
-                        index: lhs_adr,
-                        value: object,
-                        predicate: None,
-                        location: None,
-                    };
-                    self.context.new_instruction(store, element_type)?;
-                }
-                Ok(Value::Node(new_var))
-            }
-            Literal::Str(string) => {
-                let string_as_integers = vecmap(string.bytes(), |byte| {
-                    let f = FieldElement::from_be_bytes_reduce(&[byte]);
-                    Expression::Literal(Literal::Integer(
-                        f,
-                        Type::Integer(noirc_frontend::Signedness::Unsigned, 8),
-                    ))
-                });
-
-                let string_arr_literal = ArrayLiteral {
-                    contents: string_as_integers,
-                    element_type: Type::Integer(noirc_frontend::Signedness::Unsigned, 8),
-                };
-
-                let new_value = self
-                    .ssa_gen_expression(&Expression::Literal(Literal::Array(string_arr_literal)))?;
-                Ok(new_value)
-            }
-            Literal::Bool(b) => {
-                if *b {
-                    Ok(Value::Node(self.context.one()))
-                } else {
-                    Ok(Value::Node(self.context.zero()))
-                }
-            }
-        }
-    }
-
-    /// A tuple is much the same as a constructor, we just give it fields with numbered names
-    fn ssa_gen_tuple(&mut self, fields: &[Expression]) -> Result<Value, RuntimeError> {
-        let fields = fields
-            .iter()
-            .map(|field| self.ssa_gen_expression(field))
-            .collect::<Result<Vec<_>, _>>()?;
-
-        Ok(Value::Tuple(fields))
-    }
-
-    pub(super) fn ssa_gen_expression_list(&mut self, exprs: &[Expression]) -> Vec<NodeId> {
-        let mut result = Vec::with_capacity(exprs.len());
-        for expr in exprs {
-            let value = self.ssa_gen_expression(expr);
-            result.extend(value.unwrap().to_node_ids());
-        }
-        result
-    }
-
-    fn ssa_gen_for(&mut self, for_expr: &For) -> Result<Value, RuntimeError> {
-        //we add the 'i = start' instruction (in the block before the join)
-        let start_idx = self.ssa_gen_expression(&for_expr.start_range).unwrap().unwrap_id();
-        let end_idx = self.ssa_gen_expression(&for_expr.end_range).unwrap().unwrap_id();
-
-        //We support only const range for now
-        let iter_def = Definition::Local(for_expr.index_variable);
-        let iter_type = self.context.convert_type(&for_expr.index_type);
-        let index_name = for_expr.index_name.clone();
-
-        let iter_id = self.create_new_variable(index_name, Some(iter_def), iter_type, None);
-        let iter_var = self.context.get_mut_variable(iter_id).unwrap();
-        iter_var.obj_type = iter_type;
-
-        let assign = Operation::binary(BinaryOp::Assign, iter_id, start_idx);
-        let iter_ass = self.context.new_instruction(assign, iter_type)?;
-
-        //We map the iterator to start_idx so that when we seal the join block, we will get the correct value.
-        self.update_variable_id(iter_id, iter_ass, start_idx);
-
-        //join block
-        let join_idx =
-            block::new_unsealed_block(&mut self.context, block::BlockType::ForJoin, true);
-        let exit_id = block::new_sealed_block(&mut self.context, block::BlockType::Normal, true);
-        self.context.current_block = join_idx;
-
-        //should parse a for_expr.condition statement that should evaluate to bool, but
-        //we only supports i=start;i!=end for now
-        //we generate the phi for the iterator because the iterator is manually created
-        let phi = self.context.generate_empty_phi(join_idx, iter_id);
-        self.update_variable_id(iter_id, iter_id, phi); //is it still needed?
-
-        let not_equal = Operation::binary(BinaryOp::Ne, phi, end_idx);
-        let cond = self.context.new_instruction(not_equal, ObjectType::boolean())?;
-
-        let to_fix = self.context.new_instruction(Operation::Nop, ObjectType::NotAnObject)?;
-
-        //Body
-        let body_id = block::new_sealed_block(&mut self.context, block::BlockType::Normal, true);
-        self.context.try_get_mut_instruction(to_fix).unwrap().operation =
-            Operation::Jeq(cond, body_id);
-
-        let body_block1 = &mut self.context[body_id];
-        body_block1.update_variable(iter_id, phi); //TODO try with just a get_current_value(iter)
-
-        self.ssa_gen_expression(for_expr.block.as_ref())?;
-
-        //increment iter
-        let one = self.context.get_or_create_const(FieldElement::one(), iter_type);
-
-        let incr_op = Operation::binary(BinaryOp::Add, phi, one);
-        let incr = self.context.new_instruction(incr_op, iter_type)?;
-
-        let cur_block_id = self.context.current_block; //It should be the body block, except if the body has CFG statements
-        let cur_block = &mut self.context[cur_block_id];
-        cur_block.update_variable(iter_id, incr);
-
-        //body.left = join
-        cur_block.left = Some(join_idx);
-        let join_mut = &mut self.context[join_idx];
-        join_mut.predecessor.push(cur_block_id);
-
-        //jump back to join
-        self.context.new_instruction(Operation::Jmp(join_idx), ObjectType::NotAnObject)?;
-
-        //exit block
-        self.context.current_block = exit_id;
-        let exit_first = self.context.get_current_block().get_first_instruction();
-        block::link_with_target(&mut self.context, join_idx, Some(exit_id), Some(body_id));
-
-        //seal join
-        ssa_form::seal_block(&mut self.context, join_idx, join_idx);
-
-        Ok(Value::Node(exit_first))
-    }
-
-    //Parse a block of AST statements into ssa form
-    fn ssa_gen_block(&mut self, block: &[Expression]) -> Result<Value, RuntimeError> {
-        let mut last_value = Value::dummy();
-        for expr in block {
-            last_value = self.ssa_gen_expression(expr)?;
-        }
-        Ok(last_value)
-    }
-
-    fn handle_if_expr(&mut self, if_expr: &If) -> Result<Value, RuntimeError> {
-        //jump instruction
-        let mut entry_block = self.context.current_block;
-        if self.context[entry_block].kind != BlockType::Normal {
-            entry_block =
-                block::new_sealed_block(&mut self.context, block::BlockType::Normal, true);
-        }
-
-        let condition = self.ssa_gen_expression(if_expr.condition.as_ref())?.unwrap_id();
-
-        if let Some(cond) = node::NodeEval::from_id(&self.context, condition).into_const_value() {
-            if cond.is_zero() {
-                if let Some(alt) = &if_expr.alternative {
-                    return self.ssa_gen_expression(alt);
-                } else {
-                    return Ok(Value::dummy());
-                }
-            } else {
-                return self.ssa_gen_expression(if_expr.consequence.as_ref());
-            }
-        }
-
-        let jump_op = Operation::Jeq(condition, block::BlockId::dummy());
-        let jump_ins = self.context.new_instruction(jump_op, ObjectType::NotAnObject).unwrap();
-
-        //Then block
-        block::new_sealed_block(&mut self.context, block::BlockType::Normal, true);
-
-        let v1 = self.ssa_gen_expression(if_expr.consequence.as_ref())?;
-
-        //Exit block
-        let exit_block =
-            block::new_unsealed_block(&mut self.context, block::BlockType::IfJoin, true);
-        self.context[exit_block].dominator = Some(entry_block);
-
-        //Else block
-        self.context.current_block = entry_block;
-        let block2 = block::new_sealed_block(&mut self.context, block::BlockType::Normal, false);
-        self.context[entry_block].right = Some(block2);
-
-        //Fixup the jump
-        if let node::Instruction { operation: Operation::Jeq(_, target), .. } =
-            self.context.instruction_mut(jump_ins)
-        {
-            *target = block2;
-        }
-
-        let mut v2 = Value::dummy();
-        if let Some(alt) = if_expr.alternative.as_ref() {
-            v2 = self.ssa_gen_expression(alt)?;
-        }
-
-        //Connect with the exit block
-        self.context.get_current_block_mut().left = Some(exit_block);
-
-        //Exit block plumbing
-        let block2 = self.context.current_block;
-        self.context.current_block = exit_block;
-        self.context.get_current_block_mut().predecessor.push(block2);
-        ssa_form::seal_block(&mut self.context, exit_block, entry_block);
-
-        // return value:
-        let mut counter = 0;
-        let mut phi = |a, b| self.context.new_phi(a, b, &mut counter);
-        Ok(v1.zip(&v2, &mut phi))
-    }
-}
diff --git a/crates/noirc_evaluator/src/ssa/value.rs b/crates/noirc_evaluator/src/ssa/value.rs
deleted file mode 100644
index 35e5f9f12de..00000000000
--- a/crates/noirc_evaluator/src/ssa/value.rs
+++ /dev/null
@@ -1,115 +0,0 @@
-use crate::ssa::node::NodeId;
-use iter_extended::vecmap;
-use noirc_frontend::monomorphization::ast::Type;
-
-/// `Value` is used only to construct the SSA IR.
-#[derive(Debug, Clone)]
-pub(crate) enum Value {
-    Node(NodeId),
-    Tuple(Vec<Value>),
-}
-
-impl Value {
-    /// Returns a single NodeId.
-    /// Panics: If `Value` holds multiple Values
-    pub(crate) fn unwrap_id(&self) -> NodeId {
-        match self {
-            Value::Node(id) => *id,
-            Value::Tuple(_) => panic!("Tried to unwrap a struct/tuple into a NodeId"),
-        }
-    }
-
-    /// Returns a placeholder NodeId that can
-    /// be used to represent the absence of a value.
-    pub(crate) fn dummy() -> Value {
-        Value::Node(NodeId::dummy())
-    }
-
-    /// Checks if the `Value` corresponds to
-    /// `Option::None` or no value.
-    pub(crate) fn is_dummy(&self) -> bool {
-        match self {
-            Value::Node(id) => *id == NodeId::dummy(),
-            _ => false,
-        }
-    }
-
-    /// Converts `Value` into a vector of NodeId's
-    pub(crate) fn to_node_ids(&self) -> Vec<NodeId> {
-        match self {
-            Value::Node(id) => vec![*id],
-            Value::Tuple(v) => v.iter().flat_map(|i| i.to_node_ids()).collect(),
-        }
-    }
-
-    /// Calls the function `f` on `self` and the given `Value`
-    /// Panics: If `self` and the given value are not the same
-    /// enum variant
-    pub(crate) fn zip<F>(&self, rhs_value: &Value, f: &mut F) -> Value
-    where
-        F: FnMut(NodeId, NodeId) -> NodeId,
-    {
-        if self.is_dummy() || rhs_value.is_dummy() {
-            return Value::dummy();
-        }
-
-        match (self, rhs_value) {
-            (Value::Node(lhs), Value::Node(rhs)) => Value::Node(f(*lhs, *rhs)),
-            (Value::Tuple(lhs), Value::Tuple(rhs)) => {
-                Value::Tuple(vecmap(lhs.iter().zip(rhs), |(lhs_value, rhs_value)| {
-                    lhs_value.zip(rhs_value, f)
-                }))
-            }
-            _ => {
-                unreachable!("ICE: expected both `Value` instances to be of the same enum variant")
-            }
-        }
-    }
-
-    /// Returns the `Value` at position `field_index` in the
-    /// Tuple Variant.
-    /// Panics: If the `self` is not the `Tuple` Variant.
-    pub(crate) fn into_field_member(self, field_index: usize) -> Value {
-        match self {
-            Value::Node(_) => {
-                unreachable!("Runtime type error, expected struct/tuple but found a NodeId")
-            }
-            Value::Tuple(mut fields) => fields.remove(field_index),
-        }
-    }
-    pub(crate) fn get_field_member(&self, field_index: usize) -> &Value {
-        match self {
-            Value::Node(_) => {
-                unreachable!("Runtime type error, expected struct but found a NodeId")
-            }
-            Value::Tuple(fields) => &fields[field_index],
-        }
-    }
-
-    /// Reconstruct a `Value` instance whose type is `value_type`
-    fn reshape(value_type: &Type, iter: &mut core::slice::Iter<NodeId>) -> Value {
-        match value_type {
-            Type::Tuple(tup) => {
-                let values = vecmap(tup, |v| Self::reshape(v, iter));
-                Value::Tuple(values)
-            }
-            Type::Unit
-            | Type::Function(..)
-            | Type::Array(..)
-            | Type::Slice(..)
-            | Type::String(..)
-            | Type::Integer(..)
-            | Type::Bool
-            | Type::Field
-            | Type::MutableReference(_) => Value::Node(*iter.next().unwrap()),
-        }
-    }
-
-    /// Reconstruct a `Value` instance from a slice of NodeId's
-    pub(crate) fn from_slice(value_type: &Type, slice: &[NodeId]) -> Value {
-        let mut iter = slice.iter();
-        let result = Value::reshape(value_type, &mut iter);
-        assert!(iter.next().is_none());
-        result
-    }
-}
diff --git a/crates/noirc_evaluator/src/ssa_refactor.rs b/crates/noirc_evaluator/src/ssa_refactor.rs
index 29a718b590e..6326b45554d 100644
--- a/crates/noirc_evaluator/src/ssa_refactor.rs
+++ b/crates/noirc_evaluator/src/ssa_refactor.rs
@@ -7,8 +7,13 @@
 //! This module heavily borrows from Cranelift
 #![allow(dead_code)]
 
+use std::collections::BTreeSet;
+
 use crate::errors::RuntimeError;
-use acvm::acir::circuit::{Circuit, PublicInputs};
+use acvm::acir::{
+    circuit::{Circuit, PublicInputs},
+    native_types::Witness,
+};
 
 use noirc_errors::debug_info::DebugInfo;
 
@@ -32,6 +37,7 @@ pub(crate) fn optimize_into_acir(
     program: Program,
     allow_log_ops: bool,
     print_ssa_passes: bool,
+    print_brillig_trace: bool,
 ) -> Result<GeneratedAcir, RuntimeError> {
     let abi_distinctness = program.return_distinctness;
     let mut ssa = ssa_gen::generate_ssa(program)
@@ -39,7 +45,7 @@ pub(crate) fn optimize_into_acir(
         .defunctionalize()
         .print(print_ssa_passes, "After Defunctionalization:");
 
-    let brillig = ssa.to_brillig();
+    let brillig = ssa.to_brillig(print_brillig_trace);
     if let RuntimeType::Acir = ssa.main().runtime() {
         ssa = ssa
             .inline_functions()
@@ -64,23 +70,41 @@ pub(crate) fn optimize_into_acir(
 /// This is analogous to `ssa:create_circuit` and this method is called when one wants
 /// to use the new ssa module to process Noir code.
 // TODO: This no longer needs to return a result, but it is kept to match the signature of `create_circuit`
-pub fn experimental_create_circuit(
+pub fn create_circuit(
     program: Program,
-    enable_logging: bool,
+    enable_ssa_logging: bool,
+    enable_brillig_logging: bool,
     show_output: bool,
 ) -> Result<(Circuit, DebugInfo, Abi), RuntimeError> {
     let func_sig = program.main_function_signature.clone();
-    let GeneratedAcir { current_witness_index, opcodes, return_witnesses, locations, .. } =
-        optimize_into_acir(program, show_output, enable_logging)?;
+    let GeneratedAcir {
+        current_witness_index,
+        opcodes,
+        return_witnesses,
+        locations,
+        input_witnesses,
+        ..
+    } = optimize_into_acir(program, show_output, enable_ssa_logging, enable_brillig_logging)?;
 
-    let abi = gen_abi(func_sig, return_witnesses.clone());
+    let abi = gen_abi(func_sig, &input_witnesses, return_witnesses.clone());
     let public_abi = abi.clone().public_abi();
 
     let public_parameters =
         PublicInputs(public_abi.param_witnesses.values().flatten().copied().collect());
+
+    let all_parameters: BTreeSet<Witness> =
+        abi.param_witnesses.values().flatten().copied().collect();
+    let private_parameters = all_parameters.difference(&public_parameters.0).copied().collect();
+
     let return_values = PublicInputs(return_witnesses.into_iter().collect());
 
-    let circuit = Circuit { current_witness_index, opcodes, public_parameters, return_values };
+    let circuit = Circuit {
+        current_witness_index,
+        opcodes,
+        private_parameters,
+        public_parameters,
+        return_values,
+    };
     let debug_info = DebugInfo::new(locations);
 
     Ok((circuit, debug_info, abi))
diff --git a/crates/noirc_evaluator/src/ssa_refactor/abi_gen/mod.rs b/crates/noirc_evaluator/src/ssa_refactor/abi_gen/mod.rs
index db39b1c8110..778d8aba8d5 100644
--- a/crates/noirc_evaluator/src/ssa_refactor/abi_gen/mod.rs
+++ b/crates/noirc_evaluator/src/ssa_refactor/abi_gen/mod.rs
@@ -1,14 +1,18 @@
 use std::collections::BTreeMap;
 
 use acvm::acir::native_types::Witness;
-use iter_extended::{btree_map, vecmap};
+use iter_extended::btree_map;
 use noirc_abi::{Abi, AbiParameter, FunctionSignature};
 
 /// Arranges a function signature and a generated circuit's return witnesses into a
 /// `noirc_abi::Abi`.
-pub(crate) fn gen_abi(func_sig: FunctionSignature, return_witnesses: Vec<Witness>) -> Abi {
+pub(crate) fn gen_abi(
+    func_sig: FunctionSignature,
+    input_witnesses: &[Witness],
+    return_witnesses: Vec<Witness>,
+) -> Abi {
     let (parameters, return_type) = func_sig;
-    let param_witnesses = param_witnesses_from_abi_param(&parameters);
+    let param_witnesses = param_witnesses_from_abi_param(&parameters, input_witnesses);
     Abi { parameters, return_type, param_witnesses, return_witnesses }
 }
 
@@ -16,14 +20,17 @@ pub(crate) fn gen_abi(func_sig: FunctionSignature, return_witnesses: Vec<Witness
 // parameter's constituent values live.
 fn param_witnesses_from_abi_param(
     abi_params: &Vec<AbiParameter>,
+    input_witnesses: &[Witness],
 ) -> BTreeMap<String, Vec<Witness>> {
-    let mut offset = 1;
+    let mut idx = 0_usize;
+
     btree_map(abi_params, |param| {
         let num_field_elements_needed = param.typ.field_count();
-        let idx_start = offset;
-        let idx_end = idx_start + num_field_elements_needed;
-        let witnesses = vecmap(idx_start..idx_end, Witness);
-        offset += num_field_elements_needed;
-        (param.name.clone(), witnesses)
+        let mut wit = Vec::new();
+        for _ in 0..num_field_elements_needed {
+            wit.push(input_witnesses[idx]);
+            idx += 1;
+        }
+        (param.name.clone(), wit)
     })
 }
diff --git a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir.rs b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir.rs
index 6e715002161..96800b22ad0 100644
--- a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir.rs
+++ b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir.rs
@@ -1,4 +1,3 @@
 pub(crate) mod acir_variable;
-pub(crate) mod errors;
 pub(crate) mod generated_acir;
 pub(crate) mod sort;
diff --git a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/acir_variable.rs b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/acir_variable.rs
index a1fb66ab749..25d92ed8b85 100644
--- a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/acir_variable.rs
+++ b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/acir_variable.rs
@@ -1,13 +1,15 @@
-use super::{errors::AcirGenError, generated_acir::GeneratedAcir};
+use super::generated_acir::GeneratedAcir;
 use crate::brillig::brillig_gen::brillig_directive;
-use crate::ssa_refactor::acir_gen::AcirValue;
+use crate::errors::{InternalError, RuntimeError};
+use crate::ssa_refactor::acir_gen::{AcirDynamicArray, AcirValue};
 use crate::ssa_refactor::ir::types::Type as SsaType;
 use crate::ssa_refactor::ir::{instruction::Endian, types::NumericType};
+use acvm::acir::circuit::opcodes::{BlockId, MemOp};
+use acvm::acir::circuit::Opcode;
 use acvm::acir::{
     brillig::Opcode as BrilligOpcode,
     circuit::brillig::{BrilligInputs, BrilligOutputs},
 };
-
 use acvm::{
     acir::{
         circuit::opcodes::FunctionInput,
@@ -16,7 +18,7 @@ use acvm::{
     },
     FieldElement,
 };
-use iter_extended::vecmap;
+use iter_extended::{try_vecmap, vecmap};
 use noirc_errors::Location;
 use std::collections::HashMap;
 use std::{borrow::Cow, hash::Hash};
@@ -53,6 +55,11 @@ impl AcirType {
         }
     }
 
+    /// Returns a field type
+    pub(crate) fn field() -> Self {
+        AcirType::NumericType(NumericType::NativeField)
+    }
+
     /// Returns a boolean type
     fn boolean() -> Self {
         AcirType::NumericType(NumericType::Unsigned { bit_size: 1 })
@@ -108,6 +115,26 @@ pub(crate) struct AcirContext {
 }
 
 impl AcirContext {
+    pub(crate) fn current_witness_index(&self) -> Witness {
+        self.acir_ir.current_witness_index()
+    }
+
+    pub(crate) fn extract_witness(&self, inputs: &[AcirValue]) -> Vec<u32> {
+        inputs
+            .iter()
+            .flat_map(|value| value.clone().flatten())
+            .map(|value| {
+                self.vars
+                    .get(&value.0)
+                    .expect("ICE: undeclared AcirVar")
+                    .to_expression()
+                    .to_witness()
+                    .expect("ICE - cannot extract a witness")
+                    .0
+            })
+            .collect()
+    }
+
     /// Adds a constant to the context and assigns a Variable to represent it
     pub(crate) fn add_constant(&mut self, constant: FieldElement) -> AcirVar {
         let constant_data = AcirVarData::Const(constant);
@@ -156,7 +183,11 @@ impl AcirContext {
 
     /// Adds a new Variable to context whose value will
     /// be constrained to be the inverse of `var`.
-    pub(crate) fn inv_var(&mut self, var: AcirVar) -> Result<AcirVar, AcirGenError> {
+    pub(crate) fn inv_var(
+        &mut self,
+        var: AcirVar,
+        predicate: AcirVar,
+    ) -> Result<AcirVar, RuntimeError> {
         let var_data = &self.vars[&var];
         if let AcirVarData::Const(constant) = var_data {
             // Note that this will return a 0 if the inverse is not available
@@ -169,23 +200,36 @@ impl AcirContext {
         let field_type = AcirType::NumericType(NumericType::NativeField);
 
         let results = self.brillig(
-            None,
+            predicate,
             inverse_code,
             vec![AcirValue::Var(var, field_type.clone())],
             vec![field_type],
-        );
+        )?;
         let inverted_var = Self::expect_one_var(results);
 
         let should_be_one = self.mul_var(inverted_var, var)?;
-        self.assert_eq_one(should_be_one)?;
+        self.maybe_eq_predicate(should_be_one, predicate)?;
 
         Ok(inverted_var)
     }
 
-    /// Constrains the lhs to be equal to the constant value `1`
-    pub(crate) fn assert_eq_one(&mut self, var: AcirVar) -> Result<(), AcirGenError> {
-        let one_var = self.add_constant(FieldElement::one());
-        self.assert_eq_var(var, one_var)
+    // Constrains `var` to be equal to the constant value `1`
+    pub(crate) fn assert_eq_one(&mut self, var: AcirVar) -> Result<(), RuntimeError> {
+        let one = self.add_constant(FieldElement::one());
+        self.assert_eq_var(var, one)
+    }
+
+    // Constrains `var` to be equal to predicate if the predicate is true
+    // or to be equal to 0 if the predicate is false.
+    //
+    // Since we multiply `var` by the predicate, this is a no-op if the predicate is false
+    pub(crate) fn maybe_eq_predicate(
+        &mut self,
+        var: AcirVar,
+        predicate: AcirVar,
+    ) -> Result<(), RuntimeError> {
+        let pred_mul_var = self.mul_var(var, predicate)?;
+        self.assert_eq_var(pred_mul_var, predicate)
     }
 
     // Returns the variable from the results, assuming it is the only result
@@ -193,13 +237,15 @@ impl AcirContext {
         assert_eq!(results.len(), 1);
         match results[0] {
             AcirValue::Var(var, _) => var,
-            AcirValue::Array(_) => unreachable!("ICE - expected a variable"),
+            AcirValue::DynamicArray(_) | AcirValue::Array(_) => {
+                unreachable!("ICE - expected a variable")
+            }
         }
     }
 
     /// Returns an `AcirVar` that is `1` if `lhs` equals `rhs` and
     /// 0 otherwise.
-    pub(crate) fn eq_var(&mut self, lhs: AcirVar, rhs: AcirVar) -> Result<AcirVar, AcirGenError> {
+    pub(crate) fn eq_var(&mut self, lhs: AcirVar, rhs: AcirVar) -> Result<AcirVar, RuntimeError> {
         let lhs_data = &self.vars[&lhs];
         let rhs_data = &self.vars[&rhs];
 
@@ -217,7 +263,7 @@ impl AcirContext {
         lhs: AcirVar,
         rhs: AcirVar,
         typ: AcirType,
-    ) -> Result<AcirVar, AcirGenError> {
+    ) -> Result<AcirVar, RuntimeError> {
         let inputs = vec![AcirValue::Var(lhs, typ.clone()), AcirValue::Var(rhs, typ)];
         let outputs = self.black_box_function(BlackBoxFunc::XOR, inputs)?;
         Ok(outputs[0])
@@ -229,7 +275,7 @@ impl AcirContext {
         lhs: AcirVar,
         rhs: AcirVar,
         typ: AcirType,
-    ) -> Result<AcirVar, AcirGenError> {
+    ) -> Result<AcirVar, RuntimeError> {
         let inputs = vec![AcirValue::Var(lhs, typ.clone()), AcirValue::Var(rhs, typ)];
         let outputs = self.black_box_function(BlackBoxFunc::AND, inputs)?;
         Ok(outputs[0])
@@ -241,7 +287,7 @@ impl AcirContext {
         lhs: AcirVar,
         rhs: AcirVar,
         typ: AcirType,
-    ) -> Result<AcirVar, AcirGenError> {
+    ) -> Result<AcirVar, RuntimeError> {
         let bit_size = typ.bit_size();
         if bit_size == 1 {
             // Operands are booleans
@@ -264,7 +310,7 @@ impl AcirContext {
     }
 
     /// Constrains the `lhs` and `rhs` to be equal.
-    pub(crate) fn assert_eq_var(&mut self, lhs: AcirVar, rhs: AcirVar) -> Result<(), AcirGenError> {
+    pub(crate) fn assert_eq_var(&mut self, lhs: AcirVar, rhs: AcirVar) -> Result<(), RuntimeError> {
         // TODO: could use sub_var and then assert_eq_zero
         let lhs_data = &self.vars[&lhs];
         let rhs_data = &self.vars[&rhs];
@@ -275,7 +321,7 @@ impl AcirContext {
                 Ok(())
             } else {
                 // Constraint is always false - this program is unprovable
-                Err(AcirGenError::BadConstantEquality {
+                Err(RuntimeError::FailedConstraint {
                     lhs: *lhs_const,
                     rhs: *rhs_const,
                     location: self.get_location(),
@@ -296,7 +342,8 @@ impl AcirContext {
         lhs: AcirVar,
         rhs: AcirVar,
         typ: AcirType,
-    ) -> Result<AcirVar, AcirGenError> {
+        predicate: AcirVar,
+    ) -> Result<AcirVar, RuntimeError> {
         let numeric_type = match typ {
             AcirType::NumericType(numeric_type) => numeric_type,
             AcirType::Array(_, _) => {
@@ -305,12 +352,12 @@ impl AcirContext {
         };
         match numeric_type {
             NumericType::NativeField => {
-                let inv_rhs = self.inv_var(rhs)?;
+                let inv_rhs = self.inv_var(rhs, predicate)?;
                 self.mul_var(lhs, inv_rhs)
             }
             NumericType::Unsigned { bit_size } => {
                 let (quotient_var, _remainder_var) =
-                    self.euclidean_division_var(lhs, rhs, bit_size)?;
+                    self.euclidean_division_var(lhs, rhs, bit_size, predicate)?;
                 Ok(quotient_var)
             }
             NumericType::Signed { bit_size } => {
@@ -323,7 +370,7 @@ impl AcirContext {
 
     /// Adds a new Variable to context whose value will
     /// be constrained to be the multiplication of `lhs` and `rhs`
-    pub(crate) fn mul_var(&mut self, lhs: AcirVar, rhs: AcirVar) -> Result<AcirVar, AcirGenError> {
+    pub(crate) fn mul_var(&mut self, lhs: AcirVar, rhs: AcirVar) -> Result<AcirVar, RuntimeError> {
         let lhs_data = &self.vars[&lhs];
         let rhs_data = &self.vars[&rhs];
         let result = match (lhs_data, rhs_data) {
@@ -370,14 +417,14 @@ impl AcirContext {
 
     /// Adds a new Variable to context whose value will
     /// be constrained to be the subtraction of `lhs` and `rhs`
-    pub(crate) fn sub_var(&mut self, lhs: AcirVar, rhs: AcirVar) -> Result<AcirVar, AcirGenError> {
+    pub(crate) fn sub_var(&mut self, lhs: AcirVar, rhs: AcirVar) -> Result<AcirVar, RuntimeError> {
         let neg_rhs = self.neg_var(rhs);
         self.add_var(lhs, neg_rhs)
     }
 
     /// Adds a new Variable to context whose value will
     /// be constrained to be the addition of `lhs` and `rhs`
-    pub(crate) fn add_var(&mut self, lhs: AcirVar, rhs: AcirVar) -> Result<AcirVar, AcirGenError> {
+    pub(crate) fn add_var(&mut self, lhs: AcirVar, rhs: AcirVar) -> Result<AcirVar, RuntimeError> {
         let lhs_data = &self.vars[&lhs];
         let rhs_data = &self.vars[&rhs];
         let result_data = if let (AcirVarData::Const(lhs_const), AcirVarData::Const(rhs_const)) =
@@ -392,7 +439,7 @@ impl AcirContext {
     }
 
     /// Adds a new variable that is constrained to be the logical NOT of `x`.
-    pub(crate) fn not_var(&mut self, x: AcirVar, typ: AcirType) -> Result<AcirVar, AcirGenError> {
+    pub(crate) fn not_var(&mut self, x: AcirVar, typ: AcirType) -> Result<AcirVar, RuntimeError> {
         let bit_size = typ.bit_size();
         // Subtracting from max flips the bits
         let max = self.add_constant(FieldElement::from((1_u128 << bit_size) - 1));
@@ -411,7 +458,7 @@ impl AcirContext {
         lhs: AcirVar,
         rhs: AcirVar,
         _typ: AcirType,
-    ) -> Result<AcirVar, AcirGenError> {
+    ) -> Result<AcirVar, RuntimeError> {
         let rhs_data = &self.vars[&rhs];
 
         // Compute 2^{rhs}
@@ -430,17 +477,18 @@ impl AcirContext {
         lhs: AcirVar,
         rhs: AcirVar,
         bit_size: u32,
-    ) -> Result<(AcirVar, AcirVar), AcirGenError> {
-        let predicate = Expression::one();
-
+        predicate: AcirVar,
+    ) -> Result<(AcirVar, AcirVar), RuntimeError> {
         let lhs_data = &self.vars[&lhs];
         let rhs_data = &self.vars[&rhs];
+        let predicate_data = &self.vars[&predicate];
 
         let lhs_expr = lhs_data.to_expression();
         let rhs_expr = rhs_data.to_expression();
+        let predicate_expr = predicate_data.to_expression();
 
         let (quotient, remainder) =
-            self.acir_ir.euclidean_division(&lhs_expr, &rhs_expr, bit_size, &predicate)?;
+            self.acir_ir.euclidean_division(&lhs_expr, &rhs_expr, bit_size, &predicate_expr)?;
 
         let quotient_var = self.add_data(AcirVarData::Witness(quotient));
         let remainder_var = self.add_data(AcirVarData::Witness(remainder));
@@ -462,7 +510,7 @@ impl AcirContext {
         lhs: AcirVar,
         rhs: AcirVar,
         bit_size: u32,
-    ) -> Result<(AcirVar, AcirVar), AcirGenError> {
+    ) -> Result<(AcirVar, AcirVar), RuntimeError> {
         let lhs_data = &self.vars[&lhs].clone();
         let rhs_data = &self.vars[&rhs].clone();
 
@@ -485,8 +533,9 @@ impl AcirContext {
         lhs: AcirVar,
         rhs: AcirVar,
         bit_size: u32,
-    ) -> Result<AcirVar, AcirGenError> {
-        let (_, remainder) = self.euclidean_division_var(lhs, rhs, bit_size)?;
+        predicate: AcirVar,
+    ) -> Result<AcirVar, RuntimeError> {
+        let (_, remainder) = self.euclidean_division_var(lhs, rhs, bit_size, predicate)?;
         Ok(remainder)
     }
 
@@ -505,7 +554,8 @@ impl AcirContext {
         lhs: AcirVar,
         rhs: AcirVar,
         typ: AcirType,
-    ) -> Result<AcirVar, AcirGenError> {
+        predicate: AcirVar,
+    ) -> Result<AcirVar, RuntimeError> {
         let rhs_data = &self.vars[&rhs];
 
         // Compute 2^{rhs}
@@ -515,13 +565,16 @@ impl AcirContext {
         };
         let two_pow_rhs_var = self.add_constant(two_pow_rhs);
 
-        self.div_var(lhs, two_pow_rhs_var, typ)
+        self.div_var(lhs, two_pow_rhs_var, typ, predicate)
     }
 
     /// Converts the `AcirVar` to a `Witness` if it hasn't been already, and appends it to the
     /// `GeneratedAcir`'s return witnesses.
-    pub(crate) fn return_var(&mut self, acir_var: AcirVar) {
-        let acir_var_data = self.vars.get(&acir_var).expect("ICE: return of undeclared AcirVar");
+    pub(crate) fn return_var(&mut self, acir_var: AcirVar) -> Result<(), InternalError> {
+        let acir_var_data = match self.vars.get(&acir_var) {
+            Some(acir_var_data) => acir_var_data,
+            None => return Err(InternalError::UndeclaredAcirVar { location: self.get_location() }),
+        };
         // TODO: Add caching to prevent expressions from being needlessly duplicated
         let witness = match acir_var_data {
             AcirVarData::Const(constant) => {
@@ -531,6 +584,7 @@ impl AcirContext {
             AcirVarData::Witness(witness) => *witness,
         };
         self.acir_ir.push_return_witness(witness);
+        Ok(())
     }
 
     /// Constrains the `AcirVar` variable to be of type `NumericType`.
@@ -538,7 +592,7 @@ impl AcirContext {
         &mut self,
         variable: AcirVar,
         numeric_type: &NumericType,
-    ) -> Result<AcirVar, AcirGenError> {
+    ) -> Result<AcirVar, RuntimeError> {
         let data = &self.vars[&variable];
         match numeric_type {
             NumericType::Signed { bit_size } | NumericType::Unsigned { bit_size } => {
@@ -554,18 +608,28 @@ impl AcirContext {
     }
 
     /// Returns an `AcirVar` which will be constrained to be lhs mod 2^{rhs}
+    /// In order to do this, we simply perform euclidian division of lhs by 2^{rhs}
+    /// The remainder of the division is then lhs mod 2^{rhs}
     pub(crate) fn truncate_var(
         &mut self,
         lhs: AcirVar,
         rhs: u32,
         max_bit_size: u32,
-    ) -> Result<AcirVar, AcirGenError> {
+    ) -> Result<AcirVar, RuntimeError> {
         let lhs_data = &self.vars[&lhs];
         let lhs_expr = lhs_data.to_expression();
 
-        let result_expr = self.acir_ir.truncate(&lhs_expr, rhs, max_bit_size)?;
-
-        Ok(self.add_data(AcirVarData::Expr(result_expr)))
+        // 2^{rhs}
+        let divisor = FieldElement::from(2_i128).pow(&FieldElement::from(rhs as i128));
+        // Computes lhs = 2^{rhs} * q + r
+        let (_, remainder) = self.acir_ir.euclidean_division(
+            &lhs_expr,
+            &Expression::from_field(divisor),
+            max_bit_size,
+            &Expression::one(),
+        )?;
+
+        Ok(self.add_data(AcirVarData::Expr(Expression::from(remainder))))
     }
 
     /// Returns an `AcirVar` which will be `1` if lhs >= rhs
@@ -575,8 +639,8 @@ impl AcirContext {
         lhs: AcirVar,
         rhs: AcirVar,
         bit_size: u32,
-        predicate: Option<AcirVar>,
-    ) -> Result<AcirVar, AcirGenError> {
+        predicate: AcirVar,
+    ) -> Result<AcirVar, RuntimeError> {
         let lhs_data = &self.vars[&lhs];
         let rhs_data = &self.vars[&rhs];
 
@@ -586,10 +650,9 @@ impl AcirContext {
         // TODO: check what happens when we do (a as u8) >= (b as u32)
         // TODO: The frontend should shout in this case
 
-        let predicate = predicate.map(|acir_var| {
-            let predicate_data = &self.vars[&acir_var];
-            predicate_data.to_expression().into_owned()
-        });
+        let predicate_data = &self.vars[&predicate];
+        let predicate = predicate_data.to_expression().into_owned();
+
         let is_greater_than_eq =
             self.acir_ir.more_than_eq_comparison(&lhs_expr, &rhs_expr, bit_size, predicate)?;
 
@@ -604,10 +667,10 @@ impl AcirContext {
         rhs: AcirVar,
         bit_size: u32,
         predicate: AcirVar,
-    ) -> Result<AcirVar, AcirGenError> {
+    ) -> Result<AcirVar, RuntimeError> {
         // Flip the result of calling more than equal method to
         // compute less than.
-        let comparison = self.more_than_eq_var(lhs, rhs, bit_size, Some(predicate))?;
+        let comparison = self.more_than_eq_var(lhs, rhs, bit_size, predicate)?;
 
         let one = self.add_constant(FieldElement::one());
         self.sub_var(one, comparison) // comparison_negated
@@ -619,17 +682,31 @@ impl AcirContext {
         &mut self,
         name: BlackBoxFunc,
         mut inputs: Vec<AcirValue>,
-    ) -> Result<Vec<AcirVar>, AcirGenError> {
+    ) -> Result<Vec<AcirVar>, RuntimeError> {
         // Separate out any arguments that should be constants
         let constants = match name {
             BlackBoxFunc::Pedersen => {
                 // The last argument of pedersen is the domain separator, which must be a constant
-                let domain_var =
-                    inputs.pop().expect("ICE: Pedersen call requires domain separator").into_var();
-
-                let domain_constant = self.vars[&domain_var]
-                    .as_constant()
-                    .expect("ICE: Domain separator must be a constant");
+                let domain_var = match inputs.pop() {
+                    Some(domain_var) => domain_var.into_var()?,
+                    None => {
+                        return Err(RuntimeError::InternalError(InternalError::MissingArg {
+                            name: "pedersen call".to_string(),
+                            arg: "domain separator".to_string(),
+                            location: self.get_location(),
+                        }))
+                    }
+                };
+
+                let domain_constant = match self.vars[&domain_var].as_constant() {
+                    Some(domain_constant) => domain_constant,
+                    None => {
+                        return Err(RuntimeError::InternalError(InternalError::NotAConstant {
+                            name: "domain separator".to_string(),
+                            location: self.get_location(),
+                        }))
+                    }
+                };
 
                 vec![domain_constant]
             }
@@ -640,7 +717,7 @@ impl AcirContext {
         let inputs = self.prepare_inputs_for_black_box_func_call(inputs)?;
 
         // Call Black box with `FunctionInput`
-        let outputs = self.acir_ir.call_black_box(name, inputs, constants);
+        let outputs = self.acir_ir.call_black_box(name, inputs, constants)?;
 
         // Convert `Witness` values which are now constrained to be the output of the
         // black box function call into `AcirVar`s.
@@ -656,7 +733,7 @@ impl AcirContext {
     fn prepare_inputs_for_black_box_func_call(
         &mut self,
         inputs: Vec<AcirValue>,
-    ) -> Result<Vec<FunctionInput>, AcirGenError> {
+    ) -> Result<Vec<FunctionInput>, RuntimeError> {
         let mut witnesses = Vec::new();
         for input in inputs {
             for (input, typ) in input.flatten() {
@@ -687,15 +764,26 @@ impl AcirContext {
         radix_var: AcirVar,
         limb_count_var: AcirVar,
         result_element_type: AcirType,
-    ) -> Result<Vec<AcirValue>, AcirGenError> {
-        let radix =
-            self.vars[&radix_var].as_constant().expect("ICE: radix should be a constant").to_u128()
-                as u32;
+    ) -> Result<Vec<AcirValue>, RuntimeError> {
+        let radix = match self.vars[&radix_var].as_constant() {
+            Some(radix) => radix.to_u128() as u32,
+            None => {
+                return Err(RuntimeError::InternalError(InternalError::NotAConstant {
+                    name: "radix".to_string(),
+                    location: self.get_location(),
+                }));
+            }
+        };
 
-        let limb_count = self.vars[&limb_count_var]
-            .as_constant()
-            .expect("ICE: limb_size should be a constant")
-            .to_u128() as u32;
+        let limb_count = match self.vars[&limb_count_var].as_constant() {
+            Some(limb_count) => limb_count.to_u128() as u32,
+            None => {
+                return Err(RuntimeError::InternalError(InternalError::NotAConstant {
+                    name: "limb_size".to_string(),
+                    location: self.get_location(),
+                }));
+            }
+        };
 
         let input_expr = &self.vars[&input_var].to_expression();
 
@@ -731,13 +819,13 @@ impl AcirContext {
         input_var: AcirVar,
         limb_count_var: AcirVar,
         result_element_type: AcirType,
-    ) -> Result<Vec<AcirValue>, AcirGenError> {
+    ) -> Result<Vec<AcirValue>, RuntimeError> {
         let two_var = self.add_constant(FieldElement::from(2_u128));
         self.radix_decompose(endian, input_var, two_var, limb_count_var, result_element_type)
     }
 
     /// Prints the given `AcirVar`s as witnesses.
-    pub(crate) fn print(&mut self, input: Vec<AcirValue>) -> Result<(), AcirGenError> {
+    pub(crate) fn print(&mut self, input: Vec<AcirValue>) -> Result<(), RuntimeError> {
         let input = Self::flatten_values(input);
 
         let witnesses = vecmap(input, |acir_var| {
@@ -769,11 +857,13 @@ impl AcirContext {
                     Self::flatten_value(acir_vars, value);
                 }
             }
+            AcirValue::DynamicArray(_) => unreachable!("Cannot flatten a dynamic array"),
         }
     }
 
     /// Terminates the context and takes the resulting `GeneratedAcir`
-    pub(crate) fn finish(self) -> GeneratedAcir {
+    pub(crate) fn finish(mut self, inputs: Vec<u32>) -> GeneratedAcir {
+        self.acir_ir.input_witnesses = vecmap(inputs, Witness);
         self.acir_ir
     }
 
@@ -790,23 +880,28 @@ impl AcirContext {
 
     pub(crate) fn brillig(
         &mut self,
-        predicate: Option<AcirVar>,
+        predicate: AcirVar,
         code: Vec<BrilligOpcode>,
         inputs: Vec<AcirValue>,
         outputs: Vec<AcirType>,
-    ) -> Vec<AcirValue> {
-        let b_inputs = vecmap(inputs, |i| match i {
+    ) -> Result<Vec<AcirValue>, InternalError> {
+        let b_inputs = try_vecmap(inputs, |i| match i {
             AcirValue::Var(var, _) => {
-                BrilligInputs::Single(self.vars[&var].to_expression().into_owned())
+                Ok(BrilligInputs::Single(self.vars[&var].to_expression().into_owned()))
             }
             AcirValue::Array(vars) => {
                 let mut var_expressions: Vec<Expression> = Vec::new();
                 for var in vars {
-                    self.brillig_array_input(&mut var_expressions, var);
+                    self.brillig_array_input(&mut var_expressions, var)?;
                 }
-                BrilligInputs::Array(var_expressions)
+                Ok(BrilligInputs::Array(var_expressions))
             }
-        });
+            AcirValue::DynamicArray(_) => {
+                let mut var_expressions = Vec::new();
+                self.brillig_array_input(&mut var_expressions, i)?;
+                Ok(BrilligInputs::Array(var_expressions))
+            }
+        })?;
 
         let mut b_outputs = Vec::new();
         let outputs_var = vecmap(outputs, |output| match output {
@@ -817,37 +912,81 @@ impl AcirContext {
                 AcirValue::Var(var, output.clone())
             }
             AcirType::Array(element_types, size) => {
-                let mut witnesses = Vec::new();
-                let mut array_values = im::Vector::new();
-                for _ in 0..size {
-                    for element_type in &element_types {
-                        let witness_index = self.acir_ir.next_witness_index();
-                        witnesses.push(witness_index);
-                        let var = self.add_data(AcirVarData::Witness(witness_index));
-                        array_values.push_back(AcirValue::Var(var, element_type.clone()));
-                    }
-                }
+                let (acir_value, witnesses) = self.brillig_array_output(&element_types, size);
                 b_outputs.push(BrilligOutputs::Array(witnesses));
-                AcirValue::Array(array_values)
+                acir_value
             }
         });
-        let predicate = predicate.map(|var| self.vars[&var].to_expression().into_owned());
-        self.acir_ir.brillig(predicate, code, b_inputs, b_outputs);
+        let predicate = self.vars[&predicate].to_expression().into_owned();
+        self.acir_ir.brillig(Some(predicate), code, b_inputs, b_outputs);
 
-        outputs_var
+        Ok(outputs_var)
     }
 
-    fn brillig_array_input(&self, var_expressions: &mut Vec<Expression>, input: AcirValue) {
+    fn brillig_array_input(
+        &mut self,
+        var_expressions: &mut Vec<Expression>,
+        input: AcirValue,
+    ) -> Result<(), InternalError> {
         match input {
             AcirValue::Var(var, _) => {
                 var_expressions.push(self.vars[&var].to_expression().into_owned());
             }
             AcirValue::Array(vars) => {
                 for var in vars {
-                    self.brillig_array_input(var_expressions, var);
+                    self.brillig_array_input(var_expressions, var)?;
+                }
+            }
+            AcirValue::DynamicArray(AcirDynamicArray { block_id, len }) => {
+                for i in 0..len {
+                    // We generate witnesses corresponding to the array values
+                    let index = AcirValue::Var(
+                        self.add_constant(FieldElement::from(i as u128)),
+                        AcirType::NumericType(NumericType::NativeField),
+                    );
+                    let index_var = index.into_var()?;
+
+                    let value_read_var = self.read_from_memory(block_id, &index_var)?;
+                    let value_read = AcirValue::Var(
+                        value_read_var,
+                        AcirType::NumericType(NumericType::NativeField),
+                    );
+
+                    self.brillig_array_input(var_expressions, value_read)?;
+                }
+            }
+        }
+        Ok(())
+    }
+
+    /// Recursively create acir values for returned arrays. This is necessary because a brillig returned array can have nested arrays as elements.
+    /// A singular array of witnesses is collected for a top level array, by deflattening the assigned witnesses at each level.
+    fn brillig_array_output(
+        &mut self,
+        element_types: &[AcirType],
+        size: usize,
+    ) -> (AcirValue, Vec<Witness>) {
+        let mut witnesses = Vec::new();
+        let mut array_values = im::Vector::new();
+        for _ in 0..size {
+            for element_type in element_types {
+                match element_type {
+                    AcirType::Array(nested_element_types, nested_size) => {
+                        let (nested_acir_value, mut nested_witnesses) =
+                            self.brillig_array_output(nested_element_types, *nested_size);
+                        witnesses.append(&mut nested_witnesses);
+                        array_values.push_back(nested_acir_value);
+                    }
+                    AcirType::NumericType(_) => {
+                        let witness_index = self.acir_ir.next_witness_index();
+                        witnesses.push(witness_index);
+                        let var = self.add_data(AcirVarData::Witness(witness_index));
+                        array_values.push_back(AcirValue::Var(var, element_type.clone()));
+                    }
                 }
             }
         }
+        (AcirValue::Array(array_values), witnesses)
     }
 
     /// Generate output variables that are constrained to be the sorted inputs
@@ -858,7 +997,8 @@ impl AcirContext {
         &mut self,
         inputs: Vec<AcirVar>,
         bit_size: u32,
-    ) -> Result<Vec<AcirVar>, AcirGenError> {
+        predicate: AcirVar,
+    ) -> Result<Vec<AcirVar>, RuntimeError> {
         let len = inputs.len();
         // Convert the inputs into expressions
         let inputs_expr = vecmap(inputs, |input| self.vars[&input].to_expression().into_owned());
@@ -871,15 +1011,23 @@ impl AcirContext {
         });
 
         // Enforce the outputs to be a permutation of the inputs
-        self.acir_ir.permutation(&inputs_expr, &output_expr);
+        self.acir_ir.permutation(&inputs_expr, &output_expr)?;
 
         // Enforce the outputs to be sorted
         for i in 0..(outputs_var.len() - 1) {
-            self.less_than_constrain(outputs_var[i], outputs_var[i + 1], bit_size, None)?;
+            self.less_than_constrain(outputs_var[i], outputs_var[i + 1], bit_size, predicate)?;
         }
 
         Ok(outputs_var)
     }
+    /// Converts an AcirVar to a Witness
+    fn var_to_witness(&mut self, var: AcirVar) -> Result<Witness, InternalError> {
+        let var_data = match self.vars.get(&var) {
+            Some(var_data) => var_data,
+            None => return Err(InternalError::UndeclaredAcirVar { location: self.get_location() }),
+        };
+        Ok(self.acir_ir.get_or_create_witness(&var_data.to_expression()))
+    }
 
     /// Constrain lhs to be less than rhs
     fn less_than_constrain(
@@ -887,10 +1035,77 @@ impl AcirContext {
         lhs: AcirVar,
         rhs: AcirVar,
         bit_size: u32,
-        predicate: Option<AcirVar>,
-    ) -> Result<(), AcirGenError> {
+        predicate: AcirVar,
+    ) -> Result<(), RuntimeError> {
         let lhs_less_than_rhs = self.more_than_eq_var(rhs, lhs, bit_size, predicate)?;
-        self.assert_eq_one(lhs_less_than_rhs)
+        self.maybe_eq_predicate(lhs_less_than_rhs, predicate)
+    }
+
+    /// Returns a Variable that is constrained to be the result of reading
+    /// from the memory `block_id` at the given `index`.
+    pub(crate) fn read_from_memory(
+        &mut self,
+        block_id: BlockId,
+        index: &AcirVar,
+    ) -> Result<AcirVar, InternalError> {
+        // Fetch the witness corresponding to the index
+        let index_witness = self.var_to_witness(*index)?;
+
+        // Create a Variable to hold the result of the read and extract the corresponding Witness
+        let value_read_var = self.add_variable();
+        let value_read_witness = self.var_to_witness(value_read_var)?;
+
+        // Add the memory read operation to the list of opcodes
+        let op = MemOp::read_at_mem_index(index_witness.into(), value_read_witness);
+        self.acir_ir.opcodes.push(Opcode::MemoryOp { block_id, op });
+
+        Ok(value_read_var)
+    }
+
+    /// Constrains the Variable `value` to be the new value located at `index` in the memory `block_id`.
+    pub(crate) fn write_to_memory(
+        &mut self,
+        block_id: BlockId,
+        index: &AcirVar,
+        value: &AcirVar,
+    ) -> Result<(), InternalError> {
+        // Fetch the witness corresponding to the index
+        //
+        let index_witness = self.var_to_witness(*index)?;
+
+        // Fetch the witness corresponding to the value to be written
+        let value_write_witness = self.var_to_witness(*value)?;
+
+        // Add the memory write operation to the list of opcodes
+        let op = MemOp::write_to_mem_index(index_witness.into(), value_write_witness.into());
+        self.acir_ir.opcodes.push(Opcode::MemoryOp { block_id, op });
+        Ok(())
+    }
+
+    /// Initializes an array in memory with the given values `optional_values`.
+    /// If `optional_values` is empty, then the array is initialized with zeros.
+    pub(crate) fn initialize_array(
+        &mut self,
+        block_id: BlockId,
+        len: usize,
+        optional_values: Option<&[AcirValue]>,
+    ) -> Result<(), InternalError> {
+        // If the optional values are supplied, then we fill the initialized
+        // array with those values. If not, then we fill it with zeros.
+        let initialized_values = match optional_values {
+            None => {
+                let zero = self.add_constant(FieldElement::zero());
+                let zero_witness = self.var_to_witness(zero)?;
+                vec![zero_witness; len]
+            }
+            Some(optional_values) => try_vecmap(optional_values, |value| {
+                let value = value.clone().into_var()?;
+                self.var_to_witness(value)
+            })?,
+        };
+
+        self.acir_ir.opcodes.push(Opcode::MemoryInit { block_id, init: initialized_values });
+        Ok(())
     }
 }
 
diff --git a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/errors.rs b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/errors.rs
deleted file mode 100644
index fa98bbead19..00000000000
--- a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/errors.rs
+++ /dev/null
@@ -1,69 +0,0 @@
-use acvm::FieldElement;
-use noirc_errors::Location;
-
-use crate::errors::{RuntimeError, RuntimeErrorKind};
-
-#[derive(Debug, PartialEq, Eq, Clone)]
-pub(crate) enum AcirGenError {
-    InvalidRangeConstraint { num_bits: u32, location: Option<Location> },
-    IndexOutOfBounds { index: usize, array_size: usize, location: Option<Location> },
-    UnsupportedIntegerSize { num_bits: u32, max_num_bits: u32, location: Option<Location> },
-    BadConstantEquality { lhs: FieldElement, rhs: FieldElement, location: Option<Location> },
-}
-
-impl AcirGenError {
-    pub(crate) fn message(&self) -> String {
-        match self {
-            AcirGenError::InvalidRangeConstraint { num_bits, .. } => {
-                // Don't apply any constraints if the range is for the maximum number of bits or more.
-                format!(
-             "All Witnesses are by default u{num_bits} Applying this type does not apply any constraints.\n We also currently do not allow integers of size more than {num_bits}, this will be handled by BigIntegers.")
-            }
-            AcirGenError::IndexOutOfBounds { index, array_size, .. } => {
-                format!("Index out of bounds, array has size {array_size}, but index was {index}")
-            }
-            AcirGenError::UnsupportedIntegerSize { num_bits, max_num_bits, .. } => {
-                format!("Integer sized {num_bits} is over the max supported size of {max_num_bits}")
-            }
-            AcirGenError::BadConstantEquality { lhs, rhs, .. } => {
-                format!("{lhs} and {rhs} constrained to be equal though they never can be")
-            }
-        }
-    }
-}
-
-impl From<AcirGenError> for RuntimeError {
-    fn from(error: AcirGenError) -> Self {
-        match error {
-            AcirGenError::InvalidRangeConstraint { num_bits, location } => {
-                let kind = RuntimeErrorKind::UnstructuredError {
-                    message: format!(
-                        "Failed range constraint when constraining to {num_bits} bits"
-                    ),
-                };
-                RuntimeError::new(kind, location)
-            }
-            AcirGenError::IndexOutOfBounds { index, array_size, location } => {
-                let kind = RuntimeErrorKind::ArrayOutOfBounds {
-                    index: index as u128,
-                    bound: array_size as u128,
-                };
-                RuntimeError::new(kind, location)
-            }
-            AcirGenError::UnsupportedIntegerSize { num_bits, max_num_bits, location } => {
-                let kind = RuntimeErrorKind::UnstructuredError {
-                    message: format!("Unsupported integer size of {num_bits} bits. The maximum supported size is {max_num_bits} bits.")
-                };
-                RuntimeError::new(kind, location)
-            }
-            AcirGenError::BadConstantEquality { lhs: _, rhs: _, location } => {
-                // We avoid showing the actual lhs and rhs since most of the time they are just 0
-                // and 1 respectively. This would confuse users if a constraint such as
-                // assert(foo < bar) fails with "failed constraint: 0 = 1."
-                let kind =
-                    RuntimeErrorKind::UnstructuredError { message: "Failed constraint".into() };
-                RuntimeError::new(kind, location)
-            }
-        }
-    }
-}
diff --git a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/generated_acir.rs b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/generated_acir.rs
index 16e07c29730..c368a042dc9 100644
--- a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/generated_acir.rs
+++ b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/generated_acir.rs
@@ -2,9 +2,11 @@
 //! program as it is being converted from SSA form.
 use std::collections::HashMap;
 
-use crate::brillig::brillig_gen::brillig_directive;
+use crate::{
+    brillig::brillig_gen::brillig_directive,
+    errors::{InternalError, RuntimeError},
+};
 
-use super::errors::AcirGenError;
 use acvm::acir::{
     brillig::Opcode as BrilligOpcode,
     circuit::{
@@ -40,6 +42,9 @@ pub(crate) struct GeneratedAcir {
     /// abi's return type.
     pub(crate) return_witnesses: Vec<Witness>,
 
+    /// All witness indices which are inputs to the main function
+    pub(crate) input_witnesses: Vec<Witness>,
+
     /// Correspondance between an opcode index (in opcodes) and the source code location which generated it
     pub(crate) locations: HashMap<usize, Location>,
 
@@ -112,92 +117,6 @@ impl GeneratedAcir {
 }
 
 impl GeneratedAcir {
-    /// Computes lhs = 2^{rhs_bit_size} * q + r
-    ///
-    /// For example, if we had a u32:
-    ///     - `rhs` would be `32`
-    ///     - `max_bits` would be the size of `lhs`
-    ///
-    /// Take the following code:
-    /// ``
-    ///   fn main(x : u32) -> u32 {
-    ///     let a = x + x; (L1)
-    ///     let b = a * a; (L2)
-    ///     b + b (L3)
-    ///   }
-    /// ``
-    ///
-    ///  Call truncate only on L1:
-    ///     - `rhs` would be `32`
-    ///     - `max_bits` would be `33` due to the addition of two u32s
-    ///  Call truncate only on L2:
-    ///     - `rhs` would be `32`
-    ///     - `max_bits` would be `66` due to the multiplication of two u33s `a`
-    ///  Call truncate only on L3:
-    ///     -  `rhs` would be `32`
-    ///     - `max_bits` would be `67` due to the addition of two u66s `b`
-    ///
-    /// Truncation is done via the euclidean division formula:
-    ///
-    /// a = b * q + r
-    ///
-    /// where:
-    ///     - a = `lhs`
-    ///     - b = 2^{max_bits}
-    /// The prover will supply the quotient and the remainder, where the remainder
-    /// is the truncated value that we will return since it is enforced to be
-    /// in the range:  0 <= r < 2^{rhs_bit_size}
-    pub(crate) fn truncate(
-        &mut self,
-        lhs: &Expression,
-        rhs_bit_size: u32,
-        max_bits: u32,
-    ) -> Result<Expression, AcirGenError> {
-        assert!(max_bits > rhs_bit_size, "max_bits = {max_bits}, rhs = {rhs_bit_size} -- The caller should ensure that truncation is only called when the value needs to be truncated");
-        let exp_big = BigUint::from(2_u32).pow(rhs_bit_size);
-
-        // 0. Check for constant expression.
-        if let Some(a_c) = lhs.to_const() {
-            let mut a_big = BigUint::from_bytes_be(&a_c.to_be_bytes());
-            a_big %= exp_big;
-            return Ok(Expression::from(FieldElement::from_be_bytes_reduce(&a_big.to_bytes_be())));
-        }
-        // Note: This is doing a reduction. However, since the compiler will call
-        // `max_bits` before it overflows the modulus, this line should never do a reduction.
-        //
-        // For example, if the modulus is a 254 bit number.
-        // `max_bits` will never be 255 since `exp` will be 2^255, which will cause a reduction in the following line.
-        // TODO: We should change this from `from_be_bytes_reduce` to `from_be_bytes`
-        // TODO: the latter will return an option that we can unwrap in the compiler
-        let exp = FieldElement::from_be_bytes_reduce(&exp_big.to_bytes_be());
-
-        // 1. Generate witnesses a,b,c
-
-        // According to the division theorem, the remainder needs to be 0 <= r < 2^{rhs_bit_size}
-        let r_max_bits = rhs_bit_size;
-        // According to the formula above, the quotient should be within the range 0 <= q < 2^{max_bits - rhs}
-        let q_max_bits = max_bits - rhs_bit_size;
-
-        let (quotient_witness, remainder_witness) =
-            self.quotient_directive(lhs.clone(), exp.into(), None, q_max_bits, r_max_bits)?;
-
-        // 2. Add the constraint a == r + (q * 2^{rhs})
-        //
-        // 2^{rhs}
-        let mut two_pow_rhs_bits = FieldElement::from(2_i128);
-        two_pow_rhs_bits = two_pow_rhs_bits.pow(&FieldElement::from(rhs_bit_size as i128));
-
-        let remainder_expr = Expression::from(remainder_witness);
-        let quotient_expr = Expression::from(quotient_witness);
-
-        let res = &remainder_expr + &(two_pow_rhs_bits * &quotient_expr);
-        let euclidean_division = &res - lhs;
-
-        self.push_opcode(AcirOpcode::Arithmetic(euclidean_division));
-
-        Ok(Expression::from(remainder_witness))
-    }
-
     /// Calls a black box function and returns the output
     /// of said blackbox function.
     pub(crate) fn call_black_box(
@@ -205,10 +124,10 @@ impl GeneratedAcir {
         func_name: BlackBoxFunc,
         mut inputs: Vec<FunctionInput>,
         constants: Vec<FieldElement>,
-    ) -> Vec<Witness> {
-        intrinsics_check_inputs(func_name, &inputs);
+    ) -> Result<Vec<Witness>, InternalError> {
+        intrinsics_check_inputs(func_name, &inputs)?;
 
-        let output_count = black_box_expected_output_size(func_name);
+        let output_count = black_box_expected_output_size(func_name)?;
         let outputs = vecmap(0..output_count, |_| self.next_witness_index());
 
         // clone is needed since outputs is moved when used in blackbox function.
@@ -265,18 +184,30 @@ impl GeneratedAcir {
                 outputs: (outputs[0], outputs[1]),
             },
             BlackBoxFunc::Keccak256 => {
-                let var_message_size = inputs.pop().expect("ICE: Missing message_size arg");
+                let var_message_size = match inputs.pop() {
+                    Some(var_message_size) => var_message_size,
+                    None => {
+                        return Err(InternalError::MissingArg {
+                            name: "".to_string(),
+                            arg: "message_size".to_string(),
+                            location: self.current_location,
+                        });
+                    }
+                };
                 BlackBoxFuncCall::Keccak256VariableLength { inputs, var_message_size, outputs }
             }
             // TODO(#1570): Generate ACIR for recursive aggregation
             BlackBoxFunc::RecursiveAggregation => {
-                panic!("ICE: Cannot generate ACIR for recursive aggregation")
+                return Err(InternalError::NotImplemented {
+                    name: "recursive aggregation".to_string(),
+                    location: None,
+                })
             }
         };
 
         self.opcodes.push(AcirOpcode::BlackBoxFuncCall(black_box_func_call));
 
-        outputs_clone
+        Ok(outputs_clone)
     }
 
     /// Takes an input expression and returns witnesses that are constrained to be limbs
@@ -289,7 +220,7 @@ impl GeneratedAcir {
         radix: u32,
         limb_count: u32,
         bit_size: u32,
-    ) -> Result<Vec<Witness>, AcirGenError> {
+    ) -> Result<Vec<Witness>, RuntimeError> {
         let radix_big = BigUint::from(radix);
         assert_eq!(
             BigUint::from(2u128).pow(bit_size),
@@ -334,8 +265,60 @@ impl GeneratedAcir {
     ) -> Expression {
         let max_power_of_two =
             FieldElement::from(2_i128).pow(&FieldElement::from(max_bit_size as i128 - 1));
-        let inter = &(&Expression::from_field(max_power_of_two) - lhs) * &leading.into();
-        lhs.add_mul(FieldElement::from(2_i128), &inter.unwrap())
+
+        let intermediate =
+            self.mul_with_witness(&(&Expression::from(max_power_of_two) - lhs), &leading.into());
+
+        lhs.add_mul(FieldElement::from(2_i128), &intermediate)
+    }
+
+    /// Returns an expression which represents `lhs * rhs`
+    ///
+    /// If one has multiplicative term and the other is of degree one or more,
+    /// the function creates [intermediate variables][`Witness`] accordingly.
+    /// There are two cases where we can optimize the multiplication between two expressions:
+    /// 1. If the sum of the degrees of both expressions is at most 2, then we can just multiply them
+    /// as each term in the result will be degree-2.
+    /// 2. If one expression is a constant, then we can just multiply the constant with the other expression
+    ///
+    /// (1) is because an [`Expression`] can hold at most a degree-2 univariate polynomial
+    /// which is what you get when you multiply two degree-1 univariate polynomials.
+    pub(crate) fn mul_with_witness(&mut self, lhs: &Expression, rhs: &Expression) -> Expression {
+        use std::borrow::Cow;
+        let lhs_is_linear = lhs.is_linear();
+        let rhs_is_linear = rhs.is_linear();
+
+        // Case 1: The sum of the degrees of both expressions is at most 2.
+        //
+        // If one of the expressions is constant then it does not increase the degree when multiplying by another expression.
+        // If both of the expressions are linear (degree <=1) then the product will be at most degree 2.
+        let both_are_linear = lhs_is_linear && rhs_is_linear;
+        let either_is_const = lhs.is_const() || rhs.is_const();
+        if both_are_linear || either_is_const {
+            return (lhs * rhs).expect("Both expressions are degree <= 1");
+        }
+
+        // Case 2: One or both of the sides needs to be reduced to a degree-1 univariate polynomial
+        let lhs_reduced = if lhs_is_linear {
+            Cow::Borrowed(lhs)
+        } else {
+            Cow::Owned(self.get_or_create_witness(lhs).into())
+        };
+
+        // If the lhs and rhs are the same, then we do not need to reduce
+        // rhs, we only need to square the lhs.
+        if lhs == rhs {
+            return (&*lhs_reduced * &*lhs_reduced)
+                .expect("Both expressions are reduced to be degree <= 1");
+        };
+
+        let rhs_reduced = if rhs_is_linear {
+            Cow::Borrowed(rhs)
+        } else {
+            Cow::Owned(self.get_or_create_witness(rhs).into())
+        };
+
+        (&*lhs_reduced * &*rhs_reduced).expect("Both expressions are reduced to be degree <= 1")
     }
 
     /// Signed division lhs /  rhs
@@ -351,13 +334,13 @@ impl GeneratedAcir {
         lhs: &Expression,
         rhs: &Expression,
         max_bit_size: u32,
-    ) -> Result<(Expression, Expression), AcirGenError> {
+    ) -> Result<(Expression, Expression), RuntimeError> {
         // 2^{max_bit size-1}
         let max_power_of_two =
             FieldElement::from(2_i128).pow(&FieldElement::from(max_bit_size as i128 - 1));
 
         // Get the sign bit of rhs by computing rhs / max_power_of_two
-        let (rhs_leading, _) = self.euclidean_division(
+        let (rhs_leading_witness, _) = self.euclidean_division(
             rhs,
             &max_power_of_two.into(),
             max_bit_size,
@@ -365,7 +348,7 @@ impl GeneratedAcir {
         )?;
 
         // Get the sign bit of lhs by computing lhs / max_power_of_two
-        let (lhs_leading, _) = self.euclidean_division(
+        let (lhs_leading_witness, _) = self.euclidean_division(
             lhs,
             &max_power_of_two.into(),
             max_bit_size,
@@ -373,8 +356,8 @@ impl GeneratedAcir {
         )?;
 
         // Signed to unsigned:
-        let unsigned_lhs = self.two_complement(lhs, lhs_leading, max_bit_size);
-        let unsigned_rhs = self.two_complement(rhs, rhs_leading, max_bit_size);
+        let unsigned_lhs = self.two_complement(lhs, lhs_leading_witness, max_bit_size);
+        let unsigned_rhs = self.two_complement(rhs, rhs_leading_witness, max_bit_size);
         let unsigned_l_witness = self.get_or_create_witness(&unsigned_lhs);
         let unsigned_r_witness = self.get_or_create_witness(&unsigned_rhs);
 
@@ -388,13 +371,16 @@ impl GeneratedAcir {
 
         // Unsigned to signed: derive q and r from q1,r1 and the signs of lhs and rhs
         // Quotient sign is lhs sign * rhs sign, whose resulting sign bit is the XOR of the sign bits
-        let q_sign = (&Expression::from(lhs_leading) + &Expression::from(rhs_leading)).add_mul(
-            -FieldElement::from(2_i128),
-            &(&Expression::from(lhs_leading) * &Expression::from(rhs_leading)).unwrap(),
-        );
+        let sign_sum =
+            &Expression::from(lhs_leading_witness) + &Expression::from(rhs_leading_witness);
+        let sign_prod = (&Expression::from(lhs_leading_witness)
+            * &Expression::from(rhs_leading_witness))
+            .expect("Product of two witnesses so result is degree 2");
+        let q_sign = sign_sum.add_mul(-FieldElement::from(2_i128), &sign_prod);
+
         let q_sign_witness = self.get_or_create_witness(&q_sign);
         let quotient = self.two_complement(&q1.into(), q_sign_witness, max_bit_size);
-        let remainder = self.two_complement(&r1.into(), lhs_leading, max_bit_size);
+        let remainder = self.two_complement(&r1.into(), lhs_leading_witness, max_bit_size);
         Ok((quotient, remainder))
     }
 
@@ -408,31 +394,41 @@ impl GeneratedAcir {
         rhs: &Expression,
         max_bit_size: u32,
         predicate: &Expression,
-    ) -> Result<(Witness, Witness), AcirGenError> {
+    ) -> Result<(Witness, Witness), RuntimeError> {
         // lhs = rhs * q + r
         //
         // If predicate is zero, `q_witness` and `r_witness` will be 0
+
+        // maximum bit size for q and for [r and rhs]
+        let mut max_q_bits = max_bit_size;
+        let mut max_rhs_bits = max_bit_size;
+        // when rhs is constant, we can better estimate the maximum bit sizes
+        if let Some(rhs_const) = rhs.to_const() {
+            max_rhs_bits = rhs_const.num_bits();
+            if max_rhs_bits != 0 {
+                max_q_bits = max_bit_size - max_rhs_bits + 1;
+            }
+        }
+
         let (q_witness, r_witness) = self.quotient_directive(
             lhs.clone(),
             rhs.clone(),
             Some(predicate.clone()),
-            max_bit_size,
-            max_bit_size,
+            max_q_bits,
+            max_rhs_bits,
         )?;
 
         // Constrain r < rhs
-        self.bound_constraint_with_offset(&r_witness.into(), rhs, predicate, max_bit_size)?;
+        self.bound_constraint_with_offset(&r_witness.into(), rhs, predicate, max_rhs_bits)?;
 
         // a * predicate == (b * q + r) * predicate
-        // => predicate * ( a - b * q - r) == 0
+        // => predicate * (a - b * q - r) == 0
         // When the predicate is 0, the equation always passes.
         // When the predicate is 1, the euclidean division needs to be
         // true.
-        let mut rhs_constraint = (rhs * &Expression::from(q_witness)).unwrap();
-        rhs_constraint = &rhs_constraint + r_witness;
-        rhs_constraint = (&rhs_constraint * predicate).unwrap();
-        let lhs_constraint = (lhs * predicate).unwrap();
-        let div_euclidean = &lhs_constraint - &rhs_constraint;
+        let rhs_constraint = &self.mul_with_witness(rhs, &q_witness.into()) + r_witness;
+        let div_euclidean = &self.mul_with_witness(lhs, predicate)
+            - &self.mul_with_witness(&rhs_constraint, predicate);
 
         self.push_opcode(AcirOpcode::Arithmetic(div_euclidean));
 
@@ -456,7 +452,7 @@ impl GeneratedAcir {
         rhs: &Expression,
         offset: &Expression,
         bits: u32,
-    ) -> Result<(), AcirGenError> {
+    ) -> Result<(), RuntimeError> {
         const fn num_bits<T>() -> usize {
             std::mem::size_of::<T>() * 8
         }
@@ -494,7 +490,7 @@ impl GeneratedAcir {
             assert!(bits + bit_size < FieldElement::max_num_bits()); //we need to ensure lhs_offset + r does not overflow
             let mut aor = lhs_offset;
             aor.q_c += FieldElement::from(r);
-            let witness = self.create_witness_for_expression(&aor);
+            let witness = self.get_or_create_witness(&aor);
             // lhs_offset<=rhs_offset <=> lhs_offset + r < rhs_offset + r = 2^bit_size <=> witness < 2^bit_size
             self.range_constraint(witness, bit_size)?;
             return Ok(());
@@ -656,11 +652,11 @@ impl GeneratedAcir {
         &mut self,
         witness: Witness,
         num_bits: u32,
-    ) -> Result<(), AcirGenError> {
+    ) -> Result<(), RuntimeError> {
         // We class this as an error because users should instead
         // do `as Field`.
         if num_bits >= FieldElement::max_num_bits() {
-            return Err(AcirGenError::InvalidRangeConstraint {
+            return Err(RuntimeError::InvalidRangeConstraint {
                 num_bits: FieldElement::max_num_bits(),
                 location: self.current_location,
             });
@@ -684,7 +680,7 @@ impl GeneratedAcir {
         predicate: Option<Expression>,
         q_max_bits: u32,
         r_max_bits: u32,
-    ) -> Result<(Witness, Witness), AcirGenError> {
+    ) -> Result<(Witness, Witness), RuntimeError> {
         let q_witness = self.next_witness_index();
         let r_witness = self.next_witness_index();
 
@@ -704,15 +700,27 @@ impl GeneratedAcir {
     /// - `1` if lhs >= rhs
     /// - `0` otherwise
     ///
-    /// See [R1CS Workshop - Section 10](https://github.com/mir-protocol/r1cs-workshop/blob/master/workshop.pdf)
-    /// for an explanation.
+    /// We essentially computes the sign bit of `b-a`
+    /// For this we sign-extend `b-a` with `c = 2^{max_bits} - (b - a)`, since both `a` and `b` are less than `2^{max_bits}`
+    /// Then we get the bit sign of `c`, the 2-complement representation of `(b-a)`, which is a `max_bits+1` integer,
+    /// by doing the euclidean division `c / 2^{max_bits}`
+    ///
+    /// To see why it really works;
+    /// We first note that `c` is an integer of `(max_bits+1)` bits. Therefore,
+    /// if `b-a>0`, then `c < 2^{max_bits}`, so the division by `2^{max_bits}` will give `0`
+    /// If `b-a<=0`, then `c >= 2^{max_bits}`, so the division by `2^{max_bits}` will give `1`.
+    ///
+    /// In other words, `1` means `a >= b` and `0` means `b > a`.
+    /// The important thing here is that `c` does not overflow nor underflow the field;
+    /// - By construction we have `c >= 0`, so there is no underflow
+    /// - We assert at the beginning that `2^{max_bits+1}` does not overflow the field, so neither c.
     pub(crate) fn more_than_eq_comparison(
         &mut self,
         a: &Expression,
         b: &Expression,
         max_bits: u32,
-        predicate: Option<Expression>,
-    ) -> Result<Witness, AcirGenError> {
+        predicate: Expression,
+    ) -> Result<Witness, RuntimeError> {
         // Ensure that 2^{max_bits + 1} is less than the field size
         //
         // TODO: perhaps this should be a user error, instead of an assert
@@ -723,26 +731,12 @@ impl GeneratedAcir {
         let two_max_bits: FieldElement = two.pow(&FieldElement::from(max_bits as i128));
         let comparison_evaluation = (a - b) + two_max_bits;
 
-        // We want to enforce that `q` is a boolean value.
-        // In particular it should be the `n` bit of the `comparison_evaluation`
-        // which will indicate whether a >= b.
+        // Euclidian division by 2^{max_bits}  : 2^{max_bits} + a - b = q * 2^{max_bits} + r
         //
-        // In the document linked above, they mention negating the value of `q`
-        // which would tell us whether a < b. Since we do not negate `q`
-        // what we get is a boolean indicating whether a >= b.
-        let q_max_bits = 1;
-        // `r` can take any value up to `two_max_bits`.
-        let r_max_bits = max_bits;
-
-        let (q_witness, r_witness) = self.quotient_directive(
-            comparison_evaluation.clone(),
-            two_max_bits.into(),
-            predicate,
-            q_max_bits,
-            r_max_bits,
-        )?;
-
-        // Add constraint : 2^{max_bits} + a - b = q * 2^{max_bits} + r
+        // 2^{max_bits} is of max_bits+1 bit size
+        // If a>b, then a-b is less than 2^{max_bits} - 1, so 2^{max_bits} + a - b is less than 2^{max_bits} + 2^{max_bits} - 1 = 2^{max_bits+1} - 1
+        // If a <= b, then 2^{max_bits} + a - b is less than 2^{max_bits} <= 2^{max_bits+1} - 1
+        // This means that both operands of the division have at most max_bits+1 bit size.
         //
         // case: a == b
         //
@@ -762,12 +756,13 @@ impl GeneratedAcir {
         // - 2^{max_bits} - k == q * 2^{max_bits} + r
         // - This is only the case when q == 0 and r == 2^{max_bits} - k
         //
-        let mut expr = Expression::default();
-        expr.push_addition_term(two_max_bits, q_witness);
-        expr.push_addition_term(FieldElement::one(), r_witness);
-        self.push_opcode(AcirOpcode::Arithmetic(&comparison_evaluation - &expr));
-
-        Ok(q_witness)
+        let (q, _) = self.euclidean_division(
+            &comparison_evaluation,
+            &Expression::from(two_max_bits),
+            max_bits + 1,
+            &predicate,
+        )?;
+        Ok(q)
     }
 
     pub(crate) fn brillig(
@@ -794,7 +789,11 @@ impl GeneratedAcir {
     ///
     /// n.b. A sorting network is a predetermined set of switches,
     /// the control bits indicate the configuration of each switch: false for pass-through and true for cross-over
-    pub(crate) fn permutation(&mut self, in_expr: &[Expression], out_expr: &[Expression]) {
+    pub(crate) fn permutation(
+        &mut self,
+        in_expr: &[Expression],
+        out_expr: &[Expression],
+    ) -> Result<(), RuntimeError> {
         let mut bits_len = 0;
         for i in 0..in_expr.len() {
             bits_len += ((i + 1) as f32).log2().ceil() as u32;
@@ -808,77 +807,80 @@ impl GeneratedAcir {
             bits: bits.clone(),
             sort_by: vec![0],
         }));
-        let (_, b) = self.permutation_layer(in_expr, &bits, false);
+        let (_, b) = self.permutation_layer(in_expr, &bits, false)?;
 
         // Constrain the network output to out_expr
         for (b, o) in b.iter().zip(out_expr) {
             self.push_opcode(AcirOpcode::Arithmetic(b - o));
         }
+        Ok(())
     }
 }
 
 /// This function will return the number of inputs that a blackbox function
 /// expects. Returning `None` if there is no expectation.
-fn black_box_func_expected_input_size(name: BlackBoxFunc) -> Option<usize> {
+fn black_box_func_expected_input_size(name: BlackBoxFunc) -> Result<Option<usize>, InternalError> {
     match name {
         // Bitwise opcodes will take in 2 parameters
-        BlackBoxFunc::AND | BlackBoxFunc::XOR => Some(2),
+        BlackBoxFunc::AND | BlackBoxFunc::XOR => Ok(Some(2)),
         // All of the hash/cipher methods will take in a
         // variable number of inputs.
         BlackBoxFunc::Keccak256
         | BlackBoxFunc::SHA256
         | BlackBoxFunc::Blake2s
         | BlackBoxFunc::Pedersen
-        | BlackBoxFunc::HashToField128Security => None,
+        | BlackBoxFunc::HashToField128Security => Ok(None),
 
         // Can only apply a range constraint to one
         // witness at a time.
-        BlackBoxFunc::RANGE => Some(1),
+        BlackBoxFunc::RANGE => Ok(Some(1)),
 
         // Signature verification algorithms will take in a variable
         // number of inputs, since the message/hashed-message can vary in size.
         BlackBoxFunc::SchnorrVerify
         | BlackBoxFunc::EcdsaSecp256k1
-        | BlackBoxFunc::EcdsaSecp256r1 => None,
+        | BlackBoxFunc::EcdsaSecp256r1 => Ok(None),
         // Inputs for fixed based scalar multiplication
         // is just a scalar
-        BlackBoxFunc::FixedBaseScalarMul => Some(1),
+        BlackBoxFunc::FixedBaseScalarMul => Ok(Some(1)),
         // TODO(#1570): Generate ACIR for recursive aggregation
         // RecursiveAggregation has variable inputs and we could return `None` here,
-        // but as it is not fully implemented we panic for now
-        BlackBoxFunc::RecursiveAggregation => {
-            panic!("ICE: Cannot generate ACIR for recursive aggregation")
-        }
+        // but as it is not fully implemented we return an ICE error for now
+        BlackBoxFunc::RecursiveAggregation => Err(InternalError::NotImplemented {
+            name: "recursive aggregation".to_string(),
+            location: None,
+        }),
     }
 }
 
 /// This function will return the number of outputs that a blackbox function
 /// expects. Returning `None` if there is no expectation.
-fn black_box_expected_output_size(name: BlackBoxFunc) -> u32 {
+fn black_box_expected_output_size(name: BlackBoxFunc) -> Result<u32, InternalError> {
     match name {
         // Bitwise opcodes will return 1 parameter which is the output
         // or the operation.
-        BlackBoxFunc::AND | BlackBoxFunc::XOR => 1,
+        BlackBoxFunc::AND | BlackBoxFunc::XOR => Ok(1),
         // 32 byte hash algorithms
-        BlackBoxFunc::Keccak256 | BlackBoxFunc::SHA256 | BlackBoxFunc::Blake2s => 32,
+        BlackBoxFunc::Keccak256 | BlackBoxFunc::SHA256 | BlackBoxFunc::Blake2s => Ok(32),
         // Hash to field returns a field element
-        BlackBoxFunc::HashToField128Security => 1,
+        BlackBoxFunc::HashToField128Security => Ok(1),
         // Pedersen returns a point
-        BlackBoxFunc::Pedersen => 2,
+        BlackBoxFunc::Pedersen => Ok(2),
         // Can only apply a range constraint to one
         // witness at a time.
-        BlackBoxFunc::RANGE => 0,
+        BlackBoxFunc::RANGE => Ok(0),
         // Signature verification algorithms will return a boolean
         BlackBoxFunc::SchnorrVerify
         | BlackBoxFunc::EcdsaSecp256k1
-        | BlackBoxFunc::EcdsaSecp256r1 => 1,
+        | BlackBoxFunc::EcdsaSecp256r1 => Ok(1),
         // Output of fixed based scalar mul over the embedded curve
         // will be 2 field elements representing the point.
-        BlackBoxFunc::FixedBaseScalarMul => 2,
+        BlackBoxFunc::FixedBaseScalarMul => Ok(2),
         // TODO(#1570): Generate ACIR for recursive aggregation
-        BlackBoxFunc::RecursiveAggregation => {
-            panic!("ICE: Cannot generate ACIR for recursive aggregation")
-        }
+        BlackBoxFunc::RecursiveAggregation => Err(InternalError::NotImplemented {
+            name: "recursive aggregation".to_string(),
+            location: None,
+        }),
     }
 }
 
@@ -897,12 +899,16 @@ fn black_box_expected_output_size(name: BlackBoxFunc) -> u32 {
 /// #[foreign(sha256)]
 /// fn sha256<N>(_input : [u8; N]) -> [u8; 32] {}
 /// ``
-fn intrinsics_check_inputs(name: BlackBoxFunc, inputs: &[FunctionInput]) {
-    let expected_num_inputs = match black_box_func_expected_input_size(name) {
+fn intrinsics_check_inputs(
+    name: BlackBoxFunc,
+    inputs: &[FunctionInput],
+) -> Result<(), InternalError> {
+    let expected_num_inputs = match black_box_func_expected_input_size(name)? {
         Some(expected_num_inputs) => expected_num_inputs,
-        None => return,
+        None => return Ok(()),
     };
     let got_num_inputs = inputs.len();
 
     assert_eq!(expected_num_inputs,inputs.len(),"Tried to call black box function {name} with {got_num_inputs} inputs, but this function's definition requires {expected_num_inputs} inputs");
+    Ok(())
 }
diff --git a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/sort.rs b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/sort.rs
index d645f683666..42a6a5f1a4a 100644
--- a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/sort.rs
+++ b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/acir_ir/sort.rs
@@ -1,6 +1,7 @@
-use acvm::acir::native_types::{Expression, Witness};
+use crate::errors::InternalError;
 
 use super::generated_acir::GeneratedAcir;
+use acvm::acir::native_types::{Expression, Witness};
 
 impl GeneratedAcir {
     // Generates gates for a sorting network
@@ -14,10 +15,10 @@ impl GeneratedAcir {
         in_expr: &[Expression],
         bits: &[Witness],
         generate_witness: bool,
-    ) -> (Vec<Witness>, Vec<Expression>) {
+    ) -> Result<(Vec<Witness>, Vec<Expression>), InternalError> {
         let n = in_expr.len();
         if n == 1 {
-            return (Vec::new(), in_expr.to_vec());
+            return Ok((Vec::new(), in_expr.to_vec()));
         }
         let n1 = n / 2;
 
@@ -47,14 +48,17 @@ impl GeneratedAcir {
             in_sub2.push(&in_expr[2 * i + 1] - &intermediate);
         }
         if n % 2 == 1 {
-            in_sub2.push(in_expr.last().unwrap().clone());
+            in_sub2.push(match in_expr.last() {
+                Some(in_expr) => in_expr.clone(),
+                None => return Err(InternalError::EmptyArray { location: self.current_location }),
+            });
         }
         let mut out_expr = Vec::new();
         // compute results for the sub networks
         let bits1 = if generate_witness { bits } else { &bits[n1 + (n - 1) / 2..] };
-        let (w1, b1) = self.permutation_layer(&in_sub1, bits1, generate_witness);
+        let (w1, b1) = self.permutation_layer(&in_sub1, bits1, generate_witness)?;
         let bits2 = if generate_witness { bits } else { &bits[n1 + (n - 1) / 2 + w1.len()..] };
-        let (w2, b2) = self.permutation_layer(&in_sub2, bits2, generate_witness);
+        let (w2, b2) = self.permutation_layer(&in_sub2, bits2, generate_witness)?;
         // apply the output switches
         for i in 0..(n - 1) / 2 {
             let c = if generate_witness { self.next_witness_index() } else { bits[n1 + i] };
@@ -64,38 +68,17 @@ impl GeneratedAcir {
             out_expr.push(&b2[i] - &intermediate);
         }
         if n % 2 == 0 {
-            out_expr.push(b1.last().unwrap().clone());
+            out_expr.push(match b1.last() {
+                Some(b1) => b1.clone(),
+                None => return Err(InternalError::EmptyArray { location: self.current_location }),
+            });
         }
-        out_expr.push(b2.last().unwrap().clone());
+        out_expr.push(match b2.last() {
+            Some(b2) => b2.clone(),
+            None => return Err(InternalError::EmptyArray { location: self.current_location }),
+        });
         conf.extend(w1);
         conf.extend(w2);
-        (conf, out_expr)
-    }
-
-    /// Returns an expression which represents a*b
-    /// If one has multiplicative term and the other is of degree one or more,
-    /// the function creates intermediate variables accordindly
-    fn mul_with_witness(&mut self, a: &Expression, b: &Expression) -> Expression {
-        let a_arith;
-        let a_arith = if !a.mul_terms.is_empty() && !b.is_const() {
-            let a_witness = self.get_or_create_witness(a);
-            a_arith = Expression::from(a_witness);
-            &a_arith
-        } else {
-            a
-        };
-        let b_arith;
-        let b_arith = if !b.mul_terms.is_empty() && !a.is_const() {
-            if a == b {
-                a_arith
-            } else {
-                let b_witness = self.get_or_create_witness(a);
-                b_arith = Expression::from(b_witness);
-                &b_arith
-            }
-        } else {
-            b
-        };
-        (a_arith * b_arith).expect("Both expressions are reduced to be degree<=1")
+        Ok((conf, out_expr))
     }
 }
diff --git a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/mod.rs b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/mod.rs
index 72194828f5c..da8409431ce 100644
--- a/crates/noirc_evaluator/src/ssa_refactor/acir_gen/mod.rs
+++ b/crates/noirc_evaluator/src/ssa_refactor/acir_gen/mod.rs
@@ -1,19 +1,11 @@
 //! This file holds the pass to convert from Noir's SSA IR to ACIR.
+mod acir_ir;
 
-use std::collections::HashMap;
-
-use crate::{
-    brillig::{
-        brillig_gen::brillig_fn::FunctionContext as BrilligFunctionContext,
-        brillig_ir::artifact::BrilligArtifact, Brillig,
-    },
-    errors::RuntimeError,
-};
+use std::collections::{HashMap, HashSet};
+use std::fmt::Debug;
+use std::ops::RangeInclusive;
 
-use self::acir_ir::{
-    acir_variable::{AcirContext, AcirType, AcirVar},
-    errors::AcirGenError,
-};
+use self::acir_ir::acir_variable::{AcirContext, AcirType, AcirVar};
 use super::{
     ir::{
         dfg::DataFlowGraph,
@@ -27,17 +19,17 @@ use super::{
     },
     ssa_gen::Ssa,
 };
+use crate::brillig::brillig_ir::BrilligContext;
+use crate::brillig::{brillig_gen::brillig_fn::FunctionContext as BrilligFunctionContext, Brillig};
+use crate::errors::{InternalError, RuntimeError};
+pub(crate) use acir_ir::generated_acir::GeneratedAcir;
 use acvm::{
-    acir::{brillig::Opcode, native_types::Expression},
+    acir::{brillig::Opcode, circuit::opcodes::BlockId, native_types::Expression},
     FieldElement,
 };
 use iter_extended::{try_vecmap, vecmap};
-
-pub(crate) use acir_ir::generated_acir::GeneratedAcir;
 use noirc_abi::AbiDistinctness;
 
-mod acir_ir;
-
 /// Context struct for the acir generation pass.
 /// May be similar to the Evaluator struct in the current SSA IR.
 struct Context {
@@ -55,19 +47,45 @@ struct Context {
 
     /// Manages and builds the `AcirVar`s to which the converted SSA values refer.
     acir_context: AcirContext,
+
+    /// Track initialized acir dynamic arrays
+    ///
+    /// An acir array must start with a MemoryInit ACIR opcodes
+    /// and then have MemoryOp opcodes
+    /// This set is used to ensure that a MemoryOp opcode is only pushed to the circuit
+    /// if there is already a MemoryInit opcode.
+    initialized_arrays: HashSet<BlockId>,
+}
+
+#[derive(Clone)]
+pub(crate) struct AcirDynamicArray {
+    /// Identification for the Acir dynamic array
+    /// This is essentially a ACIR pointer to the array
+    block_id: BlockId,
+    /// Length of the array
+    len: usize,
+}
+impl Debug for AcirDynamicArray {
+    fn fmt(&self, f: &mut core::fmt::Formatter<'_>) -> core::fmt::Result {
+        write!(f, "id: {}, len: {}", self.block_id.0, self.len)
+    }
 }
 
 #[derive(Debug, Clone)]
 pub(crate) enum AcirValue {
     Var(AcirVar, AcirType),
     Array(im::Vector<AcirValue>),
+    DynamicArray(AcirDynamicArray),
 }
 
 impl AcirValue {
-    fn into_var(self) -> AcirVar {
+    fn into_var(self) -> Result<AcirVar, InternalError> {
         match self {
-            AcirValue::Var(var, _) => var,
-            AcirValue::Array(_) => panic!("Called AcirValue::into_var on an array"),
+            AcirValue::Var(var, _) => Ok(var),
+            AcirValue::DynamicArray(_) | AcirValue::Array(_) => Err(InternalError::General {
+                message: "Called AcirValue::into_var on an array".to_string(),
+                location: None,
+            }),
         }
     }
 
@@ -75,6 +93,7 @@ impl AcirValue {
         match self {
             AcirValue::Var(var, typ) => vec![(var, typ)],
             AcirValue::Array(array) => array.into_iter().flat_map(AcirValue::flatten).collect(),
+            AcirValue::DynamicArray(_) => unimplemented!("Cannot flatten a dynamic array"),
         }
     }
 }
@@ -116,7 +135,12 @@ impl Context {
         let mut acir_context = AcirContext::default();
         let current_side_effects_enabled_var = acir_context.add_constant(FieldElement::one());
 
-        Context { ssa_values: HashMap::new(), current_side_effects_enabled_var, acir_context }
+        Context {
+            ssa_values: HashMap::new(),
+            current_side_effects_enabled_var,
+            acir_context,
+            initialized_arrays: HashSet::new(),
+        }
     }
 
     /// Converts SSA into ACIR
@@ -125,7 +149,7 @@ impl Context {
         ssa: Ssa,
         brillig: Brillig,
         allow_log_ops: bool,
-    ) -> Result<GeneratedAcir, AcirGenError> {
+    ) -> Result<GeneratedAcir, RuntimeError> {
         let main_func = ssa.main();
         match main_func.runtime() {
             RuntimeType::Acir => self.convert_acir_main(main_func, &ssa, brillig, allow_log_ops),
@@ -139,39 +163,44 @@ impl Context {
         ssa: &Ssa,
         brillig: Brillig,
         allow_log_ops: bool,
-    ) -> Result<GeneratedAcir, AcirGenError> {
+    ) -> Result<GeneratedAcir, RuntimeError> {
         let dfg = &main_func.dfg;
         let entry_block = &dfg[main_func.entry_block()];
-
-        self.convert_ssa_block_params(entry_block.parameters(), dfg)?;
+        let input_witness = self.convert_ssa_block_params(entry_block.parameters(), dfg)?;
 
         for instruction_id in entry_block.instructions() {
             self.convert_ssa_instruction(*instruction_id, dfg, ssa, &brillig, allow_log_ops)?;
         }
 
-        self.convert_ssa_return(entry_block.unwrap_terminator(), dfg);
+        self.convert_ssa_return(entry_block.unwrap_terminator(), dfg)?;
 
-        Ok(self.acir_context.finish())
+        Ok(self.acir_context.finish(input_witness.collect()))
     }
 
     fn convert_brillig_main(
         mut self,
         main_func: &Function,
         brillig: Brillig,
-    ) -> Result<GeneratedAcir, AcirGenError> {
+    ) -> Result<GeneratedAcir, RuntimeError> {
         let dfg = &main_func.dfg;
 
         let inputs = try_vecmap(dfg[main_func.entry_block()].parameters(), |param_id| {
             let typ = dfg.type_of_value(*param_id);
             self.create_value_from_type(&typ, &mut |this, _| Ok(this.acir_context.add_variable()))
         })?;
+        let witness_inputs = self.acir_context.extract_witness(&inputs);
 
         let outputs: Vec<AcirType> =
             vecmap(main_func.returns(), |result_id| dfg.type_of_value(*result_id).into());
 
-        let code = self.gen_brillig_for(main_func, &brillig);
+        let code = self.gen_brillig_for(main_func, &brillig)?;
 
-        let output_values = self.acir_context.brillig(None, code, inputs, outputs);
+        let output_values = self.acir_context.brillig(
+            self.current_side_effects_enabled_var,
+            code,
+            inputs,
+            outputs,
+        )?;
         let output_vars: Vec<_> = output_values
             .iter()
             .flat_map(|value| value.clone().flatten())
@@ -179,10 +208,10 @@ impl Context {
             .collect();
 
         for acir_var in output_vars {
-            self.acir_context.return_var(acir_var);
+            self.acir_context.return_var(acir_var)?;
         }
 
-        Ok(self.acir_context.finish())
+        Ok(self.acir_context.finish(witness_inputs))
     }
 
     /// Adds and binds `AcirVar`s for each numeric block parameter or block parameter array element.
@@ -190,24 +219,38 @@ impl Context {
         &mut self,
         params: &[ValueId],
         dfg: &DataFlowGraph,
-    ) -> Result<(), AcirGenError> {
+    ) -> Result<RangeInclusive<u32>, RuntimeError> {
+        // The first witness (if any) is the next one
+        let start_witness = self.acir_context.current_witness_index().0 + 1;
         for param_id in params {
             let typ = dfg.type_of_value(*param_id);
             let value = self.convert_ssa_block_param(&typ)?;
+            match &value {
+                AcirValue::Var(_, _) => (),
+                AcirValue::Array(values) => {
+                    let block_id = BlockId(param_id.to_usize() as u32);
+                    let v = vecmap(values, |v| v.clone());
+                    self.initialize_array(block_id, values.len(), Some(&v))?;
+                }
+                AcirValue::DynamicArray(_) => unreachable!(
+                    "The dynamic array type is created in Acir gen and therefore cannot be a block parameter"
+                ),
+            }
             self.ssa_values.insert(*param_id, value);
         }
-        Ok(())
+        let end_witness = self.acir_context.current_witness_index().0;
+        Ok(start_witness..=end_witness)
     }
 
-    fn convert_ssa_block_param(&mut self, param_type: &Type) -> Result<AcirValue, AcirGenError> {
+    fn convert_ssa_block_param(&mut self, param_type: &Type) -> Result<AcirValue, RuntimeError> {
         self.create_value_from_type(param_type, &mut |this, typ| this.add_numeric_input_var(&typ))
     }
 
     fn create_value_from_type(
         &mut self,
         param_type: &Type,
-        make_var: &mut impl FnMut(&mut Self, NumericType) -> Result<AcirVar, AcirGenError>,
-    ) -> Result<AcirValue, AcirGenError> {
+        make_var: &mut impl FnMut(&mut Self, NumericType) -> Result<AcirVar, RuntimeError>,
+    ) -> Result<AcirValue, RuntimeError> {
         match param_type {
             Type::Numeric(numeric_type) => {
                 let typ = AcirType::new(*numeric_type);
@@ -236,7 +279,7 @@ impl Context {
     fn add_numeric_input_var(
         &mut self,
         numeric_type: &NumericType,
-    ) -> Result<AcirVar, AcirGenError> {
+    ) -> Result<AcirVar, RuntimeError> {
         let acir_var = self.acir_context.add_variable();
         if matches!(numeric_type, NumericType::Signed { .. } | NumericType::Unsigned { .. }) {
             self.acir_context.range_constrain_var(acir_var, numeric_type)?;
@@ -252,7 +295,7 @@ impl Context {
         ssa: &Ssa,
         brillig: &Brillig,
         allow_log_ops: bool,
-    ) -> Result<(), AcirGenError> {
+    ) -> Result<(), RuntimeError> {
         let instruction = &dfg[instruction_id];
         self.acir_context.set_location(dfg.get_location(&instruction_id));
         match instruction {
@@ -261,7 +304,7 @@ impl Context {
                 self.define_result_var(dfg, instruction_id, result_acir_var);
             }
             Instruction::Constrain(value_id) => {
-                let constrain_condition = self.convert_numeric_value(*value_id, dfg);
+                let constrain_condition = self.convert_numeric_value(*value_id, dfg)?;
                 self.acir_context.assert_eq_one(constrain_condition)?;
             }
             Instruction::Cast(value_id, typ) => {
@@ -280,11 +323,11 @@ impl Context {
                             RuntimeType::Brillig => {
                                 let inputs = vecmap(arguments, |arg| self.convert_value(*arg, dfg));
 
-                                let code = self.gen_brillig_for(func, brillig);
+                                let code = self.gen_brillig_for(func, brillig)?;
 
                                 let outputs: Vec<AcirType> = vecmap(result_ids, |result_id| dfg.type_of_value(*result_id).into());
 
-                                let output_values = self.acir_context.brillig(Some(self.current_side_effects_enabled_var), code, inputs, outputs);
+                                let output_values = self.acir_context.brillig(self.current_side_effects_enabled_var, code, inputs, outputs)?;
 
                                 // Compiler sanity check
                                 assert_eq!(result_ids.len(), output_values.len(), "ICE: The number of Brillig output values should match the result ids in SSA");
@@ -332,7 +375,7 @@ impl Context {
                 self.define_result_var(dfg, instruction_id, result_acir_var);
             }
             Instruction::EnableSideEffects { condition } => {
-                let acir_var = self.convert_numeric_value(*condition, dfg);
+                let acir_var = self.convert_numeric_value(*condition, dfg)?;
                 self.current_side_effects_enabled_var = acir_var;
             }
             Instruction::ArrayGet { array, index } => {
@@ -355,22 +398,33 @@ impl Context {
         Ok(())
     }
 
-    fn gen_brillig_for(&self, func: &Function, brillig: &Brillig) -> Vec<Opcode> {
+    fn gen_brillig_for(
+        &self,
+        func: &Function,
+        brillig: &Brillig,
+    ) -> Result<Vec<Opcode>, InternalError> {
         // Create the entry point artifact
-        let mut entry_point = BrilligArtifact::new_entry_point_artifact(
+        let mut entry_point = BrilligContext::new_entry_point_artifact(
             BrilligFunctionContext::parameters(func),
             BrilligFunctionContext::return_values(func),
             BrilligFunctionContext::function_id_to_function_label(func.id()),
         );
         // Link the entry point with all dependencies
         while let Some(unresolved_fn_label) = entry_point.first_unresolved_function_call() {
-            let artifact = &brillig
-                .find_by_function_label(unresolved_fn_label.clone())
-                .unwrap_or_else(|| panic!("Cannot find linked fn {unresolved_fn_label}"));
+            let artifact = &brillig.find_by_function_label(unresolved_fn_label.clone());
+            let artifact = match artifact {
+                Some(artifact) => artifact,
+                None => {
+                    return Err(InternalError::General {
+                        message: format!("Cannot find linked fn {unresolved_fn_label}"),
+                        location: None,
+                    })
+                }
+            };
             entry_point.link_with(artifact);
         }
         // Generate the final bytecode
-        entry_point.finish()
+        Ok(entry_point.finish())
     }
 
     /// Handles an ArrayGet or ArraySet instruction.
@@ -383,36 +437,206 @@ impl Context {
         index: ValueId,
         store_value: Option<ValueId>,
         dfg: &DataFlowGraph,
-    ) -> Result<(), AcirGenError> {
-        let array = self.convert_array_value(array, dfg);
-        let index = dfg
-            .get_numeric_constant(index)
-            .expect("Expected array index to be a known constant")
-            .try_to_u64()
-            .expect("Expected array index to fit into a u64") as usize;
-
-        let array_size = array.len();
-        if index >= array_size {
-            // Ignore the error if side effects are disabled.
-            if self.acir_context.is_constant_one(&self.current_side_effects_enabled_var) {
-                let location = self.acir_context.get_location();
-                return Err(AcirGenError::IndexOutOfBounds { index, array_size, location });
-            }
-            let result_type = dfg.type_of_value(dfg.instruction_results(instruction)[0]);
-            let value = self.create_default_value(&result_type)?;
-            self.define_result(dfg, instruction, value);
-            return Ok(());
+    ) -> Result<(), RuntimeError> {
+        let index_const = dfg.get_numeric_constant(index);
+
+        match self.convert_value(array, dfg) {
+            AcirValue::Var(acir_var, _) => {
+                return Err(RuntimeError::InternalError(InternalError::UnExpected {
+                    expected: "an array value".to_string(),
+                    found: format!("{acir_var:?}"),
+                    location: self.acir_context.get_location(),
+                }))
+            }
+            AcirValue::Array(array) => {
+                if let Some(index_const) = index_const {
+                    let array_size = array.len();
+                    let index = match index_const.try_to_u64() {
+                        Some(index_const) => index_const as usize,
+                        None => {
+                            let location = self.acir_context.get_location();
+                            return Err(RuntimeError::TypeConversion {
+                                from: "array index".to_string(),
+                                into: "u64".to_string(),
+                                location,
+                            });
+                        }
+                    };
+                    if index >= array_size {
+                        // Ignore the error if side effects are disabled.
+                        if self.acir_context.is_constant_one(&self.current_side_effects_enabled_var)
+                        {
+                            let location = self.acir_context.get_location();
+                            return Err(RuntimeError::IndexOutOfBounds {
+                                index,
+                                array_size,
+                                location,
+                            });
+                        }
+                        let result_type =
+                            dfg.type_of_value(dfg.instruction_results(instruction)[0]);
+                        let value = self.create_default_value(&result_type)?;
+                        self.define_result(dfg, instruction, value);
+                        return Ok(());
+                    }
+
+                    let value = match store_value {
+                        Some(store_value) => {
+                            let store_value = self.convert_value(store_value, dfg);
+                            AcirValue::Array(array.update(index, store_value))
+                        }
+                        None => array[index].clone(),
+                    };
+
+                    self.define_result(dfg, instruction, value);
+                    return Ok(());
+                }
+            }
+            AcirValue::DynamicArray(_) => (),
+        }
+
+        if let Some(store) = store_value {
+            self.array_set(instruction, array, index, store, dfg)?;
+        } else {
+            self.array_get(instruction, array, index, dfg)?;
+        }
+
+        Ok(())
+    }
+
+    /// Generates a read opcode for the array
+    fn array_get(
+        &mut self,
+        instruction: InstructionId,
+        array: ValueId,
+        index: ValueId,
+        dfg: &DataFlowGraph,
+    ) -> Result<(), RuntimeError> {
+        let array = dfg.resolve(array);
+        let block_id = BlockId(array.to_usize() as u32);
+        if !self.initialized_arrays.contains(&block_id) {
+            match &dfg[array] {
+                Value::Array { array, .. } => {
+                    let values: Vec<AcirValue> =
+                        array.iter().map(|i| self.convert_value(*i, dfg)).collect();
+                    self.initialize_array(block_id, array.len(), Some(&values))?;
+                }
+                _ => {
+                    return Err(RuntimeError::UnInitialized {
+                        name: "array".to_string(),
+                        location: self.acir_context.get_location(),
+                    })
+                }
+            }
         }
 
-        let value = match store_value {
-            Some(store_value) => {
-                let store_value = self.convert_value(store_value, dfg);
-                AcirValue::Array(array.update(index, store_value))
+        let index_var = self.convert_value(index, dfg).into_var()?;
+        let read = self.acir_context.read_from_memory(block_id, &index_var)?;
+        let typ = match dfg.type_of_value(array) {
+            Type::Array(typ, _) => {
+                if typ.len() != 1 {
+                    unimplemented!(
+                        "Non-const array indices is not implemented for non-homogenous array"
+                    );
+                }
+                typ[0].clone()
             }
-            None => array[index].clone(),
+            _ => unreachable!("ICE - expected an array"),
+        };
+        let typ = AcirType::from(typ);
+        self.define_result(dfg, instruction, AcirValue::Var(read, typ));
+        Ok(())
+    }
+
+    /// Copy the array and generates a write opcode on the new array
+    ///
+    /// Note: Copying the array is inefficient and is not the way we want to do it in the end.
+    fn array_set(
+        &mut self,
+        instruction: InstructionId,
+        array: ValueId,
+        index: ValueId,
+        store_value: ValueId,
+        dfg: &DataFlowGraph,
+    ) -> Result<(), InternalError> {
+        // Fetch the internal SSA ID for the array
+        let array = dfg.resolve(array);
+        let array_ssa_id = array.to_usize() as u32;
+
+        // Use the SSA ID to create a block ID
+        // There is currently a 1-1 mapping from array SSA ID to block ID
+        let block_id = BlockId(array_ssa_id);
+
+        // Every array has a length in its type, so we fetch that from
+        // the SSA IR.
+        let len = match dfg.type_of_value(array) {
+            Type::Array(_, len) => len,
+            _ => unreachable!("ICE - expected an array"),
         };
 
-        self.define_result(dfg, instruction, value);
+        // Check if the array has already been initialized in ACIR gen
+        // if not, we initialize it using the values from SSA
+        let already_initialized = self.initialized_arrays.contains(&block_id);
+        if !already_initialized {
+            match &dfg[array] {
+                Value::Array { array, .. } => {
+                    let values: Vec<AcirValue> =
+                        array.iter().map(|i| self.convert_value(*i, dfg)).collect();
+                    self.initialize_array(block_id, array.len(), Some(&values))?;
+                }
+                _ => {
+                    return Err(InternalError::General {
+                        message: format!("Array {array} should be initialized"),
+                        location: self.acir_context.get_location(),
+                    })
+                }
+            }
+        }
+
+        // Since array_set creates a new array, we create a new block ID for this
+        // array.
+        let result_id = dfg
+            .instruction_results(instruction)
+            .first()
+            .expect("Array set does not have one result");
+        let result_array_id = result_id.to_usize() as u32;
+        let result_block_id = BlockId(result_array_id);
+
+        // Initialize the new array with zero values
+        self.initialize_array(result_block_id, len, None)?;
+
+        // Copy the values from the old array into the newly created zeroed array
+        for i in 0..len {
+            let index = AcirValue::Var(
+                self.acir_context.add_constant(FieldElement::from(i as u128)),
+                AcirType::NumericType(NumericType::NativeField),
+            );
+            let var = index.into_var()?;
+            let read = self.acir_context.read_from_memory(block_id, &var)?;
+            self.acir_context.write_to_memory(result_block_id, &var, &read)?;
+        }
+
+        // Write the new value into the new array at the specified index
+        let index_var = self.convert_value(index, dfg).into_var()?;
+        let value_var = self.convert_value(store_value, dfg).into_var()?;
+        self.acir_context.write_to_memory(result_block_id, &index_var, &value_var)?;
+
+        let result_value =
+            AcirValue::DynamicArray(AcirDynamicArray { block_id: result_block_id, len });
+        self.define_result(dfg, instruction, result_value);
+        Ok(())
+    }
+
+    /// Initializes an array with the given values and caches the fact that we
+    /// have initialized this array.
+    fn initialize_array(
+        &mut self,
+        array: BlockId,
+        len: usize,
+        values: Option<&[AcirValue]>,
+    ) -> Result<(), InternalError> {
+        self.acir_context.initialize_array(array, len, values)?;
+        self.initialized_arrays.insert(array);
         Ok(())
     }
 
@@ -440,7 +664,11 @@ impl Context {
     }
 
     /// Converts an SSA terminator's return values into their ACIR representations
-    fn convert_ssa_return(&mut self, terminator: &TerminatorInstruction, dfg: &DataFlowGraph) {
+    fn convert_ssa_return(
+        &mut self,
+        terminator: &TerminatorInstruction,
+        dfg: &DataFlowGraph,
+    ) -> Result<(), InternalError> {
         let return_values = match terminator {
             TerminatorInstruction::Return { return_values } => return_values,
             _ => unreachable!("ICE: Program must have a singular return"),
@@ -450,8 +678,9 @@ impl Context {
         // will expand the array if there is one.
         let return_acir_vars = self.flatten_value_list(return_values, dfg);
         for acir_var in return_acir_vars {
-            self.acir_context.return_var(acir_var);
+            self.acir_context.return_var(acir_var)?;
         }
+        Ok(())
     }
 
     /// Gets the cached `AcirVar` that was converted from the corresponding `ValueId`. If it does
@@ -495,21 +724,25 @@ impl Context {
         acir_value
     }
 
-    fn convert_array_value(
+    fn convert_numeric_value(
         &mut self,
         value_id: ValueId,
         dfg: &DataFlowGraph,
-    ) -> im::Vector<AcirValue> {
+    ) -> Result<AcirVar, InternalError> {
         match self.convert_value(value_id, dfg) {
-            AcirValue::Var(acir_var, _) => panic!("Expected an array value, found: {acir_var:?}"),
-            AcirValue::Array(array) => array,
-        }
-    }
-
-    fn convert_numeric_value(&mut self, value_id: ValueId, dfg: &DataFlowGraph) -> AcirVar {
-        match self.convert_value(value_id, dfg) {
-            AcirValue::Var(acir_var, _) => acir_var,
-            AcirValue::Array(array) => panic!("Expected a numeric value, found: {array:?}"),
+            AcirValue::Var(acir_var, _) => Ok(acir_var),
+            AcirValue::Array(array) => {
+                return Err(InternalError::UnExpected {
+                    expected: "a numeric value".to_string(),
+                    found: format!("{array:?}"),
+                    location: self.acir_context.get_location(),
+                })
+            }
+            AcirValue::DynamicArray(_) => Err(InternalError::UnExpected {
+                expected: "a numeric value".to_string(),
+                found: "an array".to_string(),
+                location: self.acir_context.get_location(),
+            }),
         }
     }
 
@@ -518,9 +751,9 @@ impl Context {
         &mut self,
         binary: &Binary,
         dfg: &DataFlowGraph,
-    ) -> Result<AcirVar, AcirGenError> {
-        let lhs = self.convert_numeric_value(binary.lhs, dfg);
-        let rhs = self.convert_numeric_value(binary.rhs, dfg);
+    ) -> Result<AcirVar, RuntimeError> {
+        let lhs = self.convert_numeric_value(binary.lhs, dfg)?;
+        let rhs = self.convert_numeric_value(binary.rhs, dfg)?;
 
         let binary_type = self.type_of_binary_operation(binary, dfg);
         match &binary_type {
@@ -531,7 +764,7 @@ impl Context {
                 // truncation technique: result % 2^bit_size to be valid.
                 let max_integer_bit_size = FieldElement::max_num_bits() / 2;
                 if *bit_size > max_integer_bit_size {
-                    return Err(AcirGenError::UnsupportedIntegerSize {
+                    return Err(RuntimeError::UnsupportedIntegerSize {
                         num_bits: *bit_size,
                         max_num_bits: max_integer_bit_size,
                         location: self.acir_context.get_location(),
@@ -548,7 +781,12 @@ impl Context {
             BinaryOp::Add => self.acir_context.add_var(lhs, rhs),
             BinaryOp::Sub => self.acir_context.sub_var(lhs, rhs),
             BinaryOp::Mul => self.acir_context.mul_var(lhs, rhs),
-            BinaryOp::Div => self.acir_context.div_var(lhs, rhs, binary_type),
+            BinaryOp::Div => self.acir_context.div_var(
+                lhs,
+                rhs,
+                binary_type,
+                self.current_side_effects_enabled_var,
+            ),
             // Note: that this produces unnecessary constraints when
             // this Eq instruction is being used for a constrain statement
             BinaryOp::Eq => self.acir_context.eq_var(lhs, rhs),
@@ -559,11 +797,21 @@ impl Context {
                 self.current_side_effects_enabled_var,
             ),
             BinaryOp::Shl => self.acir_context.shift_left_var(lhs, rhs, binary_type),
-            BinaryOp::Shr => self.acir_context.shift_right_var(lhs, rhs, binary_type),
+            BinaryOp::Shr => self.acir_context.shift_right_var(
+                lhs,
+                rhs,
+                binary_type,
+                self.current_side_effects_enabled_var,
+            ),
             BinaryOp::Xor => self.acir_context.xor_var(lhs, rhs, binary_type),
             BinaryOp::And => self.acir_context.and_var(lhs, rhs, binary_type),
             BinaryOp::Or => self.acir_context.or_var(lhs, rhs, binary_type),
-            BinaryOp::Mod => self.acir_context.modulo_var(lhs, rhs, bit_count),
+            BinaryOp::Mod => self.acir_context.modulo_var(
+                lhs,
+                rhs,
+                bit_count,
+                self.current_side_effects_enabled_var,
+            ),
         }
     }
 
@@ -624,10 +872,12 @@ impl Context {
         value_id: &ValueId,
         typ: &Type,
         dfg: &DataFlowGraph,
-    ) -> Result<AcirVar, AcirGenError> {
+    ) -> Result<AcirVar, RuntimeError> {
         let (variable, incoming_type) = match self.convert_value(*value_id, dfg) {
             AcirValue::Var(variable, typ) => (variable, typ),
-            AcirValue::Array(_) => unreachable!("Cast is only applied to numerics"),
+            AcirValue::DynamicArray(_) | AcirValue::Array(_) => {
+                unreachable!("Cast is only applied to numerics")
+            }
         };
         let target_numeric = match typ {
             Type::Numeric(numeric) => numeric,
@@ -660,8 +910,8 @@ impl Context {
         bit_size: u32,
         max_bit_size: u32,
         dfg: &DataFlowGraph,
-    ) -> Result<AcirVar, AcirGenError> {
-        let mut var = self.convert_numeric_value(value_id, dfg);
+    ) -> Result<AcirVar, RuntimeError> {
+        let mut var = self.convert_numeric_value(value_id, dfg)?;
         let truncation_target = match &dfg[value_id] {
             Value::Instruction { instruction, .. } => &dfg[*instruction],
             _ => unreachable!("ICE: Truncates are only ever applied to the result of a binary op"),
@@ -688,7 +938,7 @@ impl Context {
         dfg: &DataFlowGraph,
         allow_log_ops: bool,
         result_ids: &[ValueId],
-    ) -> Result<Vec<AcirValue>, AcirGenError> {
+    ) -> Result<Vec<AcirValue>, RuntimeError> {
         match intrinsic {
             Intrinsic::BlackBox(black_box) => {
                 let inputs = vecmap(arguments, |arg| self.convert_value(*arg, dfg));
@@ -698,16 +948,16 @@ impl Context {
                 Ok(Self::convert_vars_to_values(vars, dfg, result_ids))
             }
             Intrinsic::ToRadix(endian) => {
-                let field = self.convert_value(arguments[0], dfg).into_var();
-                let radix = self.convert_value(arguments[1], dfg).into_var();
-                let limb_size = self.convert_value(arguments[2], dfg).into_var();
+                let field = self.convert_value(arguments[0], dfg).into_var()?;
+                let radix = self.convert_value(arguments[1], dfg).into_var()?;
+                let limb_size = self.convert_value(arguments[2], dfg).into_var()?;
                 let result_type = Self::array_element_type(dfg, result_ids[0]);
 
                 self.acir_context.radix_decompose(endian, field, radix, limb_size, result_type)
             }
             Intrinsic::ToBits(endian) => {
-                let field = self.convert_value(arguments[0], dfg).into_var();
-                let bit_size = self.convert_value(arguments[1], dfg).into_var();
+                let field = self.convert_value(arguments[0], dfg).into_var()?;
+                let bit_size = self.convert_value(arguments[1], dfg).into_var()?;
                 let result_type = Self::array_element_type(dfg, result_ids[0]);
 
                 self.acir_context.bit_decompose(endian, field, bit_size, result_type)
@@ -739,11 +989,21 @@ impl Context {
                     }
                 }
                 // Generate the sorted output variables
-                let out_vars =
-                    self.acir_context.sort(input_vars, bit_size).expect("Could not sort");
+                let out_vars = self
+                    .acir_context
+                    .sort(input_vars, bit_size, self.current_side_effects_enabled_var)
+                    .expect("Could not sort");
 
                 Ok(Self::convert_vars_to_values(out_vars, dfg, result_ids))
             }
+            Intrinsic::ArrayLen => {
+                let len = match self.convert_value(arguments[0], dfg) {
+                    AcirValue::Var(_, _) =>  unreachable!("Non-array passed to array.len() method"),
+                    AcirValue::Array(values) => (values.len() as u128).into(),
+                    AcirValue::DynamicArray(array) => (array.len as u128).into(),
+                };
+                Ok(vec![AcirValue::Var(self.acir_context.add_constant(len), AcirType::field())])
+            }
             _ => todo!("expected a black box function"),
         }
     }
@@ -827,7 +1087,7 @@ impl Context {
     }
 
     /// Creates a default, meaningless value meant only to be a valid value of the given type.
-    fn create_default_value(&mut self, param_type: &Type) -> Result<AcirValue, AcirGenError> {
+    fn create_default_value(&mut self, param_type: &Type) -> Result<AcirValue, RuntimeError> {
         self.create_value_from_type(param_type, &mut |this, _| {
             Ok(this.acir_context.add_constant(FieldElement::zero()))
         })
@@ -868,7 +1128,8 @@ mod tests {
         let one = builder.field_constant(FieldElement::one());
 
         let element_type = Rc::new(vec![Type::field()]);
-        let array = builder.array_constant(im::Vector::unit(one), element_type);
+        let array_type = Type::Array(element_type, 1);
+        let array = builder.array_constant(im::Vector::unit(one), array_type);
 
         builder.terminate_with_return(vec![array]);
 
diff --git a/crates/noirc_evaluator/src/ssa_refactor/ir/dfg.rs b/crates/noirc_evaluator/src/ssa_refactor/ir/dfg.rs
index 5c9fde280a8..caf65c85a7e 100644
--- a/crates/noirc_evaluator/src/ssa_refactor/ir/dfg.rs
+++ b/crates/noirc_evaluator/src/ssa_refactor/ir/dfg.rs
@@ -1,4 +1,4 @@
-use std::{borrow::Cow, collections::HashMap, rc::Rc};
+use std::{borrow::Cow, collections::HashMap};
 
 use crate::ssa_refactor::ir::instruction::SimplifyResult;
 
@@ -9,7 +9,7 @@ use super::{
         Instruction, InstructionId, InstructionResultType, Intrinsic, TerminatorInstruction,
     },
     map::DenseMap,
-    types::{CompositeType, Type},
+    types::Type,
     value::{Value, ValueId},
 };
 
@@ -226,12 +226,9 @@ impl DataFlowGraph {
     }
 
     /// Create a new constant array value from the given elements
-    pub(crate) fn make_array(
-        &mut self,
-        array: im::Vector<ValueId>,
-        element_type: Rc<CompositeType>,
-    ) -> ValueId {
-        self.make_value(Value::Array { array, element_type })
+    pub(crate) fn make_array(&mut self, array: im::Vector<ValueId>, typ: Type) -> ValueId {
+        assert!(matches!(typ, Type::Array(..) | Type::Slice(_)));
+        self.make_value(Value::Array { array, typ })
     }
 
     /// Gets or creates a ValueId for the given FunctionId.
@@ -369,27 +366,19 @@ impl DataFlowGraph {
 
     /// Returns the Value::Array associated with this ValueId if it refers to an array constant.
     /// Otherwise, this returns None.
-    pub(crate) fn get_array_constant(
-        &self,
-        value: ValueId,
-    ) -> Option<(im::Vector<ValueId>, Rc<CompositeType>)> {
+    pub(crate) fn get_array_constant(&self, value: ValueId) -> Option<(im::Vector<ValueId>, Type)> {
         match &self.values[self.resolve(value)] {
             // Vectors are shared, so cloning them is cheap
-            Value::Array { array, element_type } => Some((array.clone(), element_type.clone())),
+            Value::Array { array, typ } => Some((array.clone(), typ.clone())),
             _ => None,
         }
     }
 
-    /// Returns the Type::Array associated with this ValueId if it refers to an array parameter.
-    /// Otherwise, this returns None.
-    pub(crate) fn get_array_parameter_type(
-        &self,
-        value: ValueId,
-    ) -> Option<(Rc<CompositeType>, usize)> {
-        match &self.values[self.resolve(value)] {
-            Value::Param { typ: Type::Array(element_type, size), .. } => {
-                Some((element_type.clone(), *size))
-            }
+    /// If this value is an array, return the length of the array as indicated by its type.
+    /// Otherwise, return None.
+    pub(crate) fn try_get_array_length(&self, value: ValueId) -> Option<usize> {
+        match self.type_of_value(value) {
+            Type::Array(_, length) => Some(length),
             _ => None,
         }
     }
diff --git a/crates/noirc_evaluator/src/ssa_refactor/ir/function.rs b/crates/noirc_evaluator/src/ssa_refactor/ir/function.rs
index 76395ea74ab..ab04c1497bd 100644
--- a/crates/noirc_evaluator/src/ssa_refactor/ir/function.rs
+++ b/crates/noirc_evaluator/src/ssa_refactor/ir/function.rs
@@ -1,5 +1,7 @@
 use std::collections::HashSet;
 
+use iter_extended::vecmap;
+
 use super::basic_block::BasicBlockId;
 use super::dfg::DataFlowGraph;
 use super::instruction::TerminatorInstruction;
@@ -116,6 +118,12 @@ impl Function {
         }
         blocks
     }
+
+    pub(crate) fn signature(&self) -> Signature {
+        let params = vecmap(self.parameters(), |param| self.dfg.type_of_value(*param));
+        let returns = vecmap(self.returns(), |ret| self.dfg.type_of_value(*ret));
+        Signature { params, returns }
+    }
 }
 
 impl std::fmt::Display for RuntimeType {
@@ -133,7 +141,7 @@ impl std::fmt::Display for RuntimeType {
 /// within Call instructions.
 pub(crate) type FunctionId = Id<Function>;
 
-#[derive(Debug, Default, Clone)]
+#[derive(Debug, Default, Clone, PartialEq, Eq, Hash, Ord, PartialOrd)]
 pub(crate) struct Signature {
     pub(crate) params: Vec<Type>,
     pub(crate) returns: Vec<Type>,
diff --git a/crates/noirc_evaluator/src/ssa_refactor/ir/function_inserter.rs b/crates/noirc_evaluator/src/ssa_refactor/ir/function_inserter.rs
index 22a1399ae79..38dcfbbb168 100644
--- a/crates/noirc_evaluator/src/ssa_refactor/ir/function_inserter.rs
+++ b/crates/noirc_evaluator/src/ssa_refactor/ir/function_inserter.rs
@@ -33,11 +33,11 @@ impl<'f> FunctionInserter<'f> {
         match self.values.get(&value) {
             Some(value) => *value,
             None => match &self.function.dfg[value] {
-                super::value::Value::Array { array, element_type } => {
+                super::value::Value::Array { array, typ } => {
                     let array = array.clone();
-                    let element_type = element_type.clone();
+                    let typ = typ.clone();
                     let new_array = array.iter().map(|id| self.resolve(*id)).collect();
-                    let new_id = self.function.dfg.make_array(new_array, element_type);
+                    let new_id = self.function.dfg.make_array(new_array, typ);
                     self.values.insert(value, new_id);
                     new_id
                 }
diff --git a/crates/noirc_evaluator/src/ssa_refactor/ir/instruction.rs b/crates/noirc_evaluator/src/ssa_refactor/ir/instruction.rs
index 25f06375732..b7a3ea02ae9 100644
--- a/crates/noirc_evaluator/src/ssa_refactor/ir/instruction.rs
+++ b/crates/noirc_evaluator/src/ssa_refactor/ir/instruction.rs
@@ -420,15 +420,9 @@ fn simplify_call(func: ValueId, arguments: &[ValueId], dfg: &mut DataFlowGraph)
         Intrinsic::ArrayLen => {
             let slice = dfg.get_array_constant(arguments[0]);
             if let Some((slice, _)) = slice {
-                let slice_len =
-                    dfg.make_constant(FieldElement::from(slice.len() as u128), Type::field());
-                SimplifiedTo(slice_len)
-            } else if let Some((_, slice_len)) = dfg.get_array_parameter_type(arguments[0]) {
-                let slice_len = dfg.make_constant(
-                    FieldElement::from(slice_len as u128),
-                    Type::Numeric(NumericType::NativeField),
-                );
-                SimplifiedTo(slice_len)
+                SimplifiedTo(dfg.make_constant((slice.len() as u128).into(), Type::field()))
+            } else if let Some(length) = dfg.try_get_array_length(arguments[0]) {
+                SimplifiedTo(dfg.make_constant((length as u128).into(), Type::field()))
             } else {
                 None
             }
@@ -534,9 +528,11 @@ fn constant_to_radix(
     while limbs.len() < limb_count_with_padding as usize {
         limbs.push(FieldElement::zero());
     }
-    let result_constants =
+    let result_constants: im::Vector<ValueId> =
         limbs.into_iter().map(|limb| dfg.make_constant(limb, Type::unsigned(bit_size))).collect();
-    dfg.make_array(result_constants, Rc::new(vec![Type::unsigned(bit_size)]))
+
+    let typ = Type::Array(Rc::new(vec![Type::unsigned(bit_size)]), result_constants.len());
+    dfg.make_array(result_constants, typ)
 }
 
 /// The possible return values for Instruction::return_types
@@ -775,63 +771,67 @@ impl Binary {
         rhs: FieldElement,
         mut operand_type: Type,
     ) -> Option<Id<Value>> {
-        let value = match self.operator {
-            BinaryOp::Add => lhs + rhs,
-            BinaryOp::Sub => lhs - rhs,
-            BinaryOp::Mul => lhs * rhs,
-            BinaryOp::Div => lhs / rhs,
-            BinaryOp::Eq => {
-                operand_type = Type::bool();
-                (lhs == rhs).into()
-            }
-            BinaryOp::Lt => {
-                operand_type = Type::bool();
-                (lhs < rhs).into()
+        let value = match &operand_type {
+            Type::Numeric(NumericType::NativeField) => {
+                self.operator.get_field_function()?(lhs, rhs)
             }
+            Type::Numeric(NumericType::Unsigned { bit_size }) => {
+                let function = self.operator.get_u128_function();
 
-            // The rest of the operators we must try to convert to u128 first
-            BinaryOp::Mod => self.eval_constant_u128_operations(lhs, rhs)?,
-            BinaryOp::And => self.eval_constant_u128_operations(lhs, rhs)?,
-            BinaryOp::Or => self.eval_constant_u128_operations(lhs, rhs)?,
-            BinaryOp::Xor => self.eval_constant_u128_operations(lhs, rhs)?,
-            BinaryOp::Shl => self.eval_constant_u128_operations(lhs, rhs)?,
-            BinaryOp::Shr => self.eval_constant_u128_operations(lhs, rhs)?,
+                let lhs = truncate(lhs.try_into_u128()?, *bit_size);
+                let rhs = truncate(rhs.try_into_u128()?, *bit_size);
+                let result = function(lhs, rhs)?;
+                truncate(result, *bit_size).into()
+            }
+            _ => return None,
         };
+
+        if matches!(self.operator, BinaryOp::Eq | BinaryOp::Lt) {
+            operand_type = Type::bool();
+        }
+
         Some(dfg.make_constant(value, operand_type))
     }
+}
 
-    /// Try to evaluate the given operands as u128s for operators that are only valid on u128s,
-    /// like the bitwise operators and modulus.
-    fn eval_constant_u128_operations(
-        &self,
-        lhs: FieldElement,
-        rhs: FieldElement,
-    ) -> Option<FieldElement> {
-        let lhs = lhs.try_into_u128()?;
-        let rhs = rhs.try_into_u128()?;
-        match self.operator {
-            BinaryOp::Mod => Some((lhs % rhs).into()),
-            BinaryOp::And => Some((lhs & rhs).into()),
-            BinaryOp::Or => Some((lhs | rhs).into()),
-            BinaryOp::Shr => Some((lhs >> rhs).into()),
-            // Check for overflow and return None if anything does overflow
-            BinaryOp::Shl => {
-                let rhs = rhs.try_into().ok()?;
-                lhs.checked_shl(rhs).map(Into::into)
-            }
+fn truncate(int: u128, bit_size: u32) -> u128 {
+    let max = 2u128.pow(bit_size);
+    int % max
+}
 
-            // Converting a field xor to a u128 xor would be incorrect since we wouldn't have the
-            // extra bits of the field. So we don't optimize it here.
+impl BinaryOp {
+    fn get_field_function(self) -> Option<fn(FieldElement, FieldElement) -> FieldElement> {
+        match self {
+            BinaryOp::Add => Some(std::ops::Add::add),
+            BinaryOp::Sub => Some(std::ops::Sub::sub),
+            BinaryOp::Mul => Some(std::ops::Mul::mul),
+            BinaryOp::Div => Some(std::ops::Div::div),
+            BinaryOp::Eq => Some(|x, y| (x == y).into()),
+            BinaryOp::Lt => Some(|x, y| (x < y).into()),
+            // Bitwise operators are unsupported for Fields
+            BinaryOp::Mod => None,
+            BinaryOp::And => None,
+            BinaryOp::Or => None,
             BinaryOp::Xor => None,
+            BinaryOp::Shl => None,
+            BinaryOp::Shr => None,
+        }
+    }
 
-            op @ (BinaryOp::Add
-            | BinaryOp::Sub
-            | BinaryOp::Mul
-            | BinaryOp::Div
-            | BinaryOp::Eq
-            | BinaryOp::Lt) => panic!(
-                "eval_constant_u128_operations invalid for {op:?} use eval_constants instead"
-            ),
+    fn get_u128_function(self) -> fn(u128, u128) -> Option<u128> {
+        match self {
+            BinaryOp::Add => u128::checked_add,
+            BinaryOp::Sub => u128::checked_sub,
+            BinaryOp::Mul => u128::checked_mul,
+            BinaryOp::Div => u128::checked_div,
+            BinaryOp::Mod => u128::checked_rem,
+            BinaryOp::And => |x, y| Some(x & y),
+            BinaryOp::Or => |x, y| Some(x | y),
+            BinaryOp::Xor => |x, y| Some(x ^ y),
+            BinaryOp::Shl => |x, y| x.checked_shl(y.try_into().ok()?),
+            BinaryOp::Shr => |x, y| Some(x >> y),
+            BinaryOp::Eq => |x, y| Some((x == y) as u128),
+            BinaryOp::Lt => |x, y| Some((x < y) as u128),
         }
     }
 }
diff --git a/crates/noirc_evaluator/src/ssa_refactor/ir/types.rs b/crates/noirc_evaluator/src/ssa_refactor/ir/types.rs
index 9bb90e0b96b..7e37a72ff83 100644
--- a/crates/noirc_evaluator/src/ssa_refactor/ir/types.rs
+++ b/crates/noirc_evaluator/src/ssa_refactor/ir/types.rs
@@ -10,7 +10,7 @@ use iter_extended::vecmap;
 ///
 /// Fields do not have a notion of ordering, so this distinction
 /// is reasonable.
-#[derive(Copy, Clone, Debug, PartialEq, Eq, Hash)]
+#[derive(Copy, Clone, Debug, PartialEq, Eq, Hash, Ord, PartialOrd)]
 pub(crate) enum NumericType {
     Signed { bit_size: u32 },
     Unsigned { bit_size: u32 },
@@ -18,7 +18,7 @@ pub(crate) enum NumericType {
 }
 
 /// All types representable in the IR.
-#[derive(Clone, Debug, PartialEq, Eq, Hash)]
+#[derive(Clone, Debug, PartialEq, Eq, Hash, Ord, PartialOrd)]
 pub(crate) enum Type {
     /// Represents numeric types in the IR, including field elements
     Numeric(NumericType),
diff --git a/crates/noirc_evaluator/src/ssa_refactor/ir/value.rs b/crates/noirc_evaluator/src/ssa_refactor/ir/value.rs
index fca871ae895..cea526058b4 100644
--- a/crates/noirc_evaluator/src/ssa_refactor/ir/value.rs
+++ b/crates/noirc_evaluator/src/ssa_refactor/ir/value.rs
@@ -1,5 +1,3 @@
-use std::rc::Rc;
-
 use acvm::FieldElement;
 
 use crate::ssa_refactor::ir::basic_block::BasicBlockId;
@@ -8,7 +6,7 @@ use super::{
     function::FunctionId,
     instruction::{InstructionId, Intrinsic},
     map::Id,
-    types::{CompositeType, Type},
+    types::Type,
 };
 
 pub(crate) type ValueId = Id<Value>;
@@ -38,7 +36,7 @@ pub(crate) enum Value {
     NumericConstant { constant: FieldElement, typ: Type },
 
     /// Represents a constant array value
-    Array { array: im::Vector<ValueId>, element_type: Rc<CompositeType> },
+    Array { array: im::Vector<ValueId>, typ: Type },
 
     /// This Value refers to a function in the IR.
     /// Functions always have the type Type::Function.
@@ -64,7 +62,7 @@ impl Value {
             Value::Instruction { typ, .. } => typ.clone(),
             Value::Param { typ, .. } => typ.clone(),
             Value::NumericConstant { typ, .. } => typ.clone(),
-            Value::Array { element_type, array } => Type::Array(element_type.clone(), array.len()),
+            Value::Array { typ, .. } => typ.clone(),
             Value::Function { .. } => Type::Function,
             Value::Intrinsic { .. } => Type::Function,
             Value::ForeignFunction { .. } => Type::Function,
diff --git a/crates/noirc_evaluator/src/ssa_refactor/opt/constant_folding.rs b/crates/noirc_evaluator/src/ssa_refactor/opt/constant_folding.rs
index 3c40e2a15c5..acf048595d7 100644
--- a/crates/noirc_evaluator/src/ssa_refactor/opt/constant_folding.rs
+++ b/crates/noirc_evaluator/src/ssa_refactor/opt/constant_folding.rs
@@ -92,6 +92,8 @@ impl Context {
 
 #[cfg(test)]
 mod test {
+    use std::rc::Rc;
+
     use crate::ssa_refactor::{
         ir::{
             function::RuntimeType,
@@ -176,8 +178,9 @@ mod test {
         let v0 = builder.add_parameter(Type::field());
         let one = builder.field_constant(1u128);
         let v1 = builder.insert_binary(v0, BinaryOp::Add, one);
-        let arr =
-            builder.current_function.dfg.make_array(vec![v1].into(), vec![Type::field()].into());
+
+        let array_type = Type::Array(Rc::new(vec![Type::field()]), 1);
+        let arr = builder.current_function.dfg.make_array(vec![v1].into(), array_type);
         builder.terminate_with_return(vec![arr]);
 
         let ssa = builder.finish().fold_constants();
diff --git a/crates/noirc_evaluator/src/ssa_refactor/opt/defunctionalize.rs b/crates/noirc_evaluator/src/ssa_refactor/opt/defunctionalize.rs
index c31d0c58deb..fc3bc5d9aa6 100644
--- a/crates/noirc_evaluator/src/ssa_refactor/opt/defunctionalize.rs
+++ b/crates/noirc_evaluator/src/ssa_refactor/opt/defunctionalize.rs
@@ -4,7 +4,7 @@
 //! with a non-literal target can be replaced with a call to an apply function.
 //! The apply function is a dispatch function that takes the function id as a parameter
 //! and dispatches to the correct target.
-use std::collections::{HashMap, HashSet};
+use std::collections::{BTreeMap, BTreeSet, HashMap, HashSet};
 
 use acvm::FieldElement;
 use iter_extended::vecmap;
@@ -12,31 +12,15 @@ use iter_extended::vecmap;
 use crate::ssa_refactor::{
     ir::{
         basic_block::BasicBlockId,
-        function::{Function, FunctionId, RuntimeType},
+        function::{Function, FunctionId, RuntimeType, Signature},
         instruction::{BinaryOp, Instruction},
         types::{NumericType, Type},
-        value::Value,
+        value::{Value, ValueId},
     },
     ssa_builder::FunctionBuilder,
     ssa_gen::Ssa,
 };
 
-#[derive(Debug, Clone, PartialEq, Eq, Hash)]
-struct FunctionSignature {
-    parameters: Vec<Type>,
-    returns: Vec<Type>,
-    runtime: RuntimeType,
-}
-
-impl FunctionSignature {
-    fn from(function: &Function) -> Self {
-        let parameters = vecmap(function.parameters(), |param| function.dfg.type_of_value(*param));
-        let returns = vecmap(function.returns(), |ret| function.dfg.type_of_value(*ret));
-        let runtime = function.runtime();
-        Self { parameters, returns, runtime }
-    }
-}
-
 /// Represents an 'apply' function created by this pass to dispatch higher order functions to.
 /// Pseudocode of an `apply` function is given below:
 /// ```text
@@ -63,9 +47,7 @@ struct ApplyFunction {
 /// And creating apply functions that dispatch to the correct target by runtime comparisons with constants
 #[derive(Debug, Clone)]
 struct DefunctionalizationContext {
-    fn_to_runtime: HashMap<FunctionId, RuntimeType>,
-    variants: HashMap<FunctionSignature, Vec<FunctionId>>,
-    apply_functions: HashMap<FunctionSignature, ApplyFunction>,
+    apply_functions: HashMap<Signature, ApplyFunction>,
 }
 
 impl Ssa {
@@ -73,11 +55,9 @@ impl Ssa {
         // Find all functions used as value that share the same signature
         let variants = find_variants(&self);
 
-        let apply_functions = create_apply_functions(&mut self, &variants);
-        let fn_to_runtime =
-            self.functions.iter().map(|(func_id, func)| (*func_id, func.runtime())).collect();
+        let apply_functions = create_apply_functions(&mut self, variants);
 
-        let context = DefunctionalizationContext { fn_to_runtime, variants, apply_functions };
+        let context = DefunctionalizationContext { apply_functions };
 
         context.defunctionalize_all(&mut self);
         self
@@ -94,7 +74,7 @@ impl DefunctionalizationContext {
 
     /// Defunctionalize a single function
     fn defunctionalize(&mut self, func: &mut Function) {
-        let mut target_function_ids = HashSet::new();
+        let mut call_target_values = HashSet::new();
 
         for block_id in func.reachable_blocks() {
             let block = &func.dfg[block_id];
@@ -114,21 +94,14 @@ impl DefunctionalizationContext {
                 match func.dfg[target_func_id] {
                     // If the target is a function used as value
                     Value::Param { .. } | Value::Instruction { .. } => {
-                        // Collect the argument types
-                        let argument_types = vecmap(&arguments, |arg| func.dfg.type_of_value(*arg));
-
-                        // Collect the result types
-                        let result_types =
-                            vecmap(func.dfg.instruction_results(instruction_id), |result| {
-                                func.dfg.type_of_value(*result)
-                            });
+                        let results = func.dfg.instruction_results(instruction_id);
+                        let signature = Signature {
+                            params: vecmap(&arguments, |param| func.dfg.type_of_value(*param)),
+                            returns: vecmap(results, |result| func.dfg.type_of_value(*result)),
+                        };
+
                         // Find the correct apply function
-                        let apply_function = self.get_apply_function(&FunctionSignature {
-                            parameters: argument_types,
-                            returns: result_types,
-                            runtime: func.runtime(),
-                        });
-                        target_function_ids.insert(apply_function.id);
+                        let apply_function = self.get_apply_function(&signature);
 
                         // Replace the instruction with a call to apply
                         let apply_function_value_id = func.dfg.import_function(apply_function.id);
@@ -136,10 +109,12 @@ impl DefunctionalizationContext {
                             arguments.insert(0, target_func_id);
                         }
                         let func = apply_function_value_id;
+                        call_target_values.insert(func);
+
                         replacement_instruction = Some(Instruction::Call { func, arguments });
                     }
-                    Value::Function(id) => {
-                        target_function_ids.insert(id);
+                    Value::Function(..) => {
+                        call_target_values.insert(target_func_id);
                     }
                     _ => {}
                 }
@@ -156,7 +131,7 @@ impl DefunctionalizationContext {
                 match &func.dfg[value_id] {
                     // If the value is a static function, transform it to the function id
                     Value::Function(id) => {
-                        if !target_function_ids.contains(id) {
+                        if !call_target_values.contains(&value_id) {
                             let new_value =
                                 func.dfg.make_constant(function_id_to_field(*id), Type::field());
                             func.dfg.set_value_from_id(value_id, new_value);
@@ -173,72 +148,118 @@ impl DefunctionalizationContext {
     }
 
     /// Returns the apply function for the given signature
-    fn get_apply_function(&self, signature: &FunctionSignature) -> ApplyFunction {
+    fn get_apply_function(&self, signature: &Signature) -> ApplyFunction {
         *self.apply_functions.get(signature).expect("Could not find apply function")
     }
 }
 
-/// Collects all functions used as a value by their signatures
-fn find_variants(ssa: &Ssa) -> HashMap<FunctionSignature, Vec<FunctionId>> {
-    let mut variants: HashMap<FunctionSignature, Vec<FunctionId>> = HashMap::new();
-    let mut functions_used_as_values = HashSet::new();
+/// Collects all functions used as values that can be called by their signatures
+fn find_variants(ssa: &Ssa) -> BTreeMap<Signature, Vec<FunctionId>> {
+    let mut dynamic_dispatches: BTreeSet<Signature> = BTreeSet::new();
+    let mut functions_as_values: BTreeSet<FunctionId> = BTreeSet::new();
 
     for function in ssa.functions.values() {
-        functions_used_as_values.extend(functions_as_values(function));
+        functions_as_values.extend(find_functions_as_values(function));
+        dynamic_dispatches.extend(find_dynamic_dispatches(function));
     }
 
-    for function_id in functions_used_as_values {
-        let function = &ssa.functions[&function_id];
-        let signature = FunctionSignature::from(function);
-        variants.entry(signature).or_default().push(function_id);
+    let mut signature_to_functions_as_value: BTreeMap<Signature, Vec<FunctionId>> = BTreeMap::new();
+
+    for function_id in functions_as_values {
+        let signature = ssa.functions[&function_id].signature();
+        signature_to_functions_as_value.entry(signature).or_default().push(function_id);
+    }
+
+    let mut variants = BTreeMap::new();
+
+    for dispatch_signature in dynamic_dispatches {
+        let mut target_fns = vec![];
+        for (target_signature, functions) in &signature_to_functions_as_value {
+            if &dispatch_signature == target_signature {
+                target_fns.extend(functions);
+            }
+        }
+        variants.insert(dispatch_signature, target_fns);
     }
 
     variants
 }
 
 /// Finds all literal functions used as values in the given function
-fn functions_as_values(func: &Function) -> HashSet<FunctionId> {
-    let mut literal_functions: HashSet<_> = func
-        .dfg
-        .values_iter()
-        .filter_map(|(id, _)| match func.dfg[id] {
-            Value::Function(id) => Some(id),
-            _ => None,
-        })
-        .collect();
+fn find_functions_as_values(func: &Function) -> BTreeSet<FunctionId> {
+    let mut functions_as_values: BTreeSet<FunctionId> = BTreeSet::new();
+
+    let mut process_value = |value_id: ValueId| {
+        if let Value::Function(id) = func.dfg[value_id] {
+            functions_as_values.insert(id);
+        }
+    };
 
     for block_id in func.reachable_blocks() {
         let block = &func.dfg[block_id];
         for instruction_id in block.instructions() {
             let instruction = &func.dfg[*instruction_id];
-            let target_value = match instruction {
-                Instruction::Call { func, .. } => func,
+            match instruction {
+                Instruction::Call { arguments, .. } => {
+                    arguments.iter().for_each(|value_id| process_value(*value_id));
+                }
+                Instruction::Store { value, .. } => {
+                    process_value(*value);
+                }
                 _ => continue,
             };
-            let target_id = match func.dfg[*target_value] {
-                Value::Function(id) => id,
+        }
+
+        block.unwrap_terminator().for_each_value(&mut process_value);
+    }
+
+    functions_as_values
+}
+
+/// Finds all dynamic dispatch signatures in the given function
+fn find_dynamic_dispatches(func: &Function) -> BTreeSet<Signature> {
+    let mut dispatches = BTreeSet::new();
+
+    for block_id in func.reachable_blocks() {
+        let block = &func.dfg[block_id];
+        for instruction_id in block.instructions() {
+            let instruction = &func.dfg[*instruction_id];
+            match instruction {
+                Instruction::Call { func: target, arguments } => {
+                    if let Value::Param { .. } | Value::Instruction { .. } = &func.dfg[*target] {
+                        let results = func.dfg.instruction_results(*instruction_id);
+                        dispatches.insert(Signature {
+                            params: vecmap(arguments, |param| func.dfg.type_of_value(*param)),
+                            returns: vecmap(results, |result| func.dfg.type_of_value(*result)),
+                        });
+                    }
+                }
                 _ => continue,
             };
-            literal_functions.remove(&target_id);
         }
     }
-    literal_functions
+    dispatches
 }
 
 fn create_apply_functions(
     ssa: &mut Ssa,
-    variants_map: &HashMap<FunctionSignature, Vec<FunctionId>>,
-) -> HashMap<FunctionSignature, ApplyFunction> {
+    variants_map: BTreeMap<Signature, Vec<FunctionId>>,
+) -> HashMap<Signature, ApplyFunction> {
     let mut apply_functions = HashMap::new();
-    for (signature, variants) in variants_map.iter() {
+    for (signature, variants) in variants_map.into_iter() {
+        assert!(
+            !variants.is_empty(),
+            "ICE: at least one variant should exist for a dynamic call {:?}",
+            signature
+        );
         let dispatches_to_multiple_functions = variants.len() > 1;
+
         let id = if dispatches_to_multiple_functions {
-            create_apply_function(ssa, signature, variants)
+            create_apply_function(ssa, signature.clone(), variants)
         } else {
             variants[0]
         };
-        apply_functions
-            .insert(signature.clone(), ApplyFunction { id, dispatches_to_multiple_functions });
+        apply_functions.insert(signature, ApplyFunction { id, dispatches_to_multiple_functions });
     }
     apply_functions
 }
@@ -250,15 +271,14 @@ fn function_id_to_field(function_id: FunctionId) -> FieldElement {
 /// Creates an apply function for the given signature and variants
 fn create_apply_function(
     ssa: &mut Ssa,
-    signature: &FunctionSignature,
-    function_ids: &[FunctionId],
+    signature: Signature,
+    function_ids: Vec<FunctionId>,
 ) -> FunctionId {
     assert!(!function_ids.is_empty());
     ssa.add_fn(|id| {
-        let mut function_builder = FunctionBuilder::new("apply".to_string(), id, signature.runtime);
+        let mut function_builder = FunctionBuilder::new("apply".to_string(), id, RuntimeType::Acir);
         let target_id = function_builder.add_parameter(Type::field());
-        let params_ids =
-            vecmap(signature.parameters.clone(), |typ| function_builder.add_parameter(typ));
+        let params_ids = vecmap(signature.params, |typ| function_builder.add_parameter(typ));
 
         let mut previous_target_block = None;
         for (index, function_id) in function_ids.iter().enumerate() {
@@ -293,7 +313,7 @@ fn create_apply_function(
             let target_block = build_return_block(
                 &mut function_builder,
                 current_block,
-                signature.returns.clone(),
+                &signature.returns,
                 previous_target_block,
             );
             previous_target_block = Some(target_block);
@@ -321,13 +341,13 @@ fn create_apply_function(
 fn build_return_block(
     builder: &mut FunctionBuilder,
     previous_block: BasicBlockId,
-    passed_types: Vec<Type>,
+    passed_types: &[Type],
     target: Option<BasicBlockId>,
 ) -> BasicBlockId {
     let return_block = builder.insert_block();
     builder.switch_to_block(return_block);
 
-    let params = vecmap(passed_types, |typ| builder.add_block_parameter(return_block, typ));
+    let params = vecmap(passed_types, |typ| builder.add_block_parameter(return_block, typ.clone()));
     match target {
         None => builder.terminate_with_return(params),
         Some(target) => builder.terminate_with_jmp(target, params),
diff --git a/crates/noirc_evaluator/src/ssa_refactor/opt/flatten_cfg.rs b/crates/noirc_evaluator/src/ssa_refactor/opt/flatten_cfg.rs
index 3b6512a3c45..4ff857f942f 100644
--- a/crates/noirc_evaluator/src/ssa_refactor/opt/flatten_cfg.rs
+++ b/crates/noirc_evaluator/src/ssa_refactor/opt/flatten_cfg.rs
@@ -131,10 +131,7 @@
 //!   v11 = mul v4, Field 12
 //!   v12 = add v10, v11
 //!   store v12 at v5         (new store)
-use std::{
-    collections::{HashMap, HashSet},
-    rc::Rc,
-};
+use std::collections::{BTreeMap, HashMap, HashSet};
 
 use acvm::FieldElement;
 use iter_extended::vecmap;
@@ -148,7 +145,7 @@ use crate::ssa_refactor::{
         function::Function,
         function_inserter::FunctionInserter,
         instruction::{BinaryOp, Instruction, InstructionId, TerminatorInstruction},
-        types::{CompositeType, Type},
+        types::Type,
         value::ValueId,
     },
     ssa_gen::Ssa,
@@ -157,16 +154,14 @@ use crate::ssa_refactor::{
 mod branch_analysis;
 
 impl Ssa {
-    /// Flattens the control flow graph of each function such that the function is left with a
+    /// Flattens the control flow graph of main such that the function is left with a
     /// single block containing all instructions and no more control-flow.
     ///
     /// This pass will modify any instructions with side effects in particular, often multiplying
     /// them by jump conditions to maintain correctness even when all branches of a jmpif are inlined.
     /// For more information, see the module-level comment at the top of this file.
     pub(crate) fn flatten_cfg(mut self) -> Ssa {
-        for function in self.functions.values_mut() {
-            flatten_function_cfg(function);
-        }
+        flatten_function_cfg(self.main_mut());
         self
     }
 }
@@ -395,14 +390,9 @@ impl<'f> Context<'f> {
             Type::Numeric(_) => {
                 self.merge_numeric_values(then_condition, else_condition, then_value, else_value)
             }
-            Type::Array(element_types, len) => self.merge_array_values(
-                element_types,
-                len,
-                then_condition,
-                else_condition,
-                then_value,
-                else_value,
-            ),
+            typ @ Type::Array(_, _) => {
+                self.merge_array_values(typ, then_condition, else_condition, then_value, else_value)
+            }
             // TODO(#1889)
             Type::Slice(_) => panic!("Cannot return slices from an if expression"),
             Type::Reference => panic!("Cannot return references from an if expression"),
@@ -415,8 +405,7 @@ impl<'f> Context<'f> {
     /// by creating a new array containing the result of self.merge_values for each element.
     fn merge_array_values(
         &mut self,
-        element_types: Rc<CompositeType>,
-        len: usize,
+        typ: Type,
         then_condition: ValueId,
         else_condition: ValueId,
         then_value: ValueId,
@@ -424,6 +413,11 @@ impl<'f> Context<'f> {
     ) -> ValueId {
         let mut merged = im::Vector::new();
 
+        let (element_types, len) = match &typ {
+            Type::Array(elements, len) => (elements, *len),
+            _ => panic!("Expected array type"),
+        };
+
         for i in 0..len {
             for (element_index, element_type) in element_types.iter().enumerate() {
                 let index = ((i * element_types.len() + element_index) as u128).into();
@@ -448,7 +442,7 @@ impl<'f> Context<'f> {
             }
         }
 
-        self.inserter.function.dfg.make_array(merged, element_types)
+        self.inserter.function.dfg.make_array(merged, typ)
     }
 
     /// Merge two numeric values a and b from separate basic blocks to a single value. This
@@ -612,7 +606,7 @@ impl<'f> Context<'f> {
     /// this function also needs to be changed to reflect that.
     fn merge_stores(&mut self, then_branch: Branch, else_branch: Branch) {
         // Address -> (then_value, else_value, value_before_the_if)
-        let mut new_map = HashMap::with_capacity(then_branch.store_values.len());
+        let mut new_map = BTreeMap::new();
 
         for (address, store) in then_branch.store_values {
             new_map.insert(address, (store.new_value, store.old_value, store.old_value));
@@ -1335,8 +1329,10 @@ mod test {
         let b3 = builder.insert_block();
 
         let element_type = Rc::new(vec![Type::field()]);
+        let array_type = Type::Array(element_type.clone(), 1);
+
         let zero = builder.field_constant(0_u128);
-        let zero_array = builder.array_constant(im::Vector::unit(zero), element_type.clone());
+        let zero_array = builder.array_constant(im::Vector::unit(zero), array_type);
         let i_zero = builder.numeric_constant(0_u128, Type::unsigned(32));
         let pedersen =
             builder.import_intrinsic_id(Intrinsic::BlackBox(acvm::acir::BlackBoxFunc::Pedersen));
diff --git a/crates/noirc_evaluator/src/ssa_refactor/opt/inlining.rs b/crates/noirc_evaluator/src/ssa_refactor/opt/inlining.rs
index 430b52ce9f6..7aa2f9d176a 100644
--- a/crates/noirc_evaluator/src/ssa_refactor/opt/inlining.rs
+++ b/crates/noirc_evaluator/src/ssa_refactor/opt/inlining.rs
@@ -217,9 +217,9 @@ impl<'function> PerFunctionContext<'function> {
             Value::ForeignFunction(function) => {
                 self.context.builder.import_foreign_function(function)
             }
-            Value::Array { array, element_type } => {
+            Value::Array { array, typ } => {
                 let elements = array.iter().map(|value| self.translate_value(*value)).collect();
-                self.context.builder.array_constant(elements, element_type.clone())
+                self.context.builder.array_constant(elements, typ.clone())
             }
         };
 
diff --git a/crates/noirc_evaluator/src/ssa_refactor/opt/mem2reg.rs b/crates/noirc_evaluator/src/ssa_refactor/opt/mem2reg.rs
index 145ba25f5a5..15108abc490 100644
--- a/crates/noirc_evaluator/src/ssa_refactor/opt/mem2reg.rs
+++ b/crates/noirc_evaluator/src/ssa_refactor/opt/mem2reg.rs
@@ -212,10 +212,11 @@ mod tests {
         let two = builder.field_constant(FieldElement::one());
 
         let element_type = Rc::new(vec![Type::field()]);
-        let array = builder.array_constant(vector![one, two], element_type.clone());
+        let array_type = Type::Array(element_type, 2);
+        let array = builder.array_constant(vector![one, two], array_type.clone());
 
         builder.insert_store(v0, array);
-        let v1 = builder.insert_load(v0, Type::Array(element_type, 2));
+        let v1 = builder.insert_load(v0, array_type);
         let v2 = builder.insert_array_get(v1, one, Type::field());
         builder.terminate_with_return(vec![v2]);
 
diff --git a/crates/noirc_evaluator/src/ssa_refactor/ssa_builder/mod.rs b/crates/noirc_evaluator/src/ssa_refactor/ssa_builder/mod.rs
index d3d9e56b3af..02350d9ed17 100644
--- a/crates/noirc_evaluator/src/ssa_refactor/ssa_builder/mod.rs
+++ b/crates/noirc_evaluator/src/ssa_refactor/ssa_builder/mod.rs
@@ -1,4 +1,4 @@
-use std::{borrow::Cow, rc::Rc};
+use std::borrow::Cow;
 
 use acvm::FieldElement;
 use noirc_errors::Location;
@@ -17,7 +17,6 @@ use super::{
         dfg::InsertInstructionResult,
         function::RuntimeType,
         instruction::{InstructionId, Intrinsic},
-        types::CompositeType,
     },
     ssa_gen::Ssa,
 };
@@ -115,12 +114,8 @@ impl FunctionBuilder {
     }
 
     /// Insert an array constant into the current function with the given element values.
-    pub(crate) fn array_constant(
-        &mut self,
-        elements: im::Vector<ValueId>,
-        element_types: Rc<CompositeType>,
-    ) -> ValueId {
-        self.current_function.dfg.make_array(elements, element_types)
+    pub(crate) fn array_constant(&mut self, elements: im::Vector<ValueId>, typ: Type) -> ValueId {
+        self.current_function.dfg.make_array(elements, typ)
     }
 
     /// Returns the type of the given value.
diff --git a/crates/noirc_evaluator/src/ssa_refactor/ssa_gen/context.rs b/crates/noirc_evaluator/src/ssa_refactor/ssa_gen/context.rs
index 07ee32998d2..769ee6aa09f 100644
--- a/crates/noirc_evaluator/src/ssa_refactor/ssa_gen/context.rs
+++ b/crates/noirc_evaluator/src/ssa_refactor/ssa_gen/context.rs
@@ -558,10 +558,20 @@ impl<'a> FunctionContext<'a> {
     pub(super) fn assign_new_value(&mut self, lvalue: LValue, new_value: Values) {
         match lvalue {
             LValue::Ident(references) => self.assign(references, new_value),
-            LValue::Index { old_array, index, array_lvalue } => {
-                let rvalue = new_value.into_leaf().eval(self); // TODO
-                let new_array = self.builder.insert_array_set(old_array, index, rvalue);
-                self.assign_new_value(*array_lvalue, new_array.into());
+            LValue::Index { old_array: mut array, index, array_lvalue } => {
+                let element_size = self.builder.field_constant(self.element_size(array));
+
+                // The actual base index is the user's index * the array element type's size
+                let mut index = self.builder.insert_binary(index, BinaryOp::Mul, element_size);
+                let one = self.builder.field_constant(FieldElement::one());
+
+                new_value.for_each(|value| {
+                    let value = value.eval(self);
+                    array = self.builder.insert_array_set(array, index, value);
+                    index = self.builder.insert_binary(index, BinaryOp::Add, one);
+                });
+
+                self.assign_new_value(*array_lvalue, array.into());
             }
             LValue::MemberAccess { old_object, index, object_lvalue } => {
                 let new_object = Self::replace_field(old_object, index, new_value);
@@ -573,6 +583,13 @@ impl<'a> FunctionContext<'a> {
         }
     }
 
+    fn element_size(&self, array: ValueId) -> FieldElement {
+        match self.builder.type_of_value(array) {
+            Type::Array(elements, _) | Type::Slice(elements) => (elements.len() as u128).into(),
+            t => panic!("Uncaught type error: tried to take element size of non-array type {t}"),
+        }
+    }
+
     /// Given an lhs containing only references, create a store instruction to store each value of
     /// rhs into its corresponding value in lhs.
     fn assign(&mut self, lhs: Values, rhs: Values) {
diff --git a/crates/noirc_evaluator/src/ssa_refactor/ssa_gen/mod.rs b/crates/noirc_evaluator/src/ssa_refactor/ssa_gen/mod.rs
index 13e67f26cc5..d6169dfd218 100644
--- a/crates/noirc_evaluator/src/ssa_refactor/ssa_gen/mod.rs
+++ b/crates/noirc_evaluator/src/ssa_refactor/ssa_gen/mod.rs
@@ -2,8 +2,6 @@ mod context;
 mod program;
 mod value;
 
-use std::rc::Rc;
-
 pub(crate) use program::Ssa;
 
 use context::SharedContext;
@@ -16,12 +14,7 @@ use self::{
     value::{Tree, Values},
 };
 
-use super::ir::{
-    function::RuntimeType,
-    instruction::BinaryOp,
-    types::{CompositeType, Type},
-    value::ValueId,
-};
+use super::ir::{function::RuntimeType, instruction::BinaryOp, types::Type, value::ValueId};
 
 /// Generates SSA for the given monomorphized program.
 ///
@@ -96,8 +89,13 @@ impl<'a> FunctionContext<'a> {
         self.codegen_expression(expr).into_leaf().eval(self)
     }
 
-    /// Codegen for identifiers
-    fn codegen_ident(&mut self, ident: &ast::Ident) -> Values {
+    /// Codegen a reference to an ident.
+    /// The only difference between this and codegen_ident is that if the variable is mutable
+    /// as in `let mut var = ...;` the `Value::Mutable` will be returned directly instead of
+    /// being automatically loaded from. This is needed when taking the reference of a variable
+    /// to reassign to it. Note that mutable references `let x = &mut ...;` do not require this
+    /// since they are not automatically loaded from and must be explicitly dereferenced.
+    fn codegen_ident_reference(&mut self, ident: &ast::Ident) -> Values {
         match &ident.definition {
             ast::Definition::Local(id) => self.lookup(*id),
             ast::Definition::Function(id) => self.get_or_queue_function(*id),
@@ -111,12 +109,17 @@ impl<'a> FunctionContext<'a> {
         }
     }
 
+    /// Codegen an identifier, automatically loading its value if it is mutable.
+    fn codegen_ident(&mut self, ident: &ast::Ident) -> Values {
+        self.codegen_ident_reference(ident).map(|value| value.eval(self).into())
+    }
+
     fn codegen_literal(&mut self, literal: &ast::Literal) -> Values {
         match literal {
             ast::Literal::Array(array) => {
                 let elements = vecmap(&array.contents, |element| self.codegen_expression(element));
-                let element_types = Self::convert_type(&array.element_type).flatten();
-                self.codegen_array(elements, element_types)
+                let typ = Self::convert_non_tuple_type(&array.typ);
+                self.codegen_array(elements, typ)
             }
             ast::Literal::Integer(value, typ) => {
                 let typ = Self::convert_non_tuple_type(typ);
@@ -129,7 +132,8 @@ impl<'a> FunctionContext<'a> {
                 let elements = vecmap(string.as_bytes(), |byte| {
                     self.builder.numeric_constant(*byte as u128, Type::field()).into()
                 });
-                self.codegen_array(elements, vec![Type::char()])
+                let typ = Self::convert_non_tuple_type(&ast::Type::String(elements.len() as u64));
+                self.codegen_array(elements, typ)
             }
         }
     }
@@ -143,7 +147,7 @@ impl<'a> FunctionContext<'a> {
     /// stored the same as the array [1, 2, 3, 4].
     ///
     /// The value returned from this function is always that of the allocate instruction.
-    fn codegen_array(&mut self, elements: Vec<Values>, element_types: CompositeType) -> Values {
+    fn codegen_array(&mut self, elements: Vec<Values>, typ: Type) -> Values {
         let mut array = im::Vector::new();
 
         for element in elements {
@@ -153,7 +157,7 @@ impl<'a> FunctionContext<'a> {
             });
         }
 
-        self.builder.array_constant(array, Rc::new(element_types)).into()
+        self.builder.array_constant(array, typ).into()
     }
 
     fn codegen_block(&mut self, block: &[Expression]) -> Values {
@@ -165,20 +169,21 @@ impl<'a> FunctionContext<'a> {
     }
 
     fn codegen_unary(&mut self, unary: &ast::Unary) -> Values {
-        let rhs = self.codegen_expression(&unary.rhs);
         match unary.operator {
             noirc_frontend::UnaryOp::Not => {
+                let rhs = self.codegen_expression(&unary.rhs);
                 let rhs = rhs.into_leaf().eval(self);
                 self.builder.insert_not(rhs).into()
             }
             noirc_frontend::UnaryOp::Minus => {
+                let rhs = self.codegen_expression(&unary.rhs);
                 let rhs = rhs.into_leaf().eval(self);
                 let typ = self.builder.type_of_value(rhs);
                 let zero = self.builder.numeric_constant(0u128, typ);
                 self.builder.insert_binary(zero, BinaryOp::Sub, rhs).into()
             }
             noirc_frontend::UnaryOp::MutableReference => {
-                rhs.map(|rhs| {
+                self.codegen_reference(&unary.rhs).map(|rhs| {
                     match rhs {
                         value::Value::Normal(value) => {
                             let alloc = self.builder.insert_allocate();
@@ -191,7 +196,21 @@ impl<'a> FunctionContext<'a> {
                     }
                 })
             }
-            noirc_frontend::UnaryOp::Dereference => self.dereference(&rhs, &unary.result_type),
+            noirc_frontend::UnaryOp::Dereference { .. } => {
+                let rhs = self.codegen_expression(&unary.rhs);
+                self.dereference(&rhs, &unary.result_type)
+            }
+        }
+    }
+
+    fn codegen_reference(&mut self, expr: &Expression) -> Values {
+        match expr {
+            Expression::Ident(ident) => self.codegen_ident_reference(ident),
+            Expression::ExtractTupleField(tuple, index) => {
+                let tuple = self.codegen_reference(tuple);
+                Self::get_field(tuple, *index)
+            }
+            other => self.codegen_expression(other),
         }
     }
 
diff --git a/crates/noirc_frontend/Cargo.toml b/crates/noirc_frontend/Cargo.toml
index f3fc1c83758..a9a62673af6 100644
--- a/crates/noirc_frontend/Cargo.toml
+++ b/crates/noirc_frontend/Cargo.toml
@@ -17,6 +17,7 @@ chumsky.workspace = true
 thiserror.workspace = true
 smol_str.workspace = true
 serde.workspace = true
+serde_json.workspace = true
 rustc-hash = "1.1.0"
 small-ord-set = "0.1.3"
 
diff --git a/crates/noirc_frontend/src/ast/expression.rs b/crates/noirc_frontend/src/ast/expression.rs
index b1cd30a6777..1f1d226310f 100644
--- a/crates/noirc_frontend/src/ast/expression.rs
+++ b/crates/noirc_frontend/src/ast/expression.rs
@@ -271,7 +271,14 @@ pub enum UnaryOp {
     Minus,
     Not,
     MutableReference,
-    Dereference,
+
+    /// If implicitly_added is true, this operation was implicitly added by the compiler for a
+    /// field dereference. The compiler may undo some of these implicitly added dereferences if
+    /// the reference later turns out to be needed (e.g. passing a field by reference to a function
+    /// requiring an &mut parameter).
+    Dereference {
+        implicitly_added: bool,
+    },
 }
 
 impl UnaryOp {
@@ -291,6 +298,7 @@ pub enum Literal {
     Bool(bool),
     Integer(FieldElement),
     Str(String),
+    Unit,
 }
 
 #[derive(Debug, PartialEq, Eq, Clone)]
@@ -465,6 +473,7 @@ impl Display for Literal {
             Literal::Bool(boolean) => write!(f, "{}", if *boolean { "true" } else { "false" }),
             Literal::Integer(integer) => write!(f, "{}", integer.to_u128()),
             Literal::Str(string) => write!(f, "\"{string}\""),
+            Literal::Unit => write!(f, "()"),
         }
     }
 }
@@ -494,7 +503,7 @@ impl Display for UnaryOp {
             UnaryOp::Minus => write!(f, "-"),
             UnaryOp::Not => write!(f, "!"),
             UnaryOp::MutableReference => write!(f, "&mut"),
-            UnaryOp::Dereference => write!(f, "*"),
+            UnaryOp::Dereference { .. } => write!(f, "*"),
         }
     }
 }
diff --git a/crates/noirc_frontend/src/ast/function.rs b/crates/noirc_frontend/src/ast/function.rs
index de4e4f6f4d2..02af960f7a8 100644
--- a/crates/noirc_frontend/src/ast/function.rs
+++ b/crates/noirc_frontend/src/ast/function.rs
@@ -82,7 +82,7 @@ impl From<FunctionDefinition> for NoirFunction {
             Some(Attribute::Foreign(_)) => FunctionKind::LowLevel,
             Some(Attribute::Test) => FunctionKind::Normal,
             Some(Attribute::Oracle(_)) => FunctionKind::Oracle,
-            None => FunctionKind::Normal,
+            Some(Attribute::Deprecated(_)) | None => FunctionKind::Normal,
         };
 
         NoirFunction { def: fd, kind }
diff --git a/crates/noirc_frontend/src/ast/statement.rs b/crates/noirc_frontend/src/ast/statement.rs
index 7292d227c3e..e35394e0729 100644
--- a/crates/noirc_frontend/src/ast/statement.rs
+++ b/crates/noirc_frontend/src/ast/statement.rs
@@ -456,7 +456,7 @@ impl LValue {
             })),
             LValue::Dereference(lvalue) => {
                 ExpressionKind::Prefix(Box::new(crate::PrefixExpression {
-                    operator: crate::UnaryOp::Dereference,
+                    operator: crate::UnaryOp::Dereference { implicitly_added: false },
                     rhs: lvalue.as_expression(span),
                 }))
             }
diff --git a/crates/noirc_frontend/src/graph/mod.rs b/crates/noirc_frontend/src/graph/mod.rs
index 271bcc19e67..7ebfbae4817 100644
--- a/crates/noirc_frontend/src/graph/mod.rs
+++ b/crates/noirc_frontend/src/graph/mod.rs
@@ -4,43 +4,52 @@
 // This version is also simpler due to not having macro_defs or proc_macros
 // XXX: Edition may be reintroduced or some sort of versioning
 
+use std::str::FromStr;
+
 use fm::FileId;
 use rustc_hash::{FxHashMap, FxHashSet};
 use smol_str::SmolStr;
 
-/// The local crate is the crate being compiled.
-/// The caller should ensure that this crate has a CrateId(0).
-pub const LOCAL_CRATE: CrateId = CrateId(0);
-
 #[derive(Debug, Clone, Copy, PartialEq, Eq, Hash)]
-pub struct CrateId(usize);
+pub enum CrateId {
+    Crate(usize),
+    Stdlib(usize),
+}
 
 impl CrateId {
     pub fn dummy_id() -> CrateId {
-        CrateId(std::usize::MAX)
+        CrateId::Crate(std::usize::MAX)
+    }
+
+    pub fn is_stdlib(&self) -> bool {
+        matches!(self, CrateId::Stdlib(_))
     }
 }
 
-#[derive(Debug, Clone, PartialEq, Eq)]
+#[derive(Debug, Clone, PartialEq, Eq, Hash)]
 pub struct CrateName(SmolStr);
 
-impl CrateName {
-    /// Creates a new CrateName rejecting any crate name that
-    /// has a character on the blacklist.
-    /// The difference between RA and this implementation is that
-    /// characters on the blacklist are never allowed; there is no normalization.
-    pub fn new(name: &str) -> Result<CrateName, &str> {
+impl From<CrateName> for String {
+    fn from(crate_name: CrateName) -> Self {
+        crate_name.0.into()
+    }
+}
+
+/// Creates a new CrateName rejecting any crate name that
+/// has a character on the blacklist.
+/// The difference between RA and this implementation is that
+/// characters on the blacklist are never allowed; there is no normalization.
+impl FromStr for CrateName {
+    type Err = String;
+
+    fn from_str(name: &str) -> Result<Self, Self::Err> {
         let is_invalid = name.chars().any(|n| CHARACTER_BLACK_LIST.contains(&n));
         if is_invalid {
-            Err(name)
+            Err(name.into())
         } else {
             Ok(Self(SmolStr::new(name)))
         }
     }
-
-    pub fn as_string(&self) -> String {
-        self.0.clone().into()
-    }
 }
 
 #[derive(Debug, Clone, Default, PartialEq, Eq)]
@@ -48,12 +57,6 @@ pub struct CrateGraph {
     arena: FxHashMap<CrateId, CrateData>,
 }
 
-impl CrateGraph {
-    pub fn is_last_crate(&self, crate_id: CrateId) -> bool {
-        (self.arena.len() - 1) == crate_id.0
-    }
-}
-
 /// List of characters that are not allowed in a crate name
 /// For example, Hyphen(-) is disallowed as it is similar to underscore(_)
 /// and we do not want names that differ by a hyphen
@@ -83,7 +86,7 @@ pub struct Dependency {
 
 impl Dependency {
     pub fn as_name(&self) -> String {
-        self.name.as_string()
+        self.name.clone().into()
     }
 }
 
@@ -98,7 +101,23 @@ impl CrateGraph {
         }
 
         let data = CrateData { root_file_id: file_id, crate_type, dependencies: Vec::new() };
-        let crate_id = CrateId(self.arena.len());
+        let crate_id = CrateId::Crate(self.arena.len());
+        let prev = self.arena.insert(crate_id, data);
+        assert!(prev.is_none());
+        crate_id
+    }
+
+    pub fn add_stdlib(&mut self, crate_type: CrateType, file_id: FileId) -> CrateId {
+        let mut roots_with_file_id =
+            self.arena.iter().filter(|(_, crate_data)| crate_data.root_file_id == file_id);
+
+        let next_file_id = roots_with_file_id.next();
+        if let Some(file_id) = next_file_id {
+            return *file_id.0;
+        }
+
+        let data = CrateData { root_file_id: file_id, crate_type, dependencies: Vec::new() };
+        let crate_id = CrateId::Stdlib(self.arena.len());
         let prev = self.arena.insert(crate_id, data);
         assert!(prev.is_none());
         crate_id
@@ -199,7 +218,7 @@ pub struct CyclicDependenciesError {
 mod tests {
     use std::path::PathBuf;
 
-    use super::{CrateGraph, CrateName, CrateType, FileId};
+    use super::{CrateGraph, CrateType, FileId};
 
     fn dummy_file_ids(n: usize) -> Vec<FileId> {
         use fm::{FileMap, FILE_EXTENSION};
@@ -225,9 +244,9 @@ mod tests {
         let crate2 = graph.add_crate_root(CrateType::Library, file_ids[1]);
         let crate3 = graph.add_crate_root(CrateType::Library, file_ids[2]);
 
-        assert!(graph.add_dep(crate1, CrateName::new("crate2").unwrap(), crate2).is_ok());
-        assert!(graph.add_dep(crate2, CrateName::new("crate3").unwrap(), crate3).is_ok());
-        assert!(graph.add_dep(crate3, CrateName::new("crate1").unwrap(), crate1).is_err());
+        assert!(graph.add_dep(crate1, "crate2".parse().unwrap(), crate2).is_ok());
+        assert!(graph.add_dep(crate2, "crate3".parse().unwrap(), crate3).is_ok());
+        assert!(graph.add_dep(crate3, "crate1".parse().unwrap(), crate1).is_err());
     }
 
     #[test]
@@ -240,8 +259,8 @@ mod tests {
         let crate1 = graph.add_crate_root(CrateType::Library, file_id_0);
         let crate2 = graph.add_crate_root(CrateType::Library, file_id_1);
         let crate3 = graph.add_crate_root(CrateType::Library, file_id_2);
-        assert!(graph.add_dep(crate1, CrateName::new("crate2").unwrap(), crate2).is_ok());
-        assert!(graph.add_dep(crate2, CrateName::new("crate3").unwrap(), crate3).is_ok());
+        assert!(graph.add_dep(crate1, "crate2".parse().unwrap(), crate2).is_ok());
+        assert!(graph.add_dep(crate2, "crate3".parse().unwrap(), crate3).is_ok());
     }
     #[test]
     fn it_works2() {
diff --git a/crates/noirc_frontend/src/hir/def_collector/dc_crate.rs b/crates/noirc_frontend/src/hir/def_collector/dc_crate.rs
index b0022e26924..3f30a4990e4 100644
--- a/crates/noirc_frontend/src/hir/def_collector/dc_crate.rs
+++ b/crates/noirc_frontend/src/hir/def_collector/dc_crate.rs
@@ -1,6 +1,6 @@
 use super::dc_mod::collect_defs;
 use super::errors::DefCollectorErrorKind;
-use crate::graph::{CrateId, LOCAL_CRATE};
+use crate::graph::CrateId;
 use crate::hir::def_map::{CrateDefMap, LocalModuleId, ModuleId};
 use crate::hir::resolution::errors::ResolverError;
 use crate::hir::resolution::resolver::Resolver;
@@ -237,10 +237,8 @@ fn collect_impls(
                         errors.push(err.into_file_diagnostic(unresolved.file_id));
                     }
                 }
-            // Prohibit defining impls for primitive types if we're in the local crate.
-            // We should really prevent it for all crates that aren't the noir stdlib but
-            // there is no way of checking if the current crate is the stdlib currently.
-            } else if typ != Type::Error && crate_id == LOCAL_CRATE {
+            // Prohibit defining impls for primitive types if we're not in the stdlib
+            } else if typ != Type::Error && !crate_id.is_stdlib() {
                 let span = *span;
                 let error = DefCollectorErrorKind::NonStructTypeInImpl { span };
                 errors.push(error.into_file_diagnostic(unresolved.file_id));
@@ -452,6 +450,7 @@ fn resolve_function_set(
     let file_id = unresolved_functions.file_id;
 
     vecmap(unresolved_functions.functions, |(mod_id, func_id, func)| {
+        let module_id = ModuleId { krate: crate_id, local_id: mod_id };
         let path_resolver =
             StandardPathResolver::new(ModuleId { local_id: mod_id, krate: crate_id });
 
@@ -462,7 +461,7 @@ fn resolve_function_set(
         resolver.set_generics(impl_generics.clone());
         resolver.set_self_type(self_type.clone());
 
-        let (hir_func, func_meta, errs) = resolver.resolve_function(func, func_id);
+        let (hir_func, func_meta, errs) = resolver.resolve_function(func, func_id, module_id);
         interner.push_fn_meta(func_meta, func_id);
         interner.update_fn(func_id, hir_func);
         extend_errors(errors, file_id, errs);
diff --git a/crates/noirc_frontend/src/hir/def_map/mod.rs b/crates/noirc_frontend/src/hir/def_map/mod.rs
index 3997903a43e..b32f332bd25 100644
--- a/crates/noirc_frontend/src/hir/def_map/mod.rs
+++ b/crates/noirc_frontend/src/hir/def_map/mod.rs
@@ -39,6 +39,12 @@ pub struct ModuleId {
     pub local_id: LocalModuleId,
 }
 
+impl ModuleId {
+    pub fn dummy_id() -> ModuleId {
+        ModuleId { krate: CrateId::dummy_id(), local_id: LocalModuleId::dummy_id() }
+    }
+}
+
 impl ModuleId {
     pub fn module(self, def_maps: &HashMap<CrateId, CrateDefMap>) -> &ModuleData {
         &def_maps[&self.krate].modules()[self.local_id.0]
@@ -77,25 +83,7 @@ impl CrateDefMap {
 
         // First parse the root file.
         let root_file_id = context.crate_graph[crate_id].root_file_id;
-        let mut ast = parse_file(&mut context.file_manager, root_file_id, errors);
-
-        // TODO(#1850): This check should be removed once we fully move over to the new SSA pass
-        // Compiling with the old SSA pass will lead to duplicate method definitions between
-        // the `slice` and `array` modules of the stdlib.
-        //
-        // The last crate represents the stdlib crate.
-        // After resolving the manifest of the local crate the stdlib is added to the manifest and propagated to all crates
-        // thus being the last crate.
-        if !context.def_interner.enable_slices && context.crate_graph.is_last_crate(crate_id) {
-            let path_as_str = context
-                .file_manager
-                .path(root_file_id)
-                .to_str()
-                .expect("expected std path to be convertible to str");
-            assert_eq!(path_as_str, "std/lib");
-            ast.module_decls
-                .retain(|ident| ident.0.contents != "slice" && ident.0.contents != "collections");
-        }
+        let ast = parse_file(&mut context.file_manager, root_file_id, errors);
 
         // Allocate a default Module for the root, giving it a ModuleId
         let mut modules: Arena<ModuleData> = Arena::default();
@@ -175,7 +163,16 @@ impl CrateDefMap {
 
     /// Find a child module's name by inspecting its parent.
     /// Currently required as modules do not store their own names.
-    fn get_module_path(&self, child_id: Index, parent: Option<LocalModuleId>) -> String {
+    pub fn get_module_path(&self, child_id: Index, parent: Option<LocalModuleId>) -> String {
+        self.get_module_path_with_separator(child_id, parent, ".")
+    }
+
+    pub fn get_module_path_with_separator(
+        &self,
+        child_id: Index,
+        parent: Option<LocalModuleId>,
+        separator: &str,
+    ) -> String {
         if let Some(id) = parent {
             let parent = &self.modules[id.0];
             let name = parent
@@ -185,11 +182,11 @@ impl CrateDefMap {
                 .map(|(name, _)| &name.0.contents)
                 .expect("Child module was not a child of the given parent module");
 
-            let parent_name = self.get_module_path(id.0, parent.parent);
+            let parent_name = self.get_module_path_with_separator(id.0, parent.parent, separator);
             if parent_name.is_empty() {
                 name.to_string()
             } else {
-                format!("{parent_name}.{name}")
+                format!("{parent_name}{separator}{name}")
             }
         } else {
             String::new()
diff --git a/crates/noirc_frontend/src/hir/mod.rs b/crates/noirc_frontend/src/hir/mod.rs
index cd188f46392..5937f57a8c7 100644
--- a/crates/noirc_frontend/src/hir/mod.rs
+++ b/crates/noirc_frontend/src/hir/mod.rs
@@ -14,12 +14,10 @@ use std::collections::HashMap;
 /// Helper object which groups together several useful context objects used
 /// during name resolution. Once name resolution is finished, only the
 /// def_interner is required for type inference and monomorphization.
-#[derive(Default)]
 pub struct Context {
     pub def_interner: NodeInterner,
     pub crate_graph: CrateGraph,
     pub(crate) def_maps: HashMap<CrateId, CrateDefMap>,
-    // TODO(#1599): Remove default impl and move creation/control of the FileManager into places that construct Context
     pub file_manager: FileManager,
 
     /// Maps a given (contract) module id to the next available storage slot
@@ -89,16 +87,35 @@ impl Context {
         &self,
         crate_id: &CrateId,
         pattern: &str,
-    ) -> Vec<FuncId> {
+    ) -> Vec<(String, FuncId)> {
         let interner = &self.def_interner;
-        self.def_map(crate_id)
-            .expect("The local crate should be analyzed already")
+        let def_map = self.def_map(crate_id).expect("The local crate should be analyzed already");
+
+        def_map
             .get_all_test_functions(interner)
-            .filter_map(|id| interner.function_name(&id).contains(pattern).then_some(id))
+            .filter_map(|id| {
+                let name = interner.function_name(&id);
+
+                let meta = interner.function_meta(&id);
+                let module = self.module(meta.module_id);
+
+                let parent = def_map.get_module_path_with_separator(
+                    meta.module_id.local_id.0,
+                    module.parent,
+                    "::",
+                );
+                let path =
+                    if parent.is_empty() { name.into() } else { format!("{parent}::{name}") };
+
+                path.contains(pattern).then_some((path, id))
+            })
             .collect()
     }
 
-    pub fn get_all_test_functions_in_workspace_matching(&self, pattern: &str) -> Vec<FuncId> {
+    pub fn get_all_test_functions_in_workspace_matching(
+        &self,
+        pattern: &str,
+    ) -> Vec<(String, FuncId)> {
         let mut tests = Vec::new();
 
         for crate_id in self.crate_graph.iter_keys() {
diff --git a/crates/noirc_frontend/src/hir/resolution/errors.rs b/crates/noirc_frontend/src/hir/resolution/errors.rs
index 296be28b5a6..82688928575 100644
--- a/crates/noirc_frontend/src/hir/resolution/errors.rs
+++ b/crates/noirc_frontend/src/hir/resolution/errors.rs
@@ -6,6 +6,14 @@ use crate::{parser::ParserError, Ident, Type};
 
 use super::import::PathResolutionError;
 
+#[derive(Error, Debug, Clone, PartialEq, Eq)]
+pub enum PubPosition {
+    #[error("parameter")]
+    Parameter,
+    #[error("return type")]
+    ReturnType,
+}
+
 #[derive(Error, Debug, Clone, PartialEq, Eq)]
 pub enum ResolverError {
     #[error("Duplicate definition")]
@@ -29,7 +37,7 @@ pub enum ResolverError {
     #[error("Unneeded 'mut', pattern is already marked as mutable")]
     UnnecessaryMut { first_mut: Span, second_mut: Span },
     #[error("Unneeded 'pub', function is not the main method")]
-    UnnecessaryPub { ident: Ident },
+    UnnecessaryPub { ident: Ident, position: PubPosition },
     #[error("Required 'pub', main function must return public value")]
     NecessaryPub { ident: Ident },
     #[error("'distinct' keyword can only be used with main method")]
@@ -160,12 +168,12 @@ impl From<ResolverError> for Diagnostic {
                 );
                 error
             }
-            ResolverError::UnnecessaryPub { ident } => {
+            ResolverError::UnnecessaryPub { ident, position } => {
                 let name = &ident.0.contents;
 
-                let mut diag = Diagnostic::simple_error(
-                    format!("unnecessary pub keyword on parameter for function {name}"),
-                    "unnecessary pub parameter".to_string(),
+                let mut diag = Diagnostic::simple_warning(
+                    format!("unnecessary pub keyword on {position} for function {name}"),
+                    format!("unnecessary pub {position}"),
                     ident.0.span(),
                 );
 
diff --git a/crates/noirc_frontend/src/hir/resolution/resolver.rs b/crates/noirc_frontend/src/hir/resolution/resolver.rs
index ea0f341e983..29b3cc485d5 100644
--- a/crates/noirc_frontend/src/hir/resolution/resolver.rs
+++ b/crates/noirc_frontend/src/hir/resolution/resolver.rs
@@ -22,7 +22,7 @@ use std::collections::{HashMap, HashSet};
 use std::rc::Rc;
 
 use crate::graph::CrateId;
-use crate::hir::def_map::{ModuleDefId, TryFromModuleDefId, MAIN_FUNCTION};
+use crate::hir::def_map::{ModuleDefId, ModuleId, TryFromModuleDefId, MAIN_FUNCTION};
 use crate::hir_def::stmt::{HirAssignStatement, HirLValue, HirPattern};
 use crate::node_interner::{
     DefinitionId, DefinitionKind, ExprId, FuncId, NodeInterner, StmtId, StructId,
@@ -49,7 +49,7 @@ use crate::hir_def::{
     stmt::{HirConstrainStatement, HirLetStatement, HirStatement},
 };
 
-use super::errors::ResolverError;
+use super::errors::{PubPosition, ResolverError};
 
 const SELF_TYPE_NAME: &str = "Self";
 
@@ -137,6 +137,7 @@ impl<'a> Resolver<'a> {
         mut self,
         func: NoirFunction,
         func_id: FuncId,
+        module_id: ModuleId,
     ) -> (HirFunction, FuncMeta, Vec<ResolverError>) {
         self.scopes.start_function();
 
@@ -145,7 +146,7 @@ impl<'a> Resolver<'a> {
 
         self.add_generics(&func.def.generics);
 
-        let (hir_func, func_meta) = self.intern_function(func, func_id);
+        let (hir_func, func_meta) = self.intern_function(func, func_id, module_id);
         let func_scope_tree = self.scopes.end_function();
 
         self.check_for_unused_variables_in_scope_tree(func_scope_tree);
@@ -160,11 +161,12 @@ impl<'a> Resolver<'a> {
         }
 
         for unused_var in unused_vars.iter() {
-            let definition_info = self.interner.definition(unused_var.id);
-            let name = &definition_info.name;
-            if name != ERROR_IDENT && !definition_info.is_global() {
-                let ident = Ident(Spanned::from(unused_var.location.span, name.to_owned()));
-                self.push_err(ResolverError::UnusedVariable { ident });
+            if let Some(definition_info) = self.interner.try_definition(unused_var.id) {
+                let name = &definition_info.name;
+                if name != ERROR_IDENT && !definition_info.is_global() {
+                    let ident = Ident(Spanned::from(unused_var.location.span, name.to_owned()));
+                    self.push_err(ResolverError::UnusedVariable { ident });
+                }
             }
         }
     }
@@ -303,8 +305,13 @@ impl<'a> Resolver<'a> {
         }
     }
 
-    fn intern_function(&mut self, func: NoirFunction, id: FuncId) -> (HirFunction, FuncMeta) {
-        let func_meta = self.extract_meta(&func, id);
+    fn intern_function(
+        &mut self,
+        func: NoirFunction,
+        id: FuncId,
+        module_id: ModuleId,
+    ) -> (HirFunction, FuncMeta) {
+        let func_meta = self.extract_meta(&func, id, module_id);
         let hir_func = match func.kind {
             FunctionKind::Builtin | FunctionKind::LowLevel | FunctionKind::Oracle => {
                 HirFunction::empty()
@@ -326,11 +333,12 @@ impl<'a> Resolver<'a> {
             UnresolvedType::FieldElement(comp_time) => Type::FieldElement(comp_time),
             UnresolvedType::Array(size, elem) => {
                 let elem = Box::new(self.resolve_type_inner(*elem, new_variables));
-                if self.interner.enable_slices && size.is_none() {
-                    return Type::Slice(elem);
-                }
-                let resolved_size = self.resolve_array_size(size, new_variables);
-                Type::Array(Box::new(resolved_size), elem)
+                let size = if size.is_none() {
+                    Type::NotConstant
+                } else {
+                    self.resolve_array_size(size, new_variables)
+                };
+                Type::Array(Box::new(size), elem)
             }
             UnresolvedType::Expression(expr) => self.convert_expression_type(expr),
             UnresolvedType::Integer(comp_time, sign, bits) => Type::Integer(comp_time, sign, bits),
@@ -585,7 +593,12 @@ impl<'a> Resolver<'a> {
     /// to be used in analysis and intern the function parameters
     /// Prerequisite: self.add_generics() has already been called with the given
     /// function's generics, including any generics from the impl, if any.
-    fn extract_meta(&mut self, func: &NoirFunction, func_id: FuncId) -> FuncMeta {
+    fn extract_meta(
+        &mut self,
+        func: &NoirFunction,
+        func_id: FuncId,
+        module_id: ModuleId,
+    ) -> FuncMeta {
         let location = Location::new(func.name_ident().span(), self.file);
         let id = self.interner.function_definition_id(func_id);
         let name_ident = HirIdent { id, location };
@@ -605,7 +618,10 @@ impl<'a> Resolver<'a> {
 
         for (pattern, typ, visibility) in func.parameters().iter().cloned() {
             if visibility == noirc_abi::AbiVisibility::Public && !self.pub_allowed(func) {
-                self.push_err(ResolverError::UnnecessaryPub { ident: func.name_ident().clone() });
+                self.push_err(ResolverError::UnnecessaryPub {
+                    ident: func.name_ident().clone(),
+                    position: PubPosition::Parameter,
+                });
             }
 
             let pattern = self.resolve_pattern(pattern, DefinitionKind::Local(None));
@@ -619,6 +635,14 @@ impl<'a> Resolver<'a> {
 
         self.declare_numeric_generics(&parameter_types, &return_type);
 
+        if !self.pub_allowed(func) && func.def.return_visibility == noirc_abi::AbiVisibility::Public
+        {
+            self.push_err(ResolverError::UnnecessaryPub {
+                ident: func.name_ident().clone(),
+                position: PubPosition::ReturnType,
+            });
+        }
+
         // 'pub_allowed' also implies 'pub' is required on return types
         if self.pub_allowed(func)
             && return_type.as_ref() != &Type::Unit
@@ -651,6 +675,7 @@ impl<'a> Resolver<'a> {
             name: name_ident,
             kind: func.kind,
             attributes,
+            module_id,
             contract_function_type: self.handle_function_type(func),
             is_internal: self.handle_is_function_internal(func),
             is_unconstrained: func.def.is_unconstrained,
@@ -666,7 +691,7 @@ impl<'a> Resolver<'a> {
     /// True if the 'pub' keyword is allowed on parameters in this function
     fn pub_allowed(&self, func: &NoirFunction) -> bool {
         if self.in_contract() {
-            !func.def.is_unconstrained && !func.def.is_open
+            !func.def.is_unconstrained
         } else {
             func.name() == MAIN_FUNCTION
         }
@@ -753,10 +778,10 @@ impl<'a> Resolver<'a> {
             | Type::String(_)
             | Type::Unit
             | Type::Error
-            | Type::TypeVariable(_)
-            | Type::PolymorphicInteger(_, _)
+            | Type::TypeVariable(_, _)
             | Type::Constant(_)
             | Type::NamedGeneric(_, _)
+            | Type::NotConstant
             | Type::Forall(_, _) => (),
 
             Type::Array(length, _) => {
@@ -765,10 +790,6 @@ impl<'a> Resolver<'a> {
                 }
             }
 
-            Type::Slice(typ) => {
-                Self::find_numeric_generics_in_type(typ, found);
-            }
-
             Type::Tuple(fields) => {
                 for field in fields {
                     Self::find_numeric_generics_in_type(field, found);
@@ -883,6 +904,7 @@ impl<'a> Resolver<'a> {
                 }
                 Literal::Integer(integer) => HirLiteral::Integer(integer),
                 Literal::Str(str) => HirLiteral::Str(str),
+                Literal::Unit => HirLiteral::Unit,
             }),
             ExpressionKind::Variable(path) => {
                 // If the Path is being used as an Expression, then it is referring to a global from a separate module
@@ -948,7 +970,7 @@ impl<'a> Resolver<'a> {
                     let decl = this.add_variable_decl(
                         identifier,
                         false,
-                        false,
+                        true,
                         DefinitionKind::Local(None),
                     );
                     (decl, this.resolve_expression(block))
@@ -1049,7 +1071,7 @@ impl<'a> Resolver<'a> {
                     (Some(_), DefinitionKind::Local(_)) => DefinitionKind::Local(None),
                     (_, other) => other,
                 };
-                let id = self.add_variable_decl(name, mutable.is_some(), false, definition);
+                let id = self.add_variable_decl(name, mutable.is_some(), true, definition);
                 HirPattern::Identifier(id)
             }
             Pattern::Mutable(pattern, span) => {
@@ -1280,14 +1302,15 @@ pub fn verify_mutable_reference(interner: &NodeInterner, rhs: ExprId) -> Result<
             Err(ResolverError::MutableReferenceToArrayElement { span })
         }
         HirExpression::Ident(ident) => {
-            let definition = interner.definition(ident.id);
-            if !definition.mutable {
-                let span = interner.expr_span(&rhs);
-                let variable = definition.name.clone();
-                Err(ResolverError::MutableReferenceToImmutableVariable { span, variable })
-            } else {
-                Ok(())
+            if let Some(definition) = interner.try_definition(ident.id) {
+                if !definition.mutable {
+                    return Err(ResolverError::MutableReferenceToImmutableVariable {
+                        span: interner.expr_span(&rhs),
+                        variable: definition.name.clone(),
+                    });
+                }
             }
+            Ok(())
         }
         _ => Ok(()),
     }
@@ -1358,7 +1381,7 @@ mod test {
             let id = interner.push_fn(HirFunction::empty());
             interner.push_function_definition(func.name().to_string(), id);
             let resolver = Resolver::new(&mut interner, &path_resolver, &def_maps, file);
-            let (_, _, err) = resolver.resolve_function(func, id);
+            let (_, _, err) = resolver.resolve_function(func, id, ModuleId::dummy_id());
             errors.extend(err);
         }
 
@@ -1530,6 +1553,25 @@ mod test {
         assert!(errors.is_empty());
     }
 
+    #[test]
+    fn resolve_shadowing() {
+        let src = r#"
+            fn main(x : Field) {
+                let x = foo(x);
+                let x = x;
+                let (x, x) = (x, x);
+                let _ = x;
+            }
+
+            fn foo(x : Field) -> Field {
+                x
+            }
+        "#;
+
+        let errors = resolve_src_code(src, vec!["main", "foo"]);
+        assert!(errors.is_empty());
+    }
+
     fn path_unresolved_error(err: ResolverError, expected_unresolved_path: &str) {
         match err {
             ResolverError::PathResolutionError(PathResolutionError::Unresolved(name)) => {
diff --git a/crates/noirc_frontend/src/hir/type_check/errors.rs b/crates/noirc_frontend/src/hir/type_check/errors.rs
index b8d4cc66c18..4f032503f3d 100644
--- a/crates/noirc_frontend/src/hir/type_check/errors.rs
+++ b/crates/noirc_frontend/src/hir/type_check/errors.rs
@@ -5,6 +5,25 @@ use thiserror::Error;
 use crate::hir::resolution::errors::ResolverError;
 use crate::hir_def::expr::HirBinaryOp;
 use crate::hir_def::types::Type;
+use crate::Signedness;
+
+#[derive(Error, Debug, Clone, PartialEq, Eq)]
+pub enum Source {
+    #[error("Binary")]
+    Binary,
+    #[error("Assignment")]
+    Assignment,
+    #[error("ArrayElements")]
+    ArrayElements,
+    #[error("ArrayLen")]
+    ArrayLen,
+    #[error("StringLen")]
+    StringLen,
+    #[error("Comparison")]
+    Comparison,
+    #[error("BinOp")]
+    BinOp,
+}
 
 #[derive(Error, Debug, Clone, PartialEq, Eq)]
 pub enum TypeCheckError {
@@ -14,14 +33,54 @@ pub enum TypeCheckError {
     TypeCannotBeUsed { typ: Type, place: &'static str, span: Span },
     #[error("Expected type {expected_typ:?} is not the same as {expr_typ:?}")]
     TypeMismatch { expected_typ: String, expr_typ: String, expr_span: Span },
+    #[error("Expected type {lhs} is not the same as {rhs}")]
+    TypeMismatchWithSource { lhs: Type, rhs: Type, span: Span, source: Source },
     #[error("Expected {expected:?} found {found:?}")]
     ArityMisMatch { expected: u16, found: u16, span: Span },
     #[error("Return type in a function cannot be public")]
     PublicReturnType { typ: Type, span: Span },
-    // XXX: unstructured errors are not ideal for testing.
-    // They will be removed in a later iteration
-    #[error("Unstructured msg: {msg:?}")]
-    Unstructured { msg: String, span: Span },
+    #[error("Cannot cast type {from}, 'as' is only for primitive field or integer types")]
+    InvalidCast { from: Type, span: Span },
+    #[error("Expected a function, but found a(n) {found}")]
+    ExpectedFunction { found: Type, span: Span },
+    #[error("Type {lhs_type} has no member named {field_name}")]
+    AccessUnknownMember { lhs_type: Type, field_name: String, span: Span },
+    #[error("Function expects {expected} parameters but {found} given")]
+    ParameterCountMismatch { expected: usize, found: usize, span: Span },
+    #[error("The value is non-comptime because of this expression, which uses another non-comptime value")]
+    NotCompTime { span: Span },
+    #[error(
+        "The value is comptime because of this expression, which forces the value to be comptime"
+    )]
+    CompTime { span: Span },
+    #[error("Cannot cast to a comptime type, argument to cast is not known at compile-time")]
+    CannotCastToComptimeType { span: Span },
+    #[error("Only integer and Field types may be casted to")]
+    UnsupportedCast { span: Span },
+    #[error("Index {index} is out of bounds for this tuple {lhs_type} of length {length}")]
+    TupleIndexOutOfBounds { index: usize, lhs_type: Type, length: usize, span: Span },
+    #[error("Variable {name} must be mutable to be assigned to")]
+    VariableMustBeMutable { name: String, span: Span },
+    #[error("No method named '{method_name}' found for type '{object_type}'")]
+    UnresolvedMethodCall { method_name: String, object_type: Type, span: Span },
+    #[error("Comparisons are invalid on Field types. Try casting the operands to a sized integer type first")]
+    InvalidComparisonOnField { span: Span },
+    #[error("Integers must have the same signedness LHS is {sign_x:?}, RHS is {sign_y:?}")]
+    IntegerSignedness { sign_x: Signedness, sign_y: Signedness, span: Span },
+    #[error("Integers must have the same bit width LHS is {bit_width_x}, RHS is {bit_width_y}")]
+    IntegerBitWidth { bit_width_x: u32, bit_width_y: u32, span: Span },
+    #[error("{kind} cannot be used in an infix operation")]
+    InvalidInfixOp { kind: &'static str, span: Span },
+    #[error("Bitwise operations are invalid on Field types. Try casting the operands to a sized integer type first.")]
+    InvalidBitwiseOperationOnField { span: Span },
+    #[error("Integer cannot be used with type {typ}")]
+    IntegerTypeMismatch { typ: Type, span: Span },
+    #[error("Cannot use an integer and a Field in a binary operation, try converting the Field into an integer first")]
+    IntegerAndFieldBinaryOperation { span: Span },
+    #[error("Fields cannot be compared, try casting to an integer first")]
+    FieldComparison { span: Span },
+    #[error("The number of bits to use for this bitwise operation is ambiguous. Either the operand's type or return type should be specified")]
+    AmbiguousBitWidth { span: Span },
     #[error("Error with additional context")]
     Context { err: Box<TypeCheckError>, ctx: &'static str },
     #[error("Array is not homogeneous")]
@@ -35,6 +94,8 @@ pub enum TypeCheckError {
     },
     #[error("Cannot infer type of expression, type annotations needed before this point")]
     TypeAnnotationsNeeded { span: Span },
+    #[error("use of deprecated function {name}")]
+    CallDeprecated { name: String, note: Option<String>, span: Span },
     #[error("{0}")]
     ResolverError(ResolverError),
 }
@@ -93,9 +154,33 @@ impl From<TypeCheckError> for Diagnostic {
                 let msg = format!("Expected {expected} argument{plural}, but found {found}");
                 Diagnostic::simple_error(msg, String::new(), span)
             }
-            TypeCheckError::Unstructured { msg, span } => {
+            TypeCheckError::ParameterCountMismatch { expected, found, span } => {
+                let empty_or_s = if expected == 1 { "" } else { "s" };
+                let was_or_were = if found == 1 { "was" } else { "were" };
+                let msg = format!("Function expects {expected} parameter{empty_or_s} but {found} {was_or_were} given");
                 Diagnostic::simple_error(msg, String::new(), span)
             }
+            TypeCheckError::InvalidCast { span, .. }
+            | TypeCheckError::ExpectedFunction { span, .. }
+            | TypeCheckError::AccessUnknownMember { span, .. }
+            | TypeCheckError::CompTime { span }
+            | TypeCheckError::NotCompTime { span }
+            | TypeCheckError::CannotCastToComptimeType { span }
+            | TypeCheckError::UnsupportedCast { span }
+            | TypeCheckError::TupleIndexOutOfBounds { span, .. }
+            | TypeCheckError::VariableMustBeMutable { span, .. }
+            | TypeCheckError::UnresolvedMethodCall { span, .. }
+            | TypeCheckError::InvalidComparisonOnField { span }
+            | TypeCheckError::IntegerSignedness { span, .. }
+            | TypeCheckError::IntegerBitWidth { span, .. }
+            | TypeCheckError::InvalidInfixOp { span, .. }
+            | TypeCheckError::InvalidBitwiseOperationOnField { span, .. }
+            | TypeCheckError::IntegerTypeMismatch { span, .. }
+            | TypeCheckError::FieldComparison { span, .. }
+            | TypeCheckError::AmbiguousBitWidth { span, .. }
+            | TypeCheckError::IntegerAndFieldBinaryOperation { span } => {
+                Diagnostic::simple_error(error.to_string(), String::new(), span)
+            }
             TypeCheckError::PublicReturnType { typ, span } => Diagnostic::simple_error(
                 "Functions cannot declare a public return type".to_string(),
                 format!("return type is {typ}"),
@@ -107,6 +192,27 @@ impl From<TypeCheckError> for Diagnostic {
                 span,
             ),
             TypeCheckError::ResolverError(error) => error.into(),
+            TypeCheckError::TypeMismatchWithSource { lhs, rhs, span, source } => {
+                let message = match source {
+                    Source::Binary => format!("Types in a binary operation should match, but found {lhs} and {rhs}"),
+                    Source::Assignment => {
+                        format!("Cannot assign an expression of type {lhs} to a value of type {rhs}")
+                    }
+                    Source::ArrayElements => format!("Cannot compare {lhs} and {rhs}, the array element types differ"),
+                    Source::ArrayLen => format!("Can only compare arrays of the same length. Here LHS is of length {lhs}, and RHS is {rhs}"),
+                    Source::StringLen => format!("Can only compare strings of the same length. Here LHS is of length {lhs}, and RHS is {rhs}"),
+                    Source::Comparison => format!("Unsupported types for comparison: {lhs} and {rhs}"),
+                    Source::BinOp => format!("Unsupported types for binary operation: {lhs} and {rhs}"),
+                };
+
+                Diagnostic::simple_error(message, String::new(), span)
+            }
+            TypeCheckError::CallDeprecated { span, ref note, .. } => {
+                let primary_message = error.to_string();
+                let secondary_message = note.clone().unwrap_or_default();
+
+                Diagnostic::simple_warning(primary_message, secondary_message, span)
+            }
         }
     }
 }
diff --git a/crates/noirc_frontend/src/hir/type_check/expr.rs b/crates/noirc_frontend/src/hir/type_check/expr.rs
index 5b89f72841b..b19833fb311 100644
--- a/crates/noirc_frontend/src/hir/type_check/expr.rs
+++ b/crates/noirc_frontend/src/hir/type_check/expr.rs
@@ -2,7 +2,7 @@ use iter_extended::vecmap;
 use noirc_errors::Span;
 
 use crate::{
-    hir::resolution::resolver::verify_mutable_reference,
+    hir::{resolution::resolver::verify_mutable_reference, type_check::errors::Source},
     hir_def::{
         expr::{
             self, HirArrayLiteral, HirBinaryOp, HirExpression, HirLiteral, HirMethodCallExpression,
@@ -10,13 +10,32 @@ use crate::{
         },
         types::Type,
     },
-    node_interner::{ExprId, FuncId},
-    CompTime, Shared, TypeBinding, UnaryOp,
+    node_interner::{DefinitionKind, ExprId, FuncId},
+    token::Attribute::Deprecated,
+    CompTime, Shared, TypeBinding, TypeVariableKind, UnaryOp,
 };
 
 use super::{errors::TypeCheckError, TypeChecker};
 
 impl<'interner> TypeChecker<'interner> {
+    fn check_if_deprecated(&mut self, expr: &ExprId) {
+        if let HirExpression::Ident(expr::HirIdent { location, id }) =
+            self.interner.expression(expr)
+        {
+            if let Some(DefinitionKind::Function(func_id)) =
+                self.interner.try_definition(id).map(|def| &def.kind)
+            {
+                let meta = self.interner.function_meta(func_id);
+                if let Some(Deprecated(note)) = meta.attributes {
+                    self.errors.push(TypeCheckError::CallDeprecated {
+                        name: self.interner.definition_name(id).to_string(),
+                        note,
+                        span: location.span,
+                    });
+                }
+            }
+        }
+    }
     /// Infers a type for a given expression, and return this type.
     /// As a side-effect, this function will also remember this type in the NodeInterner
     /// for the given expr_id key.
@@ -48,7 +67,7 @@ impl<'interner> TypeChecker<'interner> {
                             .unwrap_or_else(|| self.interner.next_type_variable());
 
                         let arr_type = Type::Array(
-                            Box::new(Type::Constant(arr.len() as u64)),
+                            Box::new(Type::constant_variable(arr.len() as u64, self.interner)),
                             Box::new(first_elem_type.clone()),
                         );
 
@@ -78,6 +97,12 @@ impl<'interner> TypeChecker<'interner> {
                     }
                     HirLiteral::Array(HirArrayLiteral::Repeated { repeated_element, length }) => {
                         let elem_type = self.check_expression(&repeated_element);
+                        let length = match length {
+                            Type::Constant(length) => {
+                                Type::constant_variable(length, self.interner)
+                            }
+                            other => other,
+                        };
                         Type::Array(Box::new(length), Box::new(elem_type))
                     }
                     HirLiteral::Bool(_) => Type::Bool(CompTime::new(self.interner)),
@@ -86,6 +111,7 @@ impl<'interner> TypeChecker<'interner> {
                         let len = Type::Constant(string.len() as u64);
                         Type::String(Box::new(len))
                     }
+                    HirLiteral::Unit => Type::Unit,
                 }
             }
             HirExpression::Infix(infix_expr) => {
@@ -105,10 +131,12 @@ impl<'interner> TypeChecker<'interner> {
             }
             HirExpression::Index(index_expr) => self.check_index_expression(index_expr),
             HirExpression::Call(call_expr) => {
+                self.check_if_deprecated(&call_expr.func);
+
                 let function = self.check_expression(&call_expr.func);
                 let args = vecmap(&call_expr.arguments, |arg| {
                     let typ = self.check_expression(arg);
-                    (typ, self.interner.expr_span(arg))
+                    (typ, *arg, self.interner.expr_span(arg))
                 });
                 let span = self.interner.expr_span(expr_id);
                 self.bind_function_type(function, args, span)
@@ -116,16 +144,18 @@ impl<'interner> TypeChecker<'interner> {
             HirExpression::MethodCall(mut method_call) => {
                 let object_type = self.check_expression(&method_call.object).follow_bindings();
                 let method_name = method_call.method.0.contents.as_str();
-                match self.lookup_method(object_type.clone(), method_name, expr_id) {
+                match self.lookup_method(&object_type, method_name, expr_id) {
                     Some(method_id) => {
-                        let mut args =
-                            vec![(object_type, self.interner.expr_span(&method_call.object))];
+                        let mut args = vec![(
+                            object_type,
+                            method_call.object,
+                            self.interner.expr_span(&method_call.object),
+                        )];
 
-                        let mut arg_types = vecmap(&method_call.arguments, |arg| {
+                        for arg in &method_call.arguments {
                             let typ = self.check_expression(arg);
-                            (typ, self.interner.expr_span(arg))
-                        });
-                        args.append(&mut arg_types);
+                            args.push((typ, *arg, self.interner.expr_span(arg)));
+                        }
 
                         // Desugar the method call into a normal, resolved function call
                         // so that the backend doesn't need to worry about methods
@@ -184,7 +214,10 @@ impl<'interner> TypeChecker<'interner> {
                 };
                 let fresh_id = self.interner.next_type_variable_id();
                 let type_variable = Shared::new(TypeBinding::Unbound(fresh_id));
-                let expected_type = Type::PolymorphicInteger(expected_comptime, type_variable);
+                let expected_type = Type::TypeVariable(
+                    type_variable,
+                    TypeVariableKind::IntegerOrField(expected_comptime),
+                );
 
                 self.unify(&start_range_type, &expected_type, range_span, || {
                     TypeCheckError::TypeCannotBeUsed {
@@ -268,11 +301,17 @@ impl<'interner> TypeChecker<'interner> {
     /// if the given object type is already a mutable reference. If not, add one.
     /// This is used to automatically transform a method call: `foo.bar()` into a function
     /// call: `bar(&mut foo)`.
+    ///
+    /// A notable corner case of this function is where it interacts with auto-deref of `.`.
+    /// If a field is being mutated e.g. `foo.bar.mutate_bar()` where `foo: &mut Foo`, the compiler
+    /// will insert a dereference before bar `(*foo).bar.mutate_bar()` which would cause us to
+    /// mutate a copy of bar rather than a reference to it. We must check for this corner case here
+    /// and remove the implicitly added dereference operator if we find one.
     fn try_add_mutable_reference_to_object(
         &mut self,
         method_call: &mut HirMethodCallExpression,
         function_type: &Type,
-        argument_types: &mut [(Type, noirc_errors::Span)],
+        argument_types: &mut [(Type, ExprId, noirc_errors::Span)],
     ) {
         let expected_object_type = match function_type {
             Type::Function(args, _) => args.get(0),
@@ -287,25 +326,63 @@ impl<'interner> TypeChecker<'interner> {
             if matches!(expected_object_type.follow_bindings(), Type::MutableReference(_)) {
                 let actual_type = argument_types[0].0.follow_bindings();
 
-                if let Err(error) = verify_mutable_reference(self.interner, method_call.object) {
-                    self.errors.push(TypeCheckError::ResolverError(error));
-                }
-
                 if !matches!(actual_type, Type::MutableReference(_)) {
-                    let new_type = Type::MutableReference(Box::new(actual_type));
+                    if let Err(error) = verify_mutable_reference(self.interner, method_call.object)
+                    {
+                        self.errors.push(TypeCheckError::ResolverError(error));
+                    }
 
+                    let new_type = Type::MutableReference(Box::new(actual_type));
                     argument_types[0].0 = new_type.clone();
-                    method_call.object =
-                        self.interner.push_expr(HirExpression::Prefix(HirPrefixExpression {
-                            operator: UnaryOp::MutableReference,
-                            rhs: method_call.object,
-                        }));
-                    self.interner.push_expr_type(&method_call.object, new_type);
+
+                    // First try to remove a dereference operator that may have been implicitly
+                    // inserted by a field access expression `foo.bar` on a mutable reference `foo`.
+                    if self.try_remove_implicit_dereference(method_call.object).is_none() {
+                        // If that didn't work, then wrap the whole expression in an `&mut`
+                        method_call.object =
+                            self.interner.push_expr(HirExpression::Prefix(HirPrefixExpression {
+                                operator: UnaryOp::MutableReference,
+                                rhs: method_call.object,
+                            }));
+                        self.interner.push_expr_type(&method_call.object, new_type);
+                    }
                 }
             }
         }
     }
 
+    /// Given a method object: `(*foo).bar` of a method call `(*foo).bar.baz()`, remove the
+    /// implicitly added dereference operator if one is found.
+    ///
+    /// Returns Some(()) if a dereference was removed and None otherwise.
+    fn try_remove_implicit_dereference(&mut self, object: ExprId) -> Option<()> {
+        match self.interner.expression(&object) {
+            HirExpression::MemberAccess(access) => {
+                self.try_remove_implicit_dereference(access.lhs)?;
+
+                // Since we removed a dereference, instead of returning the field directly,
+                // we expect to be returning a reference to the field, so update the type accordingly.
+                let current_type = self.interner.id_type(object);
+                let reference_type = Type::MutableReference(Box::new(current_type));
+                self.interner.push_expr_type(&object, reference_type);
+                Some(())
+            }
+            HirExpression::Prefix(prefix) => match prefix.operator {
+                UnaryOp::Dereference { implicitly_added: true } => {
+                    // Found a dereference we can remove. Now just replace it with its rhs to remove it.
+                    let rhs = self.interner.expression(&prefix.rhs);
+                    self.interner.replace_expr(&object, rhs);
+
+                    let rhs_type = self.interner.id_type(prefix.rhs);
+                    self.interner.push_expr_type(&object, rhs_type);
+                    Some(())
+                }
+                _ => None,
+            },
+            _ => None,
+        }
+    }
+
     fn check_index_expression(&mut self, index_expr: expr::HirIndexExpression) -> Type {
         let index_type = self.check_expression(&index_expr.index);
         let span = self.interner.expr_span(&index_expr.index);
@@ -323,7 +400,6 @@ impl<'interner> TypeChecker<'interner> {
             // XXX: We can check the array bounds here also, but it may be better to constant fold first
             // and have ConstId instead of ExprId for constants
             Type::Array(_, base_type) => *base_type,
-            Type::Slice(base_type) => *base_type,
             Type::Error => Type::Error,
             typ => {
                 let span = self.interner.expr_span(&index_expr.collection);
@@ -338,33 +414,28 @@ impl<'interner> TypeChecker<'interner> {
     }
 
     fn check_cast(&mut self, from: Type, to: Type, span: Span) -> Type {
-        let is_comp_time = match from {
+        let is_comp_time = match from.follow_bindings() {
             Type::Integer(is_comp_time, ..) => is_comp_time,
             Type::FieldElement(is_comp_time) => is_comp_time,
-            Type::PolymorphicInteger(is_comp_time, binding) => match &*binding.borrow() {
-                TypeBinding::Bound(from) => return self.check_cast(from.clone(), to, span),
-                TypeBinding::Unbound(_) => is_comp_time,
-            },
+            Type::TypeVariable(_, TypeVariableKind::IntegerOrField(is_comp_time)) => is_comp_time,
+            Type::TypeVariable(_, _) => {
+                self.errors.push(TypeCheckError::TypeAnnotationsNeeded { span });
+                return Type::Error;
+            }
             Type::Bool(is_comp_time) => is_comp_time,
             Type::Error => return Type::Error,
             from => {
-                let msg = format!(
-                    "Cannot cast type {from}, 'as' is only for primitive field or integer types",
-                );
-                self.errors.push(TypeCheckError::Unstructured { msg, span });
+                self.errors.push(TypeCheckError::InvalidCast { from, span });
                 return Type::Error;
             }
         };
 
-        let error_message =
-            "Cannot cast to a comptime type, argument to cast is not known at compile-time";
         match to {
             Type::Integer(dest_comp_time, sign, bits) => {
                 if dest_comp_time.is_comp_time()
                     && is_comp_time.unify(&dest_comp_time, span).is_err()
                 {
-                    let msg = error_message.into();
-                    self.errors.push(TypeCheckError::Unstructured { msg, span });
+                    self.errors.push(TypeCheckError::CannotCastToComptimeType { span });
                 }
 
                 Type::Integer(is_comp_time, sign, bits)
@@ -373,8 +444,7 @@ impl<'interner> TypeChecker<'interner> {
                 if dest_comp_time.is_comp_time()
                     && is_comp_time.unify(&dest_comp_time, span).is_err()
                 {
-                    let msg = error_message.into();
-                    self.errors.push(TypeCheckError::Unstructured { msg, span });
+                    self.errors.push(TypeCheckError::CannotCastToComptimeType { span });
                 }
 
                 Type::FieldElement(is_comp_time)
@@ -383,15 +453,13 @@ impl<'interner> TypeChecker<'interner> {
                 if dest_comp_time.is_comp_time()
                     && is_comp_time.unify(&dest_comp_time, span).is_err()
                 {
-                    let msg = error_message.into();
-                    self.errors.push(TypeCheckError::Unstructured { msg, span });
+                    self.errors.push(TypeCheckError::CannotCastToComptimeType { span });
                 }
                 Type::Bool(dest_comp_time)
             }
             Type::Error => Type::Error,
             _ => {
-                let msg = "Only integer and Field types may be casted to".into();
-                self.errors.push(TypeCheckError::Unstructured { msg, span });
+                self.errors.push(TypeCheckError::UnsupportedCast { span });
                 Type::Error
             }
         }
@@ -403,7 +471,7 @@ impl<'interner> TypeChecker<'interner> {
         &mut self,
         function_ident_id: &ExprId,
         func_id: &FuncId,
-        arguments: Vec<(Type, Span)>,
+        arguments: Vec<(Type, ExprId, Span)>,
         span: Span,
     ) -> Type {
         if func_id == &FuncId::dummy_id() {
@@ -500,7 +568,7 @@ impl<'interner> TypeChecker<'interner> {
                 let arg_type = self.check_expression(&arg);
 
                 let span = self.interner.expr_span(expr_id);
-                self.make_subtype_of(&arg_type, &param_type, span, || {
+                self.make_subtype_of(&arg_type, &param_type, arg, || {
                     TypeCheckError::TypeMismatch {
                         expected_typ: param_type.to_string(),
                         expr_typ: arg_type.to_string(),
@@ -521,7 +589,7 @@ impl<'interner> TypeChecker<'interner> {
         let dereference_lhs = |this: &mut Self, lhs_type, element| {
             let old_lhs = *access_lhs;
             *access_lhs = this.interner.push_expr(HirExpression::Prefix(HirPrefixExpression {
-                operator: crate::UnaryOp::Dereference,
+                operator: crate::UnaryOp::Dereference { implicitly_added: true },
                 rhs: old_lhs,
             }));
             this.interner.push_expr_type(&old_lhs, lhs_type);
@@ -574,8 +642,10 @@ impl<'interner> TypeChecker<'interner> {
                     if index < length {
                         return Some((elements[index].clone(), index));
                     } else {
-                        self.errors.push(TypeCheckError::Unstructured {
-                            msg: format!("Index {index} is out of bounds for this tuple {lhs_type} of length {length}"),
+                        self.errors.push(TypeCheckError::TupleIndexOutOfBounds {
+                            index,
+                            lhs_type,
+                            length,
                             span,
                         });
                         return None;
@@ -596,8 +666,11 @@ impl<'interner> TypeChecker<'interner> {
         if let Type::TypeVariable(..) = &lhs_type {
             self.errors.push(TypeCheckError::TypeAnnotationsNeeded { span });
         } else if lhs_type != Type::Error {
-            let msg = format!("Type {lhs_type} has no member named {field_name}");
-            self.errors.push(TypeCheckError::Unstructured { msg, span });
+            self.errors.push(TypeCheckError::AccessUnknownMember {
+                lhs_type,
+                field_name: field_name.to_string(),
+                span,
+            });
         }
 
         None
@@ -609,21 +682,17 @@ impl<'interner> TypeChecker<'interner> {
         rhs_type: &Type,
         op: &HirBinaryOp,
         span: Span,
-    ) -> Result<Type, String> {
+    ) -> Result<Type, TypeCheckError> {
         use crate::BinaryOpKind::{Equal, NotEqual};
         use Type::*;
-        let make_error = move |msg| TypeCheckError::Unstructured { msg, span };
 
-        match (lhs_type, rhs_type)  {
+        match (lhs_type, rhs_type) {
             // Avoid reporting errors multiple times
-            (Error, _) | (_,Error) => Ok(Bool(CompTime::Yes(None))),
+            (Error, _) | (_, Error) => Ok(Bool(CompTime::Yes(None))),
 
-            // Matches on PolymorphicInteger and TypeVariable must be first to follow any type
+            // Matches on TypeVariable must be first to follow any type
             // bindings.
-            (var @ PolymorphicInteger(_, int), other)
-            | (other, var @ PolymorphicInteger(_, int))
-            | (var @ TypeVariable(int), other)
-            | (other, var @ TypeVariable(int)) => {
+            (var @ TypeVariable(int, _), other) | (other, var @ TypeVariable(int, _)) => {
                 if let TypeBinding::Bound(binding) = &*int.borrow() {
                     return self.comparator_operand_type_rules(other, binding, op, span);
                 }
@@ -633,7 +702,7 @@ impl<'interner> TypeChecker<'interner> {
 
                     self.push_delayed_type_check(Box::new(move || {
                         if other.is_field() || other.is_bindable() {
-                            Err(make_error("Comparisons are invalid on Field types. Try casting the operands to a sized integer type first".into()))
+                            Err(TypeCheckError::InvalidComparisonOnField { span })
                         } else {
                             Ok(())
                         }
@@ -641,34 +710,52 @@ impl<'interner> TypeChecker<'interner> {
                 }
 
                 let comptime = var.try_get_comptime();
-                if other.try_bind_to_polymorphic_int(int, &comptime, true, op.location.span).is_ok() || other == &Type::Error {
+                if other.try_bind_to_polymorphic_int(int, &comptime, true, op.location.span).is_ok()
+                    || other == &Type::Error
+                {
                     Ok(Bool(comptime.into_owned()))
                 } else {
-                    Err(format!("Types in a binary operation should match, but found {lhs_type} and {rhs_type}"))
+                    Err(TypeCheckError::TypeMismatchWithSource {
+                        rhs: lhs_type.clone(),
+                        lhs: rhs_type.clone(),
+                        span,
+                        source: Source::Binary,
+                    })
                 }
             }
-            (Integer(comptime_x, sign_x, bit_width_x), Integer(comptime_y, sign_y, bit_width_y)) => {
+            (
+                Integer(comptime_x, sign_x, bit_width_x),
+                Integer(comptime_y, sign_y, bit_width_y),
+            ) => {
                 if sign_x != sign_y {
-                    return Err(format!("Integers must have the same signedness LHS is {sign_x:?}, RHS is {sign_y:?} "))
+                    return Err(TypeCheckError::IntegerSignedness {
+                        sign_x: *sign_x,
+                        sign_y: *sign_y,
+                        span,
+                    });
                 }
                 if bit_width_x != bit_width_y {
-                    return Err(format!("Integers must have the same bit width LHS is {bit_width_x}, RHS is {bit_width_y} "))
+                    return Err(TypeCheckError::IntegerBitWidth {
+                        bit_width_x: *bit_width_x,
+                        bit_width_y: *bit_width_y,
+                        span,
+                    });
                 }
                 let comptime = comptime_x.and(comptime_y, op.location.span);
                 Ok(Bool(comptime))
             }
-            (Integer(..), FieldElement(..)) | ( FieldElement(..), Integer(..) ) => {
-                Err("Cannot use an integer and a Field in a binary operation, try converting the Field into an integer first".to_string())
+            (Integer(..), FieldElement(..)) | (FieldElement(..), Integer(..)) => {
+                Err(TypeCheckError::IntegerAndFieldBinaryOperation { span })
             }
-            (Integer(..), typ) | (typ,Integer(..)) => {
-                Err(format!("Integer cannot be used with type {typ}"))
+            (Integer(..), typ) | (typ, Integer(..)) => {
+                Err(TypeCheckError::IntegerTypeMismatch { typ: typ.clone(), span })
             }
             (FieldElement(comptime_x), FieldElement(comptime_y)) => {
                 if op.kind.is_valid_for_field_type() {
                     let comptime = comptime_x.and(comptime_y, op.location.span);
                     Ok(Bool(comptime))
                 } else {
-                    Err("Fields cannot be compared, try casting to an integer first".into())
+                    Err(TypeCheckError::FieldComparison { span })
                 }
             }
 
@@ -679,17 +766,23 @@ impl<'interner> TypeChecker<'interner> {
             }
 
             // Special-case == and != for arrays
-            (Array(x_size, x_type), Array(y_size, y_type)) if matches!(op.kind, Equal | NotEqual) => {
+            (Array(x_size, x_type), Array(y_size, y_type))
+                if matches!(op.kind, Equal | NotEqual) =>
+            {
                 x_type.unify(y_type, op.location.span, &mut self.errors, || {
-                    TypeCheckError::Unstructured {
-                        msg: format!("Cannot compare {lhs_type} and {rhs_type}, the array element types differ"),
+                    TypeCheckError::TypeMismatchWithSource {
+                        rhs: lhs_type.clone(),
+                        lhs: rhs_type.clone(),
+                        source: Source::ArrayElements,
                         span: op.location.span,
                     }
                 });
 
                 self.unify(x_size, y_size, op.location.span, || {
-                    TypeCheckError::Unstructured {
-                        msg: format!("Can only compare arrays of the same length. Here LHS is of length {x_size}, and RHS is {y_size}"),
+                    TypeCheckError::TypeMismatchWithSource {
+                        rhs: lhs_type.clone(),
+                        lhs: rhs_type.clone(),
+                        source: Source::ArrayLen,
                         span: op.location.span,
                     }
                 });
@@ -697,47 +790,61 @@ impl<'interner> TypeChecker<'interner> {
                 // We could check if all elements of all arrays are comptime but I am lazy
                 Ok(Bool(CompTime::No(Some(op.location.span))))
             }
-            (NamedGeneric(binding_a, name_a), NamedGeneric(binding_b, name_b)) => {
+            (lhs @ NamedGeneric(binding_a, _), rhs @ NamedGeneric(binding_b, _)) => {
                 if binding_a == binding_b {
                     return Ok(Bool(CompTime::No(Some(op.location.span))));
                 }
-                Err(format!("Unsupported types for comparison: {name_a} and {name_b}"))
+                Err(TypeCheckError::TypeMismatchWithSource {
+                    rhs: lhs.clone(),
+                    lhs: rhs.clone(),
+                    source: Source::Comparison,
+                    span,
+                })
             }
             (String(x_size), String(y_size)) => {
                 x_size.unify(y_size, op.location.span, &mut self.errors, || {
-                    TypeCheckError::Unstructured {
-                        msg: format!("Can only compare strings of the same length. Here LHS is of length {x_size}, and RHS is {y_size} "),
+                    TypeCheckError::TypeMismatchWithSource {
+                        rhs: *x_size.clone(),
+                        lhs: *y_size.clone(),
                         span: op.location.span,
+                        source: Source::StringLen,
                     }
                 });
 
                 Ok(Bool(CompTime::No(Some(op.location.span))))
             }
-            (lhs, rhs) => Err(format!("Unsupported types for comparison: {lhs} and {rhs}")),
+            (lhs, rhs) => Err(TypeCheckError::TypeMismatchWithSource {
+                rhs: lhs.clone(),
+                lhs: rhs.clone(),
+                source: Source::Comparison,
+                span,
+            }),
         }
     }
 
     fn lookup_method(
         &mut self,
-        object_type: Type,
+        object_type: &Type,
         method_name: &str,
         expr_id: &ExprId,
     ) -> Option<FuncId> {
-        match &object_type {
+        match object_type {
             Type::Struct(typ, _args) => {
                 match self.interner.lookup_method(typ.borrow().id, method_name) {
                     Some(method_id) => Some(method_id),
                     None => {
-                        self.errors.push(TypeCheckError::Unstructured {
+                        self.errors.push(TypeCheckError::UnresolvedMethodCall {
+                            method_name: method_name.to_string(),
+                            object_type: object_type.clone(),
                             span: self.interner.expr_span(expr_id),
-                            msg: format!(
-                                "No method named '{method_name}' found for type '{object_type}'",
-                            ),
                         });
                         None
                     }
                 }
             }
+            // Mutable references to another type should resolve to methods of their element type.
+            // This may be a struct or a primitive type.
+            Type::MutableReference(element) => self.lookup_method(element, method_name, expr_id),
             // If we fail to resolve the object to a struct type, we have no way of type
             // checking its arguments as we can't even resolve the name of the function
             Type::Error => None,
@@ -747,9 +854,10 @@ impl<'interner> TypeChecker<'interner> {
             other => match self.interner.lookup_primitive_method(other, method_name) {
                 Some(method_id) => Some(method_id),
                 None => {
-                    self.errors.push(TypeCheckError::Unstructured {
+                    self.errors.push(TypeCheckError::UnresolvedMethodCall {
+                        method_name: method_name.to_string(),
+                        object_type: object_type.clone(),
                         span: self.interner.expr_span(expr_id),
-                        msg: format!("No method named '{method_name}' found for type '{other}'",),
                     });
                     None
                 }
@@ -757,58 +865,58 @@ impl<'interner> TypeChecker<'interner> {
         }
     }
 
-    fn bind_function_type(&mut self, function: Type, args: Vec<(Type, Span)>, span: Span) -> Type {
+    fn bind_function_type(
+        &mut self,
+        function: Type,
+        args: Vec<(Type, ExprId, Span)>,
+        span: Span,
+    ) -> Type {
         // Could do a single unification for the entire function type, but matching beforehand
         // lets us issue a more precise error on the individual argument that fails to type check.
         match function {
-            Type::TypeVariable(binding) => {
+            Type::TypeVariable(binding, TypeVariableKind::Normal) => {
                 if let TypeBinding::Bound(typ) = &*binding.borrow() {
                     return self.bind_function_type(typ.clone(), args, span);
                 }
 
                 let ret = self.interner.next_type_variable();
-                let args = vecmap(args, |(arg, _)| arg);
+                let args = vecmap(args, |(arg, _, _)| arg);
                 let expected = Type::Function(args, Box::new(ret.clone()));
-                *binding.borrow_mut() = TypeBinding::Bound(expected);
 
+                if let Err(error) = binding.borrow_mut().bind_to(expected, span) {
+                    self.errors.push(error);
+                }
                 ret
             }
             Type::Function(parameters, ret) => {
                 if parameters.len() != args.len() {
-                    let empty_or_s = if parameters.len() == 1 { "" } else { "s" };
-                    let was_or_were = if args.len() == 1 { "was" } else { "were" };
-
-                    self.errors.push(TypeCheckError::Unstructured {
-                        msg: format!(
-                            "Function expects {} parameter{} but {} {} given",
-                            parameters.len(),
-                            empty_or_s,
-                            args.len(),
-                            was_or_were
-                        ),
+                    self.errors.push(TypeCheckError::ParameterCountMismatch {
+                        expected: parameters.len(),
+                        found: args.len(),
                         span,
                     });
                     return Type::Error;
                 }
 
-                for (param, (arg, arg_span)) in parameters.iter().zip(args) {
-                    arg.make_subtype_of(param, arg_span, &mut self.errors, || {
-                        TypeCheckError::TypeMismatch {
+                for (param, (arg, arg_id, arg_span)) in parameters.iter().zip(args) {
+                    arg.make_subtype_with_coercions(
+                        param,
+                        arg_id,
+                        self.interner,
+                        &mut self.errors,
+                        || TypeCheckError::TypeMismatch {
                             expected_typ: param.to_string(),
                             expr_typ: arg.to_string(),
                             expr_span: arg_span,
-                        }
-                    });
+                        },
+                    );
                 }
 
                 *ret
             }
             Type::Error => Type::Error,
-            other => {
-                self.errors.push(TypeCheckError::Unstructured {
-                    msg: format!("Expected a function, but found a(n) {other}"),
-                    span,
-                });
+            found => {
+                self.errors.push(TypeCheckError::ExpectedFunction { found, span });
                 Type::Error
             }
         }
@@ -823,25 +931,18 @@ impl<'interner> TypeChecker<'interner> {
         rhs_type: &Type,
         span: Span,
     ) -> Result<Type, TypeCheckError> {
-        let make_error = move |msg| TypeCheckError::Unstructured { msg, span };
-
         if op.kind.is_comparator() {
-            return self
-                .comparator_operand_type_rules(lhs_type, rhs_type, op, span)
-                .map_err(make_error);
+            return self.comparator_operand_type_rules(lhs_type, rhs_type, op, span);
         }
 
         use Type::*;
-        match (lhs_type, rhs_type)  {
+        match (lhs_type, rhs_type) {
             // An error type on either side will always return an error
-            (Error, _) | (_,Error) => Ok(Error),
+            (Error, _) | (_, Error) => Ok(Error),
 
-            // Matches on PolymorphicInteger and TypeVariable must be first so that we follow any type
+            // Matches on TypeVariable must be first so that we follow any type
             // bindings.
-            (var @ PolymorphicInteger(_, int), other)
-            | (other, var @ PolymorphicInteger(_, int))
-            | (var @ TypeVariable(int), other)
-            | (other, var @ TypeVariable(int)) => {
+            (var @ TypeVariable(int, _), other) | (other, var @ TypeVariable(int, _)) => {
                 if let TypeBinding::Bound(binding) = &*int.borrow() {
                     return self.infix_operand_type_rules(binding, op, other, span);
                 }
@@ -854,9 +955,9 @@ impl<'interner> TypeChecker<'interner> {
                     // finishes resolving so we can still allow cases like `let x: u8 = 1 << 2;`.
                     self.push_delayed_type_check(Box::new(move || {
                         if other.is_field() {
-                            Err(make_error("Bitwise operations are invalid on Field types. Try casting the operands to a sized integer type first".into()))
+                            Err(TypeCheckError::InvalidBitwiseOperationOnField { span })
                         } else if other.is_bindable() {
-                            Err(make_error("The number of bits to use for this bitwise operation is ambiguous. Either the operand's type or return type should be specified".into()))
+                            Err(TypeCheckError::AmbiguousBitWidth { span })
                         } else {
                             Ok(())
                         }
@@ -864,47 +965,78 @@ impl<'interner> TypeChecker<'interner> {
                 }
 
                 let comptime = var.try_get_comptime();
-                if other.try_bind_to_polymorphic_int(int, &comptime, true, op.location.span).is_ok() || other == &Type::Error {
+                if other.try_bind_to_polymorphic_int(int, &comptime, true, op.location.span).is_ok()
+                    || other == &Type::Error
+                {
                     Ok(other.clone())
                 } else {
-                    Err(make_error(format!("Types in a binary operation should match, but found {lhs_type} and {rhs_type}")))
+                    Err(TypeCheckError::TypeMismatchWithSource {
+                        rhs: lhs_type.clone(),
+                        lhs: rhs_type.clone(),
+                        source: Source::Binary,
+                        span,
+                    })
                 }
             }
-            (Integer(comptime_x, sign_x, bit_width_x), Integer(comptime_y, sign_y, bit_width_y)) => {
+            (
+                Integer(comptime_x, sign_x, bit_width_x),
+                Integer(comptime_y, sign_y, bit_width_y),
+            ) => {
                 if sign_x != sign_y {
-                    return Err(make_error(format!("Integers must have the same signedness LHS is {sign_x:?}, RHS is {sign_y:?} ")))
+                    return Err(TypeCheckError::IntegerSignedness {
+                        sign_x: *sign_x,
+                        sign_y: *sign_y,
+                        span,
+                    });
                 }
                 if bit_width_x != bit_width_y {
-                    return Err(make_error(format!("Integers must have the same bit width LHS is {bit_width_x}, RHS is {bit_width_y} ")))
+                    return Err(TypeCheckError::IntegerBitWidth {
+                        bit_width_x: *bit_width_x,
+                        bit_width_y: *bit_width_y,
+                        span,
+                    });
                 }
                 let comptime = comptime_x.and(comptime_y, op.location.span);
                 Ok(Integer(comptime, *sign_x, *bit_width_x))
             }
             (Integer(..), FieldElement(..)) | (FieldElement(..), Integer(..)) => {
-                Err(make_error("Cannot use an integer and a Field in a binary operation, try converting the Field into an integer".to_string()))
+                Err(TypeCheckError::IntegerAndFieldBinaryOperation { span })
             }
-            (Integer(..), typ) | (typ,Integer(..)) => {
-                Err(make_error(format!("Integer cannot be used with type {typ}")))
+            (Integer(..), typ) | (typ, Integer(..)) => {
+                Err(TypeCheckError::IntegerTypeMismatch { typ: typ.clone(), span })
             }
             // These types are not supported in binary operations
-            (Array(..), _) | (_, Array(..)) => Err(make_error("Arrays cannot be used in an infix operation".to_string())),
-            (Struct(..), _) | (_, Struct(..)) => Err(make_error("Structs cannot be used in an infix operation".to_string())),
-            (Tuple(_), _) | (_, Tuple(_)) => Err(make_error("Tuples cannot be used in an infix operation".to_string())),
+            (Array(..), _) | (_, Array(..)) => {
+                Err(TypeCheckError::InvalidInfixOp { kind: "Arrays", span })
+            }
+            (Struct(..), _) | (_, Struct(..)) => {
+                Err(TypeCheckError::InvalidInfixOp { kind: "Structs", span })
+            }
+            (Tuple(_), _) | (_, Tuple(_)) => {
+                Err(TypeCheckError::InvalidInfixOp { kind: "Tuples", span })
+            }
 
-            (Unit, _) | (_,Unit) => Ok(Unit),
+            (Unit, _) | (_, Unit) => Ok(Unit),
 
             // The result of two Fields is always a witness
             (FieldElement(comptime_x), FieldElement(comptime_y)) => {
                 if op.is_bitwise() {
-                    return Err(make_error("Bitwise operations are invalid on Field types. Try casting the operands to a sized integer type first.".into()));
+                    return Err(TypeCheckError::InvalidBitwiseOperationOnField { span });
                 }
                 let comptime = comptime_x.and(comptime_y, op.location.span);
                 Ok(FieldElement(comptime))
             }
 
-            (Bool(comptime_x), Bool(comptime_y)) => Ok(Bool(comptime_x.and(comptime_y, op.location.span))),
+            (Bool(comptime_x), Bool(comptime_y)) => {
+                Ok(Bool(comptime_x.and(comptime_y, op.location.span)))
+            }
 
-            (lhs, rhs) => Err(make_error(format!("Unsupported types for binary operation: {lhs} and {rhs}"))),
+            (lhs, rhs) => Err(TypeCheckError::TypeMismatchWithSource {
+                rhs: lhs.clone(),
+                lhs: rhs.clone(),
+                source: Source::BinOp,
+                span,
+            }),
         }
     }
 
@@ -938,7 +1070,7 @@ impl<'interner> TypeChecker<'interner> {
             crate::UnaryOp::MutableReference => {
                 Type::MutableReference(Box::new(rhs_type.follow_bindings()))
             }
-            crate::UnaryOp::Dereference => {
+            crate::UnaryOp::Dereference { implicitly_added: _ } => {
                 let element_type = self.interner.next_type_variable();
                 unify(Type::MutableReference(Box::new(element_type.clone())));
                 element_type
diff --git a/crates/noirc_frontend/src/hir/type_check/mod.rs b/crates/noirc_frontend/src/hir/type_check/mod.rs
index b8bb6c788e9..26d0e36abf9 100644
--- a/crates/noirc_frontend/src/hir/type_check/mod.rs
+++ b/crates/noirc_frontend/src/hir/type_check/mod.rs
@@ -63,13 +63,17 @@ pub fn type_check_func(interner: &mut NodeInterner, func_id: FuncId) -> Vec<Type
     // Check declared return type and actual return type
     if !can_ignore_ret {
         let func_span = interner.expr_span(function_body_id); // XXX: We could be more specific and return the span of the last stmt, however stmts do not have spans yet
-        function_last_type.make_subtype_of(&declared_return_type, func_span, &mut errors, || {
-            TypeCheckError::TypeMismatch {
+        function_last_type.make_subtype_with_coercions(
+            &declared_return_type,
+            *function_body_id,
+            interner,
+            &mut errors,
+            || TypeCheckError::TypeMismatch {
                 expected_typ: declared_return_type.to_string(),
                 expr_typ: function_last_type.to_string(),
                 expr_span: func_span,
-            }
-        });
+            },
+        );
     }
 
     errors
@@ -130,10 +134,16 @@ impl<'interner> TypeChecker<'interner> {
         &mut self,
         actual: &Type,
         expected: &Type,
-        span: Span,
+        expression: ExprId,
         make_error: impl FnOnce() -> TypeCheckError,
     ) {
-        actual.make_subtype_of(expected, span, &mut self.errors, make_error);
+        actual.make_subtype_with_coercions(
+            expected,
+            expression,
+            self.interner,
+            &mut self.errors,
+            make_error,
+        );
     }
 }
 
@@ -229,6 +239,7 @@ mod test {
         let func_meta = FuncMeta {
             name,
             kind: FunctionKind::Normal,
+            module_id: ModuleId::dummy_id(),
             attributes: None,
             location,
             contract_function_type: None,
@@ -378,7 +389,8 @@ mod test {
 
         let func_meta = vecmap(program.functions, |nf| {
             let resolver = Resolver::new(&mut interner, &path_resolver, &def_maps, file);
-            let (hir_func, func_meta, resolver_errors) = resolver.resolve_function(nf, main_id);
+            let (hir_func, func_meta, resolver_errors) =
+                resolver.resolve_function(nf, main_id, ModuleId::dummy_id());
             assert_eq!(resolver_errors, vec![]);
             (hir_func, func_meta)
         });
diff --git a/crates/noirc_frontend/src/hir/type_check/stmt.rs b/crates/noirc_frontend/src/hir/type_check/stmt.rs
index 52b6fc7dd2e..3130a8616de 100644
--- a/crates/noirc_frontend/src/hir/type_check/stmt.rs
+++ b/crates/noirc_frontend/src/hir/type_check/stmt.rs
@@ -8,7 +8,7 @@ use crate::hir_def::types::Type;
 use crate::node_interner::{DefinitionId, ExprId, StmtId};
 use crate::CompTime;
 
-use super::errors::TypeCheckError;
+use super::errors::{Source, TypeCheckError};
 use super::TypeChecker;
 
 impl<'interner> TypeChecker<'interner> {
@@ -108,12 +108,13 @@ impl<'interner> TypeChecker<'interner> {
         });
 
         let span = self.interner.expr_span(&assign_stmt.expression);
-        self.make_subtype_of(&expr_type, &lvalue_type, span, || {
-            let msg = format!(
-                "Cannot assign an expression of type {expr_type} to a value of type {lvalue_type}"
-            );
-
-            TypeCheckError::Unstructured { msg, span }
+        self.make_subtype_of(&expr_type, &lvalue_type, assign_stmt.expression, || {
+            TypeCheckError::TypeMismatchWithSource {
+                rhs: expr_type.clone(),
+                lhs: lvalue_type.clone(),
+                span,
+                source: Source::Assignment,
+            }
         });
     }
 
@@ -128,15 +129,13 @@ impl<'interner> TypeChecker<'interner> {
                     let typ = self.interner.id_type(ident.id).instantiate(self.interner).0;
                     let typ = typ.follow_bindings();
 
-                    let definition = self.interner.definition(ident.id);
-                    if !definition.mutable && !matches!(typ, Type::MutableReference(_)) {
-                        self.errors.push(TypeCheckError::Unstructured {
-                            msg: format!(
-                                "Variable {} must be mutable to be assigned to",
-                                definition.name
-                            ),
-                            span: ident.location.span,
-                        });
+                    if let Some(definition) = self.interner.try_definition(ident.id) {
+                        if !definition.mutable && !matches!(typ, Type::MutableReference(_)) {
+                            self.errors.push(TypeCheckError::VariableMustBeMutable {
+                                name: definition.name.clone(),
+                                span: ident.location.span,
+                            });
+                        }
                     }
 
                     typ
@@ -193,7 +192,6 @@ impl<'interner> TypeChecker<'interner> {
 
                 let typ = match result {
                     Type::Array(_, elem_type) => *elem_type,
-                    Type::Slice(elem_type) => *elem_type,
                     Type::Error => Type::Error,
                     other => {
                         // TODO: Need a better span here
@@ -261,7 +259,7 @@ impl<'interner> TypeChecker<'interner> {
             // Now check if LHS is the same type as the RHS
             // Importantly, we do not coerce any types implicitly
             let expr_span = self.interner.expr_span(&rhs_expr);
-            self.make_subtype_of(&expr_type, &annotated_type, expr_span, || {
+            self.make_subtype_of(&expr_type, &annotated_type, rhs_expr, || {
                 TypeCheckError::TypeMismatch {
                     expected_typ: annotated_type.to_string(),
                     expr_typ: expr_type.to_string(),
diff --git a/crates/noirc_frontend/src/hir_def/expr.rs b/crates/noirc_frontend/src/hir_def/expr.rs
index b9ee6634cc7..63b7e421dc3 100644
--- a/crates/noirc_frontend/src/hir_def/expr.rs
+++ b/crates/noirc_frontend/src/hir_def/expr.rs
@@ -80,6 +80,7 @@ pub enum HirLiteral {
     Bool(bool),
     Integer(FieldElement),
     Str(String),
+    Unit,
 }
 
 #[derive(Debug, Clone)]
diff --git a/crates/noirc_frontend/src/hir_def/function.rs b/crates/noirc_frontend/src/hir_def/function.rs
index 304772f1d0e..a69e8bb08b5 100644
--- a/crates/noirc_frontend/src/hir_def/function.rs
+++ b/crates/noirc_frontend/src/hir_def/function.rs
@@ -4,6 +4,7 @@ use noirc_errors::{Location, Span};
 
 use super::expr::{HirBlockExpression, HirExpression, HirIdent};
 use super::stmt::HirPattern;
+use crate::hir::def_map::ModuleId;
 use crate::node_interner::{ExprId, NodeInterner};
 use crate::{token::Attribute, FunctionKind};
 use crate::{ContractFunctionType, Type};
@@ -116,6 +117,8 @@ pub struct FuncMeta {
 
     pub kind: FunctionKind,
 
+    pub module_id: ModuleId,
+
     /// A function's attributes are the `#[...]` items above the function
     /// definition, if any. Currently, this is limited to a maximum of only one
     /// Attribute per function.
diff --git a/crates/noirc_frontend/src/hir_def/types.rs b/crates/noirc_frontend/src/hir_def/types.rs
index 9441307bf28..6e1113345a8 100644
--- a/crates/noirc_frontend/src/hir_def/types.rs
+++ b/crates/noirc_frontend/src/hir_def/types.rs
@@ -5,13 +5,18 @@ use std::{
     rc::Rc,
 };
 
-use crate::{hir::type_check::TypeCheckError, node_interner::NodeInterner};
+use crate::{
+    hir::type_check::TypeCheckError,
+    node_interner::{ExprId, NodeInterner},
+};
 use iter_extended::vecmap;
 use noirc_abi::AbiType;
 use noirc_errors::Span;
 
 use crate::{node_interner::StructId, Ident, Signedness};
 
+use super::expr::{HirCallExpression, HirExpression, HirIdent};
+
 #[derive(Debug, PartialEq, Eq, Clone, Hash)]
 pub enum Type {
     /// A primitive Field type, and whether or not it is known at compile-time.
@@ -21,9 +26,6 @@ pub enum Type {
     /// is either a type variable of some kind or a Type::Constant.
     Array(Box<Type>, Box<Type>),
 
-    /// Slice(E) is a slice with elements of type E.
-    Slice(Box<Type>),
-
     /// A primitive integer type with the given sign, bit count, and whether it is known at compile-time.
     /// E.g. `u32` would be `Integer(CompTime::No(None), Unsigned, 32)`
     Integer(CompTime, Signedness, u32),
@@ -58,14 +60,7 @@ pub enum Type {
     /// is a process that replaces each NamedGeneric in a generic function with a TypeVariable.
     /// Doing this at each call site of a generic function is how they can be called with
     /// different argument types each time.
-    TypeVariable(TypeVariable),
-
-    /// A generic integer or field type. This is a more specific kind of TypeVariable
-    /// that can only be bound to Type::Field, Type::Integer, or other PolymorphicIntegers.
-    /// This is the type of undecorated integer literals like `46`. Typing them in this way
-    /// allows them to be polymorphic over the actual integer/field type used without requiring
-    /// type annotations on each integer literal.
-    PolymorphicInteger(CompTime, TypeVariable),
+    TypeVariable(TypeVariable, TypeVariableKind),
 
     /// NamedGenerics are the 'T' or 'U' in a user-defined generic function
     /// like `fn foo<T, U>(...) {}`. Unlike TypeVariables, they cannot be bound over.
@@ -88,6 +83,11 @@ pub enum Type {
     /// bind to an integer without special checks to bind it to a non-type.
     Constant(u64),
 
+    /// The type of a slice is an array of size NotConstant.
+    /// The size of an array literal is resolved to this if it ever uses operations
+    /// involving slices.
+    NotConstant,
+
     /// The result of some type error. Remembering type errors as their own type variant lets
     /// us avoid issuing repeat type errors for the same item. For example, a lambda with
     /// an invalid type would otherwise issue a new error each time it is called
@@ -278,6 +278,24 @@ pub enum BinaryTypeOperator {
     Modulo,
 }
 
+#[derive(Debug, PartialEq, Eq, Clone, Hash)]
+pub enum TypeVariableKind {
+    /// Can bind to any type
+    Normal,
+
+    /// A generic integer or field type. This is a more specific kind of TypeVariable
+    /// that can only be bound to Type::Field, Type::Integer, or other polymorphic integers.
+    /// This is the type of undecorated integer literals like `46`. Typing them in this way
+    /// allows them to be polymorphic over the actual integer/field type used without requiring
+    /// type annotations on each integer literal.
+    IntegerOrField(CompTime),
+
+    /// A potentially constant array size. This will only bind to itself, Type::NotConstant, or
+    /// Type::Constant(n) with a matching size. This defaults to Type::Constant(n) if still unbound
+    /// during monomorphization.
+    Constant(u64),
+}
+
 /// A TypeVariable is a mutable reference that is either
 /// bound to some type, or unbound with a given TypeVariableId.
 pub type TypeVariable = Shared<TypeBinding>;
@@ -294,6 +312,20 @@ impl TypeBinding {
     pub fn is_unbound(&self) -> bool {
         matches!(self, TypeBinding::Unbound(_))
     }
+
+    pub fn bind_to(&mut self, binding: Type, span: Span) -> Result<(), TypeCheckError> {
+        match self {
+            TypeBinding::Bound(_) => panic!("Tried to bind an already bound type variable!"),
+            TypeBinding::Unbound(id) => {
+                if binding.occurs(*id) {
+                    Err(TypeCheckError::TypeAnnotationsNeeded { span })
+                } else {
+                    *self = TypeBinding::Bound(binding);
+                    Ok(())
+                }
+            }
+        }
+    }
 }
 
 /// A unique ID used to differentiate different type variables
@@ -522,12 +554,21 @@ impl Type {
     }
 
     pub fn type_variable(id: TypeVariableId) -> Type {
-        Type::TypeVariable(Shared::new(TypeBinding::Unbound(id)))
+        Type::TypeVariable(Shared::new(TypeBinding::Unbound(id)), TypeVariableKind::Normal)
+    }
+
+    /// Returns a TypeVariable(_, TypeVariableKind::Constant(length)) to bind to
+    /// a constant integer for e.g. an array length.
+    pub fn constant_variable(length: u64, interner: &mut NodeInterner) -> Type {
+        let id = interner.next_type_variable_id();
+        let kind = TypeVariableKind::Constant(length);
+        Type::TypeVariable(Shared::new(TypeBinding::Unbound(id)), kind)
     }
 
     pub fn polymorphic_integer(interner: &mut NodeInterner) -> Type {
         let id = interner.next_type_variable_id();
-        Type::PolymorphicInteger(CompTime::new(interner), Shared::new(TypeBinding::Unbound(id)))
+        let kind = TypeVariableKind::IntegerOrField(CompTime::new(interner));
+        Type::TypeVariable(Shared::new(TypeBinding::Unbound(id)), kind)
     }
 
     /// A bit of an awkward name for this function - this function returns
@@ -536,12 +577,10 @@ impl Type {
     /// they shouldn't be bound over until monomorphization.
     pub fn is_bindable(&self) -> bool {
         match self {
-            Type::PolymorphicInteger(_, binding) | Type::TypeVariable(binding) => {
-                match &*binding.borrow() {
-                    TypeBinding::Bound(binding) => binding.is_bindable(),
-                    TypeBinding::Unbound(_) => true,
-                }
-            }
+            Type::TypeVariable(binding, _) => match &*binding.borrow() {
+                TypeBinding::Bound(binding) => binding.is_bindable(),
+                TypeBinding::Unbound(_) => true,
+            },
             _ => false,
         }
     }
@@ -572,18 +611,16 @@ impl Type {
             | Type::String(_)
             | Type::Unit
             | Type::Error
-            | Type::TypeVariable(_)
-            | Type::PolymorphicInteger(_, _)
+            | Type::TypeVariable(_, _)
             | Type::Constant(_)
             | Type::NamedGeneric(_, _)
+            | Type::NotConstant
             | Type::Forall(_, _) => false,
 
             Type::Array(length, elem) => {
                 elem.contains_numeric_typevar(target_id) || named_generic_id_matches_target(length)
             }
 
-            Type::Slice(elem) => elem.contains_numeric_typevar(target_id),
-
             Type::Tuple(fields) => {
                 fields.iter().any(|field| field.contains_numeric_typevar(target_id))
             }
@@ -609,7 +646,9 @@ impl Type {
             Type::FieldElement(comptime)
             | Type::Integer(comptime, _, _)
             | Type::Bool(comptime)
-            | Type::PolymorphicInteger(comptime, _) => Cow::Borrowed(comptime),
+            | Type::TypeVariable(_, TypeVariableKind::IntegerOrField(comptime)) => {
+                Cow::Borrowed(comptime)
+            }
             _ => Cow::Owned(CompTime::No(None)),
         }
     }
@@ -621,15 +660,21 @@ impl std::fmt::Display for Type {
             Type::FieldElement(comp_time) => {
                 write!(f, "{comp_time}Field")
             }
-            Type::Array(len, typ) => write!(f, "[{typ}; {len}]"),
-            Type::Slice(typ) => write!(f, "[{typ}]"),
+            Type::Array(len, typ) => {
+                if matches!(len.follow_bindings(), Type::NotConstant) {
+                    write!(f, "[{typ}]")
+                } else {
+                    write!(f, "[{typ}; {len}]")
+                }
+            }
             Type::Integer(comp_time, sign, num_bits) => match sign {
                 Signedness::Signed => write!(f, "{comp_time}i{num_bits}"),
                 Signedness::Unsigned => write!(f, "{comp_time}u{num_bits}"),
             },
-            Type::PolymorphicInteger(_, binding) => {
+            Type::TypeVariable(id, TypeVariableKind::Normal) => write!(f, "{}", id.borrow()),
+            Type::TypeVariable(binding, TypeVariableKind::IntegerOrField(_)) => {
                 if let TypeBinding::Unbound(_) = &*binding.borrow() {
-                    // Show a Field by default if this PolymorphicInteger is unbound, since that is
+                    // Show a Field by default if this TypeVariableKind::IntegerOrField is unbound, since that is
                     // what they bind to by default anyway. It is less confusing than displaying it
                     // as a generic.
                     write!(f, "Field")
@@ -637,6 +682,14 @@ impl std::fmt::Display for Type {
                     write!(f, "{}", binding.borrow())
                 }
             }
+            Type::TypeVariable(binding, TypeVariableKind::Constant(n)) => {
+                if let TypeBinding::Unbound(_) = &*binding.borrow() {
+                    // TypeVariableKind::Constant(n) binds to Type::Constant(n) by default, so just show that.
+                    write!(f, "{n}")
+                } else {
+                    write!(f, "{}", binding.borrow())
+                }
+            }
             Type::Struct(s, args) => {
                 let args = vecmap(args, |arg| arg.to_string());
                 if args.is_empty() {
@@ -653,7 +706,6 @@ impl std::fmt::Display for Type {
             Type::String(len) => write!(f, "str<{len}>"),
             Type::Unit => write!(f, "()"),
             Type::Error => write!(f, "error"),
-            Type::TypeVariable(id) => write!(f, "{}", id.borrow()),
             Type::NamedGeneric(binding, name) => match &*binding.borrow() {
                 TypeBinding::Bound(binding) => binding.fmt(f),
                 TypeBinding::Unbound(_) if name.is_empty() => write!(f, "_"),
@@ -671,6 +723,7 @@ impl std::fmt::Display for Type {
             Type::MutableReference(element) => {
                 write!(f, "&mut {element}")
             }
+            Type::NotConstant => write!(f, "_"),
         }
     }
 }
@@ -724,7 +777,7 @@ impl Type {
             Type::FieldElement(comptime) | Type::Integer(comptime, _, _) => {
                 comptime.set_span(new_span);
             }
-            Type::PolymorphicInteger(span, binding) => {
+            Type::TypeVariable(binding, TypeVariableKind::IntegerOrField(span)) => {
                 if let TypeBinding::Bound(binding) = &mut *binding.borrow_mut() {
                     return binding.set_comp_time_span(new_span);
                 }
@@ -739,7 +792,7 @@ impl Type {
             Type::FieldElement(comptime) | Type::Integer(comptime, _, _) => {
                 *comptime = new_comptime;
             }
-            Type::PolymorphicInteger(comptime, binding) => {
+            Type::TypeVariable(binding, TypeVariableKind::IntegerOrField(comptime)) => {
                 if let TypeBinding::Bound(binding) = &mut *binding.borrow_mut() {
                     return binding.set_comp_time(new_comptime);
                 }
@@ -749,6 +802,62 @@ impl Type {
         }
     }
 
+    /// Try to bind a MaybeConstant variable to self, succeeding if self is a Constant,
+    /// MaybeConstant, or type variable.
+    pub fn try_bind_to_maybe_constant(
+        &self,
+        var: &TypeVariable,
+        target_length: u64,
+    ) -> Result<(), SpanKind> {
+        let target_id = match &*var.borrow() {
+            TypeBinding::Bound(_) => unreachable!(),
+            TypeBinding::Unbound(id) => *id,
+        };
+
+        match self {
+            Type::Constant(length) if *length == target_length => {
+                *var.borrow_mut() = TypeBinding::Bound(self.clone());
+                Ok(())
+            }
+            Type::NotConstant => {
+                *var.borrow_mut() = TypeBinding::Bound(Type::NotConstant);
+                Ok(())
+            }
+            Type::TypeVariable(binding, kind) => {
+                let borrow = binding.borrow();
+                match &*borrow {
+                    TypeBinding::Bound(typ) => typ.try_bind_to_maybe_constant(var, target_length),
+                    // Avoid infinitely recursive bindings
+                    TypeBinding::Unbound(id) if *id == target_id => Ok(()),
+                    TypeBinding::Unbound(_) => match kind {
+                        TypeVariableKind::Normal => {
+                            drop(borrow);
+                            let clone = Type::TypeVariable(
+                                var.clone(),
+                                TypeVariableKind::Constant(target_length),
+                            );
+                            *binding.borrow_mut() = TypeBinding::Bound(clone);
+                            Ok(())
+                        }
+                        TypeVariableKind::Constant(length) if *length == target_length => {
+                            drop(borrow);
+                            let clone = Type::TypeVariable(
+                                var.clone(),
+                                TypeVariableKind::Constant(target_length),
+                            );
+                            *binding.borrow_mut() = TypeBinding::Bound(clone);
+                            Ok(())
+                        }
+                        TypeVariableKind::Constant(_) | TypeVariableKind::IntegerOrField(_) => {
+                            Err(SpanKind::None)
+                        }
+                    },
+                }
+            }
+            _ => Err(SpanKind::None),
+        }
+    }
+
     /// Try to bind a PolymorphicInt variable to self, succeeding if self is an integer, field,
     /// other PolymorphicInt type, or type variable. If use_subtype is true, the CompTime fields
     /// of each will be checked via sub-typing rather than unification.
@@ -783,7 +892,7 @@ impl Type {
             Type::FieldElement(int_comp_time, ..) | Type::Integer(int_comp_time, ..) => {
                 bind(int_comp_time)
             }
-            Type::PolymorphicInteger(int_comp_time, self_var) => {
+            Type::TypeVariable(self_var, TypeVariableKind::IntegerOrField(int_comp_time)) => {
                 let borrow = self_var.borrow();
                 match &*borrow {
                     TypeBinding::Bound(typ) => {
@@ -797,7 +906,7 @@ impl Type {
                     }
                 }
             }
-            Type::TypeVariable(binding) => {
+            Type::TypeVariable(binding, TypeVariableKind::Normal) => {
                 let borrow = binding.borrow();
                 match &*borrow {
                     TypeBinding::Bound(typ) => {
@@ -809,8 +918,10 @@ impl Type {
                         drop(borrow);
                         // PolymorphicInt is more specific than TypeVariable so we bind the type
                         // variable to PolymorphicInt instead.
-                        let mut clone =
-                            Type::PolymorphicInteger(var_comp_time.clone(), var.clone());
+                        let mut clone = Type::TypeVariable(
+                            var.clone(),
+                            TypeVariableKind::IntegerOrField(var_comp_time.clone()),
+                        );
                         clone.set_comp_time_span(span);
                         *binding.borrow_mut() = TypeBinding::Bound(clone);
                         Ok(())
@@ -848,9 +959,7 @@ impl Type {
 
     fn get_inner_type_variable(&self) -> Option<Shared<TypeBinding>> {
         match self {
-            Type::PolymorphicInteger(_, var)
-            | Type::TypeVariable(var)
-            | Type::NamedGeneric(var, _) => Some(var.clone()),
+            Type::TypeVariable(var, _) | Type::NamedGeneric(var, _) => Some(var.clone()),
             _ => None,
         }
     }
@@ -859,7 +968,7 @@ impl Type {
         match self {
             Type::FieldElement(comptime) => comptime.is_comp_time(),
             Type::Integer(comptime, ..) => comptime.is_comp_time(),
-            Type::PolymorphicInteger(comptime, binding) => {
+            Type::TypeVariable(binding, TypeVariableKind::IntegerOrField(comptime)) => {
                 if let TypeBinding::Bound(binding) = &*binding.borrow() {
                     return binding.is_comp_time();
                 }
@@ -896,12 +1005,10 @@ impl Type {
 
         match (expected.is_comp_time(), err_span) {
             (true, SpanKind::NotCompTime(span)) => {
-                let msg = "The value is non-comptime because of this expression, which uses another non-comptime value".into();
-                errors.push(TypeCheckError::Unstructured { msg, span });
+                errors.push(TypeCheckError::NotCompTime { span });
             }
             (false, SpanKind::CompTime(span)) => {
-                let msg = "The value is comptime because of this expression, which forces the value to be comptime".into();
-                errors.push(TypeCheckError::Unstructured { msg, span });
+                errors.push(TypeCheckError::CompTime { span });
             }
             _ => (),
         }
@@ -911,11 +1018,13 @@ impl Type {
     /// any unified bindings are on success.
     fn try_unify(&self, other: &Type, span: Span) -> Result<(), SpanKind> {
         use Type::*;
+        use TypeVariableKind as Kind;
+
         match (self, other) {
             (Error, _) | (_, Error) => Ok(()),
 
-            (PolymorphicInteger(comptime, binding), other)
-            | (other, PolymorphicInteger(comptime, binding)) => {
+            (TypeVariable(binding, Kind::IntegerOrField(comptime)), other)
+            | (other, TypeVariable(binding, Kind::IntegerOrField(comptime))) => {
                 // If it is already bound, unify against what it is bound to
                 if let TypeBinding::Bound(link) = &*binding.borrow() {
                     return link.try_unify(other, span);
@@ -925,7 +1034,8 @@ impl Type {
                 other.try_bind_to_polymorphic_int(binding, comptime, false, span)
             }
 
-            (TypeVariable(binding), other) | (other, TypeVariable(binding)) => {
+            (TypeVariable(binding, Kind::Normal), other)
+            | (other, TypeVariable(binding, Kind::Normal)) => {
                 if let TypeBinding::Bound(link) = &*binding.borrow() {
                     return link.try_unify(other, span);
                 }
@@ -933,13 +1043,20 @@ impl Type {
                 other.try_bind_to(binding)
             }
 
+            (TypeVariable(binding, Kind::Constant(length)), other)
+            | (other, TypeVariable(binding, Kind::Constant(length))) => {
+                if let TypeBinding::Bound(link) = &*binding.borrow() {
+                    return link.try_unify(other, span);
+                }
+
+                other.try_bind_to_maybe_constant(binding, *length)
+            }
+
             (Array(len_a, elem_a), Array(len_b, elem_b)) => {
                 len_a.try_unify(len_b, span)?;
                 elem_a.try_unify(elem_b, span)
             }
 
-            (Slice(elem_a), Slice(elem_b)) => elem_a.try_unify(elem_b, span),
-
             (Tuple(elements_a), Tuple(elements_b)) => {
                 if elements_a.len() != elements_b.len() {
                     Err(SpanKind::None)
@@ -1029,12 +1146,65 @@ impl Type {
         }
     }
 
-    fn is_subtype_of(&self, other: &Type, span: Span) -> Result<(), SpanKind> {
+    /// Similar to `make_subtype_of` but if the check fails this will attempt to coerce the
+    /// argument to the target type. When this happens, the given expression is wrapped in
+    /// a new expression to convert its type. E.g. `array` -> `array.as_slice()`
+    ///
+    /// Currently the only type coercion in Noir is `[T; N]` into `[T]` via `.as_slice()`.
+    pub fn make_subtype_with_coercions(
+        &self,
+        expected: &Type,
+        expression: ExprId,
+        interner: &mut NodeInterner,
+        errors: &mut Vec<TypeCheckError>,
+        make_error: impl FnOnce() -> TypeCheckError,
+    ) {
+        let span = interner.expr_span(&expression);
+        if let Err(err_span) = self.is_subtype_of(expected, span) {
+            if !self.try_array_to_slice_coercion(expected, expression, span, interner) {
+                Self::issue_errors(expected, err_span, errors, make_error);
+            }
+        }
+    }
+
+    /// Try to apply the array to slice coercion to this given type pair and expression.
+    /// If self can be converted to target this way, do so and return true to indicate success.
+    fn try_array_to_slice_coercion(
+        &self,
+        target: &Type,
+        expression: ExprId,
+        span: Span,
+        interner: &mut NodeInterner,
+    ) -> bool {
+        let this = self.follow_bindings();
+        let target = target.follow_bindings();
+
+        if let (Type::Array(size1, element1), Type::Array(size2, element2)) = (&this, &target) {
+            let size1 = size1.follow_bindings();
+            let size2 = size2.follow_bindings();
+
+            // If we have an array and our target is a slice
+            if matches!(size1, Type::Constant(_)) && matches!(size2, Type::NotConstant) {
+                // Still have to ensure the element types match.
+                // Don't need to issue an error here if not, it will be done in make_subtype_of_with_coercions
+                if element1.is_subtype_of(element2, span).is_ok() {
+                    convert_array_expression_to_slice(expression, this, target, interner);
+                    return true;
+                }
+            }
+        }
+        false
+    }
+
+    /// Checks if self is a subtype of `other`. Returns Ok(()) if it is and Err(_) if not.
+    /// Note that this function may permanently bind type variables regardless of whether it
+    /// returned Ok or Err.
+    pub fn is_subtype_of(&self, other: &Type, span: Span) -> Result<(), SpanKind> {
         use Type::*;
         match (self, other) {
             (Error, _) | (_, Error) => Ok(()),
 
-            (PolymorphicInteger(comptime, binding), other) => {
+            (TypeVariable(binding, TypeVariableKind::IntegerOrField(comptime)), other) => {
                 if let TypeBinding::Bound(link) = &*binding.borrow() {
                     return link.is_subtype_of(other, span);
                 }
@@ -1043,7 +1213,7 @@ impl Type {
                 other.try_bind_to_polymorphic_int(binding, comptime, true, span)
             }
             // These needs to be a separate case to keep the argument order of is_subtype_of
-            (other, PolymorphicInteger(comptime, binding)) => {
+            (other, TypeVariable(binding, TypeVariableKind::IntegerOrField(comptime))) => {
                 if let TypeBinding::Bound(link) = &*binding.borrow() {
                     return other.is_subtype_of(link, span);
                 }
@@ -1053,14 +1223,14 @@ impl Type {
                 other.try_bind_to_polymorphic_int(binding, comptime, false, span)
             }
 
-            (TypeVariable(binding), other) => {
+            (TypeVariable(binding, TypeVariableKind::Normal), other) => {
                 if let TypeBinding::Bound(link) = &*binding.borrow() {
                     return link.is_subtype_of(other, span);
                 }
 
                 other.try_bind_to(binding)
             }
-            (other, TypeVariable(binding)) => {
+            (other, TypeVariable(binding, TypeVariableKind::Normal)) => {
                 if let TypeBinding::Bound(link) = &*binding.borrow() {
                     return other.is_subtype_of(link, span);
                 }
@@ -1068,15 +1238,26 @@ impl Type {
                 other.try_bind_to(binding)
             }
 
+            (TypeVariable(binding, TypeVariableKind::Constant(length)), other) => {
+                if let TypeBinding::Bound(link) = &*binding.borrow() {
+                    return link.is_subtype_of(other, span);
+                }
+
+                other.try_bind_to_maybe_constant(binding, *length)
+            }
+            (other, TypeVariable(binding, TypeVariableKind::Constant(length))) => {
+                if let TypeBinding::Bound(link) = &*binding.borrow() {
+                    return other.is_subtype_of(link, span);
+                }
+
+                other.try_bind_to_maybe_constant(binding, *length)
+            }
+
             (Array(len_a, elem_a), Array(len_b, elem_b)) => {
                 len_a.is_subtype_of(len_b, span)?;
                 elem_a.is_subtype_of(elem_b, span)
             }
 
-            (Slice(elem_a), Slice(elem_b)) => elem_a.is_subtype_of(elem_b, span),
-
-            (Array(_, elem_a), Slice(elem_b)) => elem_a.is_subtype_of(elem_b, span),
-
             (Tuple(elements_a), Tuple(elements_b)) => {
                 if elements_a.len() != elements_b.len() {
                     Err(SpanKind::None)
@@ -1169,13 +1350,14 @@ impl Type {
     /// If this type is a Type::Constant (used in array lengths), or is bound
     /// to a Type::Constant, return the constant as a u64.
     pub fn evaluate_to_u64(&self) -> Option<u64> {
+        if let Some(binding) = self.get_inner_type_variable() {
+            if let TypeBinding::Bound(binding) = &*binding.borrow() {
+                return binding.evaluate_to_u64();
+            }
+        }
+
         match self {
-            Type::PolymorphicInteger(_, binding)
-            | Type::NamedGeneric(binding, _)
-            | Type::TypeVariable(binding) => match &*binding.borrow() {
-                TypeBinding::Bound(binding) => binding.evaluate_to_u64(),
-                TypeBinding::Unbound(_) => None,
-            },
+            Type::TypeVariable(_, TypeVariableKind::Constant(size)) => Some(*size),
             Type::Array(len, _elem) => len.evaluate_to_u64(),
             Type::Constant(x) => Some(*x),
             _ => None,
@@ -1201,10 +1383,12 @@ impl Type {
 
                 AbiType::Integer { sign, width: *bit_width }
             }
-            Type::PolymorphicInteger(_, binding) => match &*binding.borrow() {
-                TypeBinding::Bound(typ) => typ.as_abi_type(),
-                TypeBinding::Unbound(_) => Type::default_int_type(None).as_abi_type(),
-            },
+            Type::TypeVariable(binding, TypeVariableKind::IntegerOrField(_)) => {
+                match &*binding.borrow() {
+                    TypeBinding::Bound(typ) => typ.as_abi_type(),
+                    TypeBinding::Unbound(_) => Type::default_int_type(None).as_abi_type(),
+                }
+            }
             Type::Bool(_) => AbiType::Boolean,
             Type::String(size) => {
                 let size = size
@@ -1222,12 +1406,12 @@ impl Type {
                 AbiType::Struct { fields }
             }
             Type::Tuple(_) => todo!("as_abi_type not yet implemented for tuple types"),
-            Type::TypeVariable(_) => unreachable!(),
+            Type::TypeVariable(_, _) => unreachable!(),
             Type::NamedGeneric(..) => unreachable!(),
             Type::Forall(..) => unreachable!(),
             Type::Function(_, _) => unreachable!(),
-            Type::Slice(_) => unreachable!("slices cannot be used in the abi"),
             Type::MutableReference(_) => unreachable!("&mut cannot be used in the abi"),
+            Type::NotConstant => unreachable!(),
         }
     }
 
@@ -1309,18 +1493,13 @@ impl Type {
                 let element = Box::new(element.substitute(type_bindings));
                 Type::Array(size, element)
             }
-            Type::Slice(element) => {
-                let element = Box::new(element.substitute(type_bindings));
-                Type::Slice(element)
-            }
             Type::String(size) => {
                 let size = Box::new(size.substitute(type_bindings));
                 Type::String(size)
             }
-            Type::PolymorphicInteger(_, binding)
-            | Type::NamedGeneric(binding, _)
-            | Type::TypeVariable(binding) => substitute_binding(binding),
-
+            Type::NamedGeneric(binding, _) | Type::TypeVariable(binding, _) => {
+                substitute_binding(binding)
+            }
             // Do not substitute fields, it can lead to infinite recursion
             // and we should not match fields when type checking anyway.
             Type::Struct(fields, args) => {
@@ -1354,6 +1533,7 @@ impl Type {
             | Type::Bool(_)
             | Type::Constant(_)
             | Type::Error
+            | Type::NotConstant
             | Type::Unit => self.clone(),
         }
     }
@@ -1362,16 +1542,15 @@ impl Type {
     fn occurs(&self, target_id: TypeVariableId) -> bool {
         match self {
             Type::Array(len, elem) => len.occurs(target_id) || elem.occurs(target_id),
-            Type::Slice(element) => element.occurs(target_id),
             Type::String(len) => len.occurs(target_id),
             Type::Struct(_, generic_args) => generic_args.iter().any(|arg| arg.occurs(target_id)),
             Type::Tuple(fields) => fields.iter().any(|field| field.occurs(target_id)),
-            Type::PolymorphicInteger(_, binding)
-            | Type::NamedGeneric(binding, _)
-            | Type::TypeVariable(binding) => match &*binding.borrow() {
-                TypeBinding::Bound(binding) => binding.occurs(target_id),
-                TypeBinding::Unbound(id) => *id == target_id,
-            },
+            Type::NamedGeneric(binding, _) | Type::TypeVariable(binding, _) => {
+                match &*binding.borrow() {
+                    TypeBinding::Bound(binding) => binding.occurs(target_id),
+                    TypeBinding::Unbound(id) => *id == target_id,
+                }
+            }
             Type::Forall(typevars, typ) => {
                 !typevars.iter().any(|(id, _)| *id == target_id) && typ.occurs(target_id)
             }
@@ -1385,6 +1564,7 @@ impl Type {
             | Type::Bool(_)
             | Type::Constant(_)
             | Type::Error
+            | Type::NotConstant
             | Type::Unit => false,
         }
     }
@@ -1401,7 +1581,6 @@ impl Type {
             Array(size, elem) => {
                 Array(Box::new(size.follow_bindings()), Box::new(elem.follow_bindings()))
             }
-            Slice(elem) => Slice(Box::new(elem.follow_bindings())),
             String(size) => String(Box::new(size.follow_bindings())),
             Struct(def, args) => {
                 let args = vecmap(args, |arg| arg.follow_bindings());
@@ -1409,7 +1588,7 @@ impl Type {
             }
             Tuple(args) => Tuple(vecmap(args, |arg| arg.follow_bindings())),
 
-            TypeVariable(var) | PolymorphicInteger(_, var) | NamedGeneric(var, _) => {
+            TypeVariable(var, _) | NamedGeneric(var, _) => {
                 if let TypeBinding::Bound(typ) = &*var.borrow() {
                     return typ.follow_bindings();
                 }
@@ -1426,13 +1605,44 @@ impl Type {
             // Expect that this function should only be called on instantiated types
             Forall(..) => unreachable!(),
 
-            FieldElement(_) | Integer(_, _, _) | Bool(_) | Constant(_) | Unit | Error => {
-                self.clone()
-            }
+            FieldElement(_)
+            | Integer(_, _, _)
+            | Bool(_)
+            | Constant(_)
+            | Unit
+            | Error
+            | NotConstant => self.clone(),
         }
     }
 }
 
+/// Wraps a given `expression` in `expression.as_slice()`
+fn convert_array_expression_to_slice(
+    expression: ExprId,
+    array_type: Type,
+    target_type: Type,
+    interner: &mut NodeInterner,
+) {
+    let as_slice_method = interner
+        .lookup_primitive_method(&array_type, "as_slice")
+        .expect("Expected 'as_slice' method to be present in Noir's stdlib");
+
+    let as_slice_id = interner.function_definition_id(as_slice_method);
+    let location = interner.expr_location(&expression);
+    let as_slice = HirExpression::Ident(HirIdent { location, id: as_slice_id });
+    let func = interner.push_expr(as_slice);
+
+    let arguments = vec![expression];
+    let call = HirExpression::Call(HirCallExpression { func, arguments, location });
+    let call = interner.push_expr(call);
+
+    interner.push_expr_location(call, location.span, location.file);
+    interner.push_expr_location(func, location.span, location.file);
+
+    interner.push_expr_type(&call, target_type.clone());
+    interner.push_expr_type(&func, Type::Function(vec![array_type], Box::new(target_type)));
+}
+
 impl BinaryTypeOperator {
     /// Return the actual rust numeric function associated with this operator
     pub fn function(self) -> fn(u64, u64) -> u64 {
@@ -1445,3 +1655,14 @@ impl BinaryTypeOperator {
         }
     }
 }
+
+impl TypeVariableKind {
+    /// Returns the default type this type variable should be bound to if it is still unbound
+    /// during monomorphization.
+    pub(crate) fn default_type(&self) -> Type {
+        match self {
+            TypeVariableKind::IntegerOrField(_) | TypeVariableKind::Normal => Type::field(None),
+            TypeVariableKind::Constant(length) => Type::Constant(*length),
+        }
+    }
+}
diff --git a/crates/noirc_frontend/src/lexer/errors.rs b/crates/noirc_frontend/src/lexer/errors.rs
index 189bfdb4bb2..0b6440dec44 100644
--- a/crates/noirc_frontend/src/lexer/errors.rs
+++ b/crates/noirc_frontend/src/lexer/errors.rs
@@ -8,7 +8,7 @@ use thiserror::Error;
 #[derive(Error, Clone, Debug, PartialEq, Eq)]
 pub enum LexerErrorKind {
     #[error("An unexpected character {:?} was found.", found)]
-    UnexpectedCharacter { span: Span, expected: String, found: char },
+    UnexpectedCharacter { span: Span, expected: String, found: Option<char> },
     #[error("NotADoubleChar : {:?} is not a double char token", found)]
     NotADoubleChar { span: Span, found: Token },
     #[error("InvalidIntegerLiteral : {:?} is not a integer", found)]
@@ -19,6 +19,8 @@ pub enum LexerErrorKind {
     TooManyBits { span: Span, max: u32, got: u32 },
     #[error("LogicalAnd used instead of bitwise and")]
     LogicalAnd { span: Span },
+    #[error("Unterminated block comment")]
+    UnterminatedBlockComment { span: Span },
 }
 
 impl LexerErrorKind {
@@ -30,6 +32,7 @@ impl LexerErrorKind {
             LexerErrorKind::MalformedFuncAttribute { span, .. } => *span,
             LexerErrorKind::TooManyBits { span, .. } => *span,
             LexerErrorKind::LogicalAnd { span } => *span,
+            LexerErrorKind::UnterminatedBlockComment { span } => *span,
         }
     }
 
@@ -39,11 +42,15 @@ impl LexerErrorKind {
                 span,
                 expected,
                 found,
-            } => (
-                "an unexpected character was found".to_string(),
-                format!(" expected {expected} , but got {found}"),
-                *span,
-            ),
+            } => {
+                let found: String = found.map(Into::into).unwrap_or_else(|| "<eof>".into());
+
+                (
+                    "an unexpected character was found".to_string(),
+                    format!(" expected {expected} , but got {}", found),
+                    *span,
+                )
+            },
             LexerErrorKind::NotADoubleChar { span, found } => (
                 format!("tried to parse {found} as double char"),
                 format!(
@@ -73,6 +80,7 @@ impl LexerErrorKind {
                 "Try `&` instead, or use `if` only if you require short-circuiting".to_string(),
                 *span,
             ),
+            LexerErrorKind::UnterminatedBlockComment { span } => ("unterminated block comment".to_string(), "Unterminated block comment".to_string(), *span),
         }
     }
 }
diff --git a/crates/noirc_frontend/src/lexer/lexer.rs b/crates/noirc_frontend/src/lexer/lexer.rs
index 2c8583ef2c7..e376d85ddf0 100644
--- a/crates/noirc_frontend/src/lexer/lexer.rs
+++ b/crates/noirc_frontend/src/lexer/lexer.rs
@@ -176,25 +176,12 @@ impl<'a> Lexer<'a> {
                 if self.peek_char_is('/') {
                     self.next_char();
                     return self.parse_comment();
+                } else if self.peek_char_is('*') {
+                    self.next_char();
+                    return self.parse_block_comment();
                 }
                 Ok(spanned_prev_token)
             }
-            Token::Underscore => {
-                let next_char = self.peek_char();
-                let peeked_char = match next_char {
-                    Some(peek_char) => peek_char,
-                    None => return Ok(spanned_prev_token),
-                };
-
-                if peeked_char.is_ascii_alphabetic() {
-                    // Okay to unwrap here because we already peeked to
-                    // see that we have a character
-                    let current_char = self.next_char().unwrap();
-                    return self.eat_word(current_char);
-                }
-
-                Ok(spanned_prev_token)
-            }
             _ => Err(LexerErrorKind::NotADoubleChar {
                 span: Span::single_char(self.position),
                 found: prev_token,
@@ -241,7 +228,7 @@ impl<'a> Lexer<'a> {
             '0'..='9' => self.eat_digit(initial_char),
             _ => Err(LexerErrorKind::UnexpectedCharacter {
                 span: Span::single_char(self.position),
-                found: initial_char,
+                found: initial_char.into(),
                 expected: "an alpha numeric character".to_owned(),
             }),
         }
@@ -251,22 +238,19 @@ impl<'a> Lexer<'a> {
         if !self.peek_char_is('[') {
             return Err(LexerErrorKind::UnexpectedCharacter {
                 span: Span::single_char(self.position),
-                found: self.next_char().unwrap(),
+                found: self.next_char(),
                 expected: "[".to_owned(),
             });
         }
         self.next_char();
 
-        let (word, start, end) = self.eat_while(None, |ch| {
-            (ch.is_ascii_alphabetic() || ch.is_numeric() || ch == '_' || ch == '(' || ch == ')')
-                && (ch != ']')
-        });
+        let (word, start, end) = self.eat_while(None, |ch| ch != ']');
 
         if !self.peek_char_is(']') {
             return Err(LexerErrorKind::UnexpectedCharacter {
                 span: Span::single_char(self.position),
                 expected: "]".to_owned(),
-                found: self.next_char().unwrap(),
+                found: self.next_char(),
             });
         }
         self.next_char();
@@ -335,6 +319,38 @@ impl<'a> Lexer<'a> {
         self.next_token()
     }
 
+    fn parse_block_comment(&mut self) -> SpannedTokenResult {
+        let span = Span::new(self.position..self.position + 1);
+        let mut depth = 1usize;
+
+        while let Some(ch) = self.next_char() {
+            match ch {
+                '/' if self.peek_char_is('*') => {
+                    self.next_char();
+                    depth += 1;
+                }
+                '*' if self.peek_char_is('/') => {
+                    self.next_char();
+                    depth -= 1;
+
+                    // This block comment is closed, so for a construction like "/* */ */"
+                    // there will be a successfully parsed block comment "/* */"
+                    // and " */" will be processed separately.
+                    if depth == 0 {
+                        break;
+                    }
+                }
+                _ => {}
+            }
+        }
+
+        if depth == 0 {
+            self.next_token()
+        } else {
+            Err(LexerErrorKind::UnterminatedBlockComment { span })
+        }
+    }
+
     /// Skips white space. They are not significant in the source language
     fn eat_whitespace(&mut self) {
         self.eat_while(None, |ch| ch.is_whitespace());
@@ -399,6 +415,33 @@ fn test_single_double_char() {
     }
 }
 
+#[test]
+fn invalid_attribute() {
+    let input = "#";
+    let mut lexer = Lexer::new(input);
+
+    let token = lexer.next().unwrap();
+    assert!(token.is_err());
+}
+
+#[test]
+fn deprecated_attribute() {
+    let input = r#"#[deprecated]"#;
+    let mut lexer = Lexer::new(input);
+
+    let token = lexer.next().unwrap().unwrap();
+    assert_eq!(token.token(), &Token::Attribute(Attribute::Deprecated(None)));
+}
+
+#[test]
+fn deprecated_attribute_with_note() {
+    let input = r#"#[deprecated("hello")]"#;
+    let mut lexer = Lexer::new(input);
+
+    let token = lexer.next().unwrap().unwrap();
+    assert_eq!(token.token(), &Token::Attribute(Attribute::Deprecated("hello".to_string().into())));
+}
+
 #[test]
 fn test_custom_gate_syntax() {
     let input = "#[foreign(sha256)]#[foreign(blake2s)]#[builtin(sum)]";
@@ -460,6 +503,16 @@ fn test_arithmetic_sugar() {
     }
 }
 
+#[test]
+fn unterminated_block_comment() {
+    let input = "/*/";
+
+    let mut lexer = Lexer::new(input);
+    let token = lexer.next().unwrap();
+
+    assert!(token.is_err());
+}
+
 #[test]
 fn test_comment() {
     let input = "// hello
@@ -480,6 +533,49 @@ fn test_comment() {
     }
 }
 
+#[test]
+fn test_block_comment() {
+    let input = "
+    /* comment */
+    let x = 5
+    /* comment */
+    ";
+
+    let expected = vec![
+        Token::Keyword(Keyword::Let),
+        Token::Ident("x".to_string()),
+        Token::Assign,
+        Token::Int(FieldElement::from(5_i128)),
+    ];
+
+    let mut lexer = Lexer::new(input);
+    for token in expected.into_iter() {
+        let first_lexer_output = lexer.next_token().unwrap();
+        assert_eq!(first_lexer_output, token);
+    }
+}
+
+#[test]
+fn test_nested_block_comments() {
+    let input = "
+    /*   /* */  /** */  /*! */  */
+    let x = 5
+    /*   /* */  /** */  /*! */  */
+    ";
+
+    let expected = vec![
+        Token::Keyword(Keyword::Let),
+        Token::Ident("x".to_string()),
+        Token::Assign,
+        Token::Int(FieldElement::from(5_i128)),
+    ];
+
+    let mut lexer = Lexer::new(input);
+    for token in expected.into_iter() {
+        let first_lexer_output = lexer.next_token().unwrap();
+        assert_eq!(first_lexer_output, token);
+    }
+}
 #[test]
 fn test_eat_string_literal() {
     let input = "let _word = \"hello\"";
diff --git a/crates/noirc_frontend/src/lexer/token.rs b/crates/noirc_frontend/src/lexer/token.rs
index 90bc957600c..b39d1640c57 100644
--- a/crates/noirc_frontend/src/lexer/token.rs
+++ b/crates/noirc_frontend/src/lexer/token.rs
@@ -80,8 +80,6 @@ pub enum Token {
     Semicolon,
     /// !
     Bang,
-    /// _
-    Underscore,
     /// =
     Assign,
     #[allow(clippy::upper_case_acronyms)]
@@ -182,7 +180,6 @@ impl fmt::Display for Token {
             Token::Semicolon => write!(f, ";"),
             Token::Assign => write!(f, "="),
             Token::Bang => write!(f, "!"),
-            Token::Underscore => write!(f, "_"),
             Token::EOF => write!(f, "end of input"),
             Token::Invalid(c) => write!(f, "{c}"),
         }
@@ -325,6 +322,7 @@ pub enum Attribute {
     Foreign(String),
     Builtin(String),
     Oracle(String),
+    Deprecated(Option<String>),
     Test,
 }
 
@@ -335,6 +333,8 @@ impl fmt::Display for Attribute {
             Attribute::Builtin(ref k) => write!(f, "#[builtin({k})]"),
             Attribute::Oracle(ref k) => write!(f, "#[oracle({k})]"),
             Attribute::Test => write!(f, "#[test]"),
+            Attribute::Deprecated(None) => write!(f, "#[deprecated]"),
+            Attribute::Deprecated(Some(ref note)) => write!(f, r#"#[deprecated("{note}")]"#),
         }
     }
 }
@@ -348,29 +348,52 @@ impl Attribute {
             .filter(|string_segment| !string_segment.is_empty())
             .collect();
 
-        if word_segments.len() != 2 {
-            if word_segments.len() == 1 && word_segments[0] == "test" {
-                return Ok(Token::Attribute(Attribute::Test));
-            } else {
-                return Err(LexerErrorKind::MalformedFuncAttribute {
-                    span,
-                    found: word.to_owned(),
-                });
-            }
-        }
-
-        let attribute_type = word_segments[0];
-        let attribute_name = word_segments[1];
+        let validate = |slice: &str| {
+            let is_valid = slice
+                .chars()
+                .all(|ch| {
+                    ch.is_ascii_alphabetic()
+                        || ch.is_numeric()
+                        || ch == '_'
+                        || ch == '('
+                        || ch == ')'
+                })
+                .then_some(());
+
+            is_valid.ok_or(LexerErrorKind::MalformedFuncAttribute { span, found: word.to_owned() })
+        };
 
-        let tok = match attribute_type {
-            "foreign" => Token::Attribute(Attribute::Foreign(attribute_name.to_string())),
-            "builtin" => Token::Attribute(Attribute::Builtin(attribute_name.to_string())),
-            "oracle" => Token::Attribute(Attribute::Oracle(attribute_name.to_string())),
+        let attribute = match &word_segments[..] {
+            ["foreign", name] => {
+                validate(name)?;
+                Attribute::Foreign(name.to_string())
+            }
+            ["builtin", name] => {
+                validate(name)?;
+                Attribute::Builtin(name.to_string())
+            }
+            ["oracle", name] => {
+                validate(name)?;
+                Attribute::Oracle(name.to_string())
+            }
+            ["deprecated"] => Attribute::Deprecated(None),
+            ["deprecated", name] => {
+                if !name.starts_with('"') && !name.ends_with('"') {
+                    return Err(LexerErrorKind::MalformedFuncAttribute {
+                        span,
+                        found: word.to_owned(),
+                    });
+                }
+
+                Attribute::Deprecated(name.trim_matches('"').to_string().into())
+            }
+            ["test"] => Attribute::Test,
             _ => {
                 return Err(LexerErrorKind::MalformedFuncAttribute { span, found: word.to_owned() })
             }
         };
-        Ok(tok)
+
+        Ok(Token::Attribute(attribute))
     }
 
     pub fn builtin(self) -> Option<String> {
@@ -402,7 +425,8 @@ impl AsRef<str> for Attribute {
             Attribute::Foreign(string) => string,
             Attribute::Builtin(string) => string,
             Attribute::Oracle(string) => string,
-            Attribute::Test => "",
+            Attribute::Deprecated(Some(string)) => string,
+            Attribute::Test | Attribute::Deprecated(None) => "",
         }
     }
 }
@@ -528,7 +552,6 @@ impl Keyword {
 
             "true" => return Some(Token::Bool(true)),
             "false" => return Some(Token::Bool(false)),
-            "_" => return Some(Token::Underscore),
             _ => return None,
         };
 
diff --git a/crates/noirc_frontend/src/main.rs b/crates/noirc_frontend/src/main.rs
deleted file mode 100644
index 8f27b878ffb..00000000000
--- a/crates/noirc_frontend/src/main.rs
+++ /dev/null
@@ -1,73 +0,0 @@
-//! The noir compiler is separated into the following passes which are listed
-//! in order in square brackets. The inputs and outputs of each pass are also given:
-//!
-//! Source file -[Lexing]-> Tokens -[Parsing]-> Ast -[Name Resolution]-> Hir -[Type Checking]-> Hir -[Monomorphization]-> Monomorphized Ast
-//!
-//! After the monomorphized ast is created, it is passed to the noirc_evaluator crate to convert it to SSA form,
-//! perform optimizations, convert to ACIR and eventually prove/verify the program.
-use std::path::PathBuf;
-
-use fm::FileManager;
-use hir::{def_map::CrateDefMap, Context};
-use noirc_frontend::graph::{CrateGraph, CrateType};
-use noirc_frontend::hir::{self, def_map::ModuleDefId};
-
-// XXX: This is another sandbox test
-fn main() {
-    // File Manager
-    let mut fm = FileManager::default();
-    //
-    // Add root file to file manager
-    let dir_path: PathBuf = PathBuf::from("example_project/lib.nr");
-    let root_file_id = fm.add_file(&dir_path).unwrap();
-
-    // CrateGraph
-    let mut crate_graph = CrateGraph::default();
-    // Initiate crate with root file
-    let crate_id = crate_graph.add_crate_root(CrateType::Library, root_file_id);
-
-    // initiate context with file manager and crate graph
-    let mut context = Context::new(fm, crate_graph);
-
-    // Now create the CrateDefMap
-    // This is preamble for analysis
-    // With a CrateDefMap, we are sure that the imports are correct, and the modules declared are located
-    // The modules are resolved and type checked!
-    let mut errors = vec![];
-    CrateDefMap::collect_defs(crate_id, &mut context, &mut errors);
-    assert_eq!(errors, vec![]);
-    let def_map = context.def_map(&crate_id).unwrap();
-
-    // Get root module
-    let root = def_map.root();
-    let module = def_map.modules().get(root.0).unwrap();
-    for def_id in module.value_definitions() {
-        let func_id = match def_id {
-            ModuleDefId::FunctionId(func_id) => func_id,
-            _ => unreachable!(),
-        };
-
-        // Get the HirFunction for that Id
-        let hir = context.def_interner.function(&func_id);
-        println!("func hir is {:?}", hir);
-    }
-    //
-
-    // println!("----------------------------CRATE DATA------------------------------");
-    // println!("Local module id is: {:?}", def_map.root());
-    // println!("crate id is: {:?}", def_map.krate());
-    // println!("-----------------------------MODULES DATA----------------------------");
-    // for (i, (module_index, module_data)) in def_map.modules().iter().enumerate() {
-    //     println!("-----------------------------Start Data for module at position {}----------------------------", i);
-    //     println!("current module id is: {:?}", module_index);
-    //     println!("parent module id is: {:?}", module_data.parent);
-    //     println!("-----------------------------Children for module at position {}----------------------------", i);
-    //     for (child_name, child_id) in &module_data.children {
-    //         println!("{:?} is a child module with id {:?}", child_name, child_id);
-    //     }
-    //     println!("scope is : {:?}", module_data.scope);
-    //     println!("origin is : {:?}", module_data.origin);
-    //     println!("-----------------------------End Data for module at position {}----------------------------", i);
-    // }
-    // println!("-----------------------------END MODULES DATA----------------------------");
-}
diff --git a/crates/noirc_frontend/src/monomorphization/ast.rs b/crates/noirc_frontend/src/monomorphization/ast.rs
index 7cac2ed8e4f..488d05c6509 100644
--- a/crates/noirc_frontend/src/monomorphization/ast.rs
+++ b/crates/noirc_frontend/src/monomorphization/ast.rs
@@ -119,7 +119,7 @@ pub struct Cast {
 #[derive(Debug, Clone)]
 pub struct ArrayLiteral {
     pub contents: Vec<Expression>,
-    pub element_type: Type,
+    pub typ: Type,
 }
 
 #[derive(Debug, Clone)]
diff --git a/crates/noirc_frontend/src/monomorphization/mod.rs b/crates/noirc_frontend/src/monomorphization/mod.rs
index d8dfb1550c0..bb0228091da 100644
--- a/crates/noirc_frontend/src/monomorphization/mod.rs
+++ b/crates/noirc_frontend/src/monomorphization/mod.rs
@@ -22,7 +22,7 @@ use crate::{
     },
     node_interner::{self, DefinitionKind, NodeInterner, StmtId},
     token::Attribute,
-    CompTime, FunctionKind, Type, TypeBinding, TypeBindings,
+    ContractFunctionType, FunctionKind, TypeBinding, TypeBindings, TypeVariableKind,
 };
 
 use self::ast::{Definition, FuncId, Function, LocalId, Program};
@@ -191,7 +191,8 @@ impl<'interner> Monomorphizer<'interner> {
         let return_type = Self::convert_type(meta.return_type());
         let parameters = self.parameters(meta.parameters);
         let body = self.expr(*self.interner.function(&f).as_expr());
-        let unconstrained = meta.is_unconstrained;
+        let unconstrained = meta.is_unconstrained
+            || matches!(meta.contract_function_type, Some(ContractFunctionType::Open));
 
         let function = ast::Function { id, name, parameters, body, return_type, unconstrained };
         self.push_function(id, function);
@@ -268,9 +269,10 @@ impl<'interner> Monomorphizer<'interner> {
             HirExpression::Literal(HirLiteral::Array(array)) => match array {
                 HirArrayLiteral::Standard(array) => self.standard_array(expr, array),
                 HirArrayLiteral::Repeated { repeated_element, length } => {
-                    self.repeated_array(repeated_element, length)
+                    self.repeated_array(expr, repeated_element, length)
                 }
             },
+            HirExpression::Literal(HirLiteral::Unit) => ast::Expression::Block(vec![]),
             HirExpression::Block(block) => self.block(block.0),
 
             HirExpression::Prefix(prefix) => ast::Expression::Unary(ast::Unary {
@@ -352,64 +354,26 @@ impl<'interner> Monomorphizer<'interner> {
         array: node_interner::ExprId,
         array_elements: Vec<node_interner::ExprId>,
     ) -> ast::Expression {
-        let element_type =
-            Self::convert_type(&unwrap_array_element_type(&self.interner.id_type(array)));
+        let typ = Self::convert_type(&self.interner.id_type(array));
         let contents = vecmap(array_elements, |id| self.expr(id));
-        Self::aos_to_soa(contents, element_type)
+        ast::Expression::Literal(ast::Literal::Array(ast::ArrayLiteral { contents, typ }))
     }
 
     fn repeated_array(
         &mut self,
+        array: node_interner::ExprId,
         repeated_element: node_interner::ExprId,
         length: HirType,
     ) -> ast::Expression {
-        let element_type = Self::convert_type(&self.interner.id_type(repeated_element));
+        let typ = Self::convert_type(&self.interner.id_type(array));
+
         let contents = self.expr(repeated_element);
         let length = length
             .evaluate_to_u64()
             .expect("Length of array is unknown when evaluating numeric generic");
 
         let contents = vec![contents; length as usize];
-        Self::aos_to_soa(contents, element_type)
-    }
-
-    /// Convert an array in (potentially) array of structs form into struct of arrays form.
-    /// This will do nothing if the given array element type is a primitive type like Field.
-    ///
-    ///
-    /// TODO Remove side effects from clones
-    fn aos_to_soa(
-        array_contents: Vec<ast::Expression>,
-        element_type: ast::Type,
-    ) -> ast::Expression {
-        match element_type {
-            ast::Type::Field
-            | ast::Type::Integer(_, _)
-            | ast::Type::Bool
-            | ast::Type::Unit
-            | ast::Type::Function(_, _)
-            | ast::Type::MutableReference(_) => {
-                ast::Expression::Literal(ast::Literal::Array(ast::ArrayLiteral {
-                    contents: array_contents,
-                    element_type,
-                }))
-            }
-
-            ast::Type::Tuple(elements) => ast::Expression::Tuple(vecmap(
-                elements.into_iter().enumerate(),
-                |(i, element_type)| {
-                    let contents = vecmap(&array_contents, |element| {
-                        ast::Expression::ExtractTupleField(Box::new(element.clone()), i)
-                    });
-
-                    Self::aos_to_soa(contents, element_type)
-                },
-            )),
-
-            ast::Type::Array(_, _) | ast::Type::String(_) | ast::Type::Slice(_) => {
-                unreachable!("Nested arrays, arrays of strings, and Vecs are not supported")
-            }
-        }
+        ast::Expression::Literal(ast::Literal::Array(ast::ArrayLiteral { contents, typ }))
     }
 
     fn index(&mut self, id: node_interner::ExprId, index: HirIndexExpression) -> ast::Expression {
@@ -418,42 +382,7 @@ impl<'interner> Monomorphizer<'interner> {
         let collection = Box::new(self.expr(index.collection));
         let index = Box::new(self.expr(index.index));
         let location = self.interner.expr_location(&id);
-        Self::aos_to_soa_index(collection, index, element_type, location)
-    }
-
-    /// Unpack an array index into an array of structs into a struct of arrays index if needed.
-    /// E.g. transforms my_pair_array[i] into (my_pair1_array[i], my_pair2_array[i])
-    fn aos_to_soa_index(
-        collection: Box<ast::Expression>,
-        index: Box<ast::Expression>,
-        element_type: ast::Type,
-        location: Location,
-    ) -> ast::Expression {
-        match element_type {
-            ast::Type::Field
-            | ast::Type::Integer(_, _)
-            | ast::Type::Bool
-            | ast::Type::Unit
-            | ast::Type::Function(_, _)
-            | ast::Type::MutableReference(_) => {
-                ast::Expression::Index(ast::Index { collection, index, element_type, location })
-            }
-
-            ast::Type::Tuple(elements) => {
-                let elements = elements.into_iter().enumerate();
-                ast::Expression::Tuple(vecmap(elements, |(i, element_type)| {
-                    // collection should itself be a tuple of arrays
-                    let collection =
-                        Box::new(ast::Expression::ExtractTupleField(collection.clone(), i));
-
-                    Self::aos_to_soa_index(collection, index.clone(), element_type, location)
-                }))
-            }
-
-            ast::Type::Array(_, _) | ast::Type::String(_) | ast::Type::Slice(_) => {
-                unreachable!("Nested arrays and arrays of strings or Vecs are not supported")
-            }
-        }
+        ast::Expression::Index(ast::Index { collection, index, element_type, location })
     }
 
     fn statement(&mut self, id: StmtId) -> ast::Expression {
@@ -661,35 +590,49 @@ impl<'interner> Monomorphizer<'interner> {
             HirType::Unit => ast::Type::Unit,
 
             HirType::Array(length, element) => {
-                let length = length.evaluate_to_u64().unwrap_or(0);
-                let element = Self::convert_type(element.as_ref());
-                Self::aos_to_soa_type(length, element)
-            }
+                let element = Box::new(Self::convert_type(element.as_ref()));
 
-            HirType::Slice(element) => {
-                let element = Self::convert_type(element.as_ref());
-                ast::Type::Slice(Box::new(element))
+                if let Some(length) = length.evaluate_to_u64() {
+                    ast::Type::Array(length, element)
+                } else {
+                    ast::Type::Slice(element)
+                }
             }
 
-            HirType::PolymorphicInteger(_, binding)
-            | HirType::TypeVariable(binding)
-            | HirType::NamedGeneric(binding, _) => {
+            HirType::NamedGeneric(binding, _) => {
                 if let TypeBinding::Bound(binding) = &*binding.borrow() {
                     return Self::convert_type(binding);
                 }
 
-                // Default any remaining unbound type variables to Field.
+                // Default any remaining unbound type variables.
                 // This should only happen if the variable in question is unused
                 // and within a larger generic type.
                 // NOTE: Make sure to review this if there is ever type-directed dispatch,
                 // like automatic solving of traits. It should be fine since it is strictly
                 // after type checking, but care should be taken that it doesn't change which
                 // impls are chosen.
-                *binding.borrow_mut() =
-                    TypeBinding::Bound(HirType::FieldElement(CompTime::No(None)));
+                *binding.borrow_mut() = TypeBinding::Bound(HirType::field(None));
                 ast::Type::Field
             }
 
+            HirType::TypeVariable(binding, kind) => {
+                if let TypeBinding::Bound(binding) = &*binding.borrow() {
+                    return Self::convert_type(binding);
+                }
+
+                // Default any remaining unbound type variables.
+                // This should only happen if the variable in question is unused
+                // and within a larger generic type.
+                // NOTE: Make sure to review this if there is ever type-directed dispatch,
+                // like automatic solving of traits. It should be fine since it is strictly
+                // after type checking, but care should be taken that it doesn't change which
+                // impls are chosen.
+                let default = kind.default_type();
+                let monomorphized_default = Self::convert_type(&default);
+                *binding.borrow_mut() = TypeBinding::Bound(default);
+                monomorphized_default
+            }
+
             HirType::Struct(def, args) => {
                 let fields = def.borrow().get_fields(args);
                 let fields = vecmap(fields, |(_, field)| Self::convert_type(&field));
@@ -712,46 +655,70 @@ impl<'interner> Monomorphizer<'interner> {
                 ast::Type::MutableReference(Box::new(element))
             }
 
-            HirType::Forall(_, _) | HirType::Constant(_) | HirType::Error => {
+            HirType::Forall(_, _)
+            | HirType::Constant(_)
+            | HirType::NotConstant
+            | HirType::Error => {
                 unreachable!("Unexpected type {} found", typ)
             }
         }
     }
 
-    /// Converts arrays of structs (AOS) into structs of arrays (SOA).
-    /// This is required since our SSA pass does not support arrays of structs.
-    fn aos_to_soa_type(length: u64, element: ast::Type) -> ast::Type {
-        match element {
-            ast::Type::Field
-            | ast::Type::Integer(_, _)
-            | ast::Type::Bool
-            | ast::Type::Unit
-            | ast::Type::Function(_, _)
-            | ast::Type::MutableReference(_) => ast::Type::Array(length, Box::new(element)),
-
-            ast::Type::Tuple(elements) => {
-                ast::Type::Tuple(vecmap(elements, |typ| Self::aos_to_soa_type(length, typ)))
-            }
-
-            ast::Type::Array(_, _) | ast::Type::String(_) | ast::Type::Slice(_) => {
-                unreachable!("Nested arrays and arrays of strings are not supported")
-            }
-        }
-    }
-
     fn function_call(
         &mut self,
         call: HirCallExpression,
         id: node_interner::ExprId,
     ) -> ast::Expression {
         let func = Box::new(self.expr(call.func));
-        let arguments = vecmap(&call.arguments, |id| self.expr(*id));
+        let mut arguments = vecmap(&call.arguments, |id| self.expr(*id));
+        let hir_arguments = vecmap(&call.arguments, |id| self.interner.expression(id));
         let return_type = self.interner.id_type(id);
         let return_type = Self::convert_type(&return_type);
         let location = call.location;
 
-        self.try_evaluate_call(&func, &call.arguments, &return_type)
-            .unwrap_or(ast::Expression::Call(ast::Call { func, arguments, return_type, location }))
+        if let ast::Expression::Ident(ident) = func.as_ref() {
+            if let Definition::Oracle(name) = &ident.definition {
+                if name.as_str() == "println" {
+                    // Oracle calls are required to be wrapped in an unconstrained function
+                    // Thus, the only argument to the `println` oracle is expected to always be an ident
+                    self.append_abi_arg(&hir_arguments[0], &mut arguments);
+                }
+            }
+        }
+
+        self.try_evaluate_call(&func, &return_type).unwrap_or(ast::Expression::Call(ast::Call {
+            func,
+            arguments,
+            return_type,
+            location,
+        }))
+    }
+
+    /// Adds a function argument that contains type metadata that is required to tell
+    /// a caller (such as nargo) how to convert values passed to an foreign call
+    /// back to a human-readable string.
+    /// The values passed to an foreign call will be a simple list of field elements,
+    /// thus requiring extra metadata to correctly decode this list of elements.
+    ///
+    /// The Noir compiler has an `AbiType` that handles encoding/decoding a list
+    /// of field elements to/from JSON. The type metadata attached in this method
+    /// is the serialized `AbiType` for the argument passed to the function.
+    /// The caller that is running a Noir program should then deserialize the `AbiType`,
+    /// and accurately decode the list of field elements passed to the foreign call.  
+    fn append_abi_arg(&self, hir_argument: &HirExpression, arguments: &mut Vec<ast::Expression>) {
+        match hir_argument {
+            HirExpression::Ident(ident) => {
+                let typ = self.interner.id_type(ident.id);
+                let typ = typ.follow_bindings();
+
+                let abi_type = typ.as_abi_type();
+                let abi_as_string =
+                    serde_json::to_string(&abi_type).expect("ICE: expected Abi type to serialize");
+
+                arguments.push(ast::Expression::Literal(ast::Literal::Str(abi_as_string)));
+            }
+            _ => unreachable!("logging expr {:?} is not supported", arguments[0]),
+        }
     }
 
     /// Try to evaluate certain builtin functions (currently only 'array_len' and field modulus methods)
@@ -763,25 +730,12 @@ impl<'interner> Monomorphizer<'interner> {
     fn try_evaluate_call(
         &mut self,
         func: &ast::Expression,
-        arguments: &[node_interner::ExprId],
         result_type: &ast::Type,
     ) -> Option<ast::Expression> {
         if let ast::Expression::Ident(ident) = func {
             if let Definition::Builtin(opcode) = &ident.definition {
                 // TODO(#1736): Move this builtin to the SSA pass
                 return match opcode.as_str() {
-                    "array_len" => {
-                        let typ = self.interner.id_type(arguments[0]);
-                        if let Type::Array(_, _) = typ {
-                            let len = typ.evaluate_to_u64().unwrap();
-                            Some(ast::Expression::Literal(ast::Literal::Integer(
-                                (len as u128).into(),
-                                ast::Type::Field,
-                            )))
-                        } else {
-                            None
-                        }
-                    }
                     "modulus_num_bits" => Some(ast::Expression::Literal(ast::Literal::Integer(
                         (FieldElement::max_num_bits() as u128).into(),
                         ast::Type::Field,
@@ -811,17 +765,17 @@ impl<'interner> Monomorphizer<'interner> {
     }
 
     fn modulus_array_literal(&self, bytes: Vec<u8>, arr_elem_bits: u32) -> ast::Expression {
+        use ast::*;
+        let int_type = Type::Integer(crate::Signedness::Unsigned, arr_elem_bits);
+
         let bytes_as_expr = vecmap(bytes, |byte| {
-            ast::Expression::Literal(ast::Literal::Integer(
-                (byte as u128).into(),
-                ast::Type::Integer(crate::Signedness::Unsigned, arr_elem_bits),
-            ))
+            Expression::Literal(Literal::Integer((byte as u128).into(), int_type.clone()))
         });
-        let arr_literal = ast::ArrayLiteral {
-            contents: bytes_as_expr,
-            element_type: ast::Type::Integer(crate::Signedness::Unsigned, arr_elem_bits),
-        };
-        ast::Expression::Literal(ast::Literal::Array(arr_literal))
+
+        let typ = Type::Array(bytes_as_expr.len() as u64, Box::new(int_type));
+
+        let arr_literal = ArrayLiteral { typ, contents: bytes_as_expr };
+        Expression::Literal(Literal::Array(arr_literal))
     }
 
     fn queue_function(
@@ -863,7 +817,9 @@ impl<'interner> Monomorphizer<'interner> {
 
         match index_lvalue {
             Some((index, element_type, location)) => {
-                Self::aos_to_soa_assign(expression, Box::new(lvalue), index, element_type, location)
+                let lvalue =
+                    ast::LValue::Index { array: Box::new(lvalue), index, element_type, location };
+                ast::Expression::Assign(ast::Assign { lvalue, expression })
             }
             None => ast::Expression::Assign(ast::Assign { expression, lvalue }),
         }
@@ -911,38 +867,6 @@ impl<'interner> Monomorphizer<'interner> {
         }
     }
 
-    fn aos_to_soa_assign(
-        expression: Box<ast::Expression>,
-        lvalue: Box<ast::LValue>,
-        index: Box<ast::Expression>,
-        typ: ast::Type,
-        location: Location,
-    ) -> ast::Expression {
-        match typ {
-            ast::Type::Tuple(fields) => {
-                let fields = fields.into_iter().enumerate();
-                ast::Expression::Block(vecmap(fields, |(i, field)| {
-                    let expression = ast::Expression::ExtractTupleField(expression.clone(), i);
-                    let lvalue =
-                        ast::LValue::MemberAccess { object: lvalue.clone(), field_index: i };
-                    Self::aos_to_soa_assign(
-                        Box::new(expression),
-                        Box::new(lvalue),
-                        index.clone(),
-                        field,
-                        location,
-                    )
-                }))
-            }
-
-            // No changes if the element_type is not a tuple
-            element_type => {
-                let lvalue = ast::LValue::Index { array: lvalue, index, element_type, location };
-                ast::Expression::Assign(ast::Assign { lvalue, expression })
-            }
-        }
-    }
-
     fn lambda(&mut self, lambda: HirLambda) -> ast::Expression {
         let ret_type = Self::convert_type(&lambda.return_type);
         let lambda_name = "lambda";
@@ -992,7 +916,7 @@ impl<'interner> Monomorphizer<'interner> {
                 let element = self.zeroed_value_of_type(element_type.as_ref());
                 ast::Expression::Literal(ast::Literal::Array(ast::ArrayLiteral {
                     contents: vec![element; *length as usize],
-                    element_type: element_type.as_ref().clone(),
+                    typ: ast::Type::Array(*length, element_type.clone()),
                 }))
             }
             ast::Type::String(length) => {
@@ -1007,7 +931,7 @@ impl<'interner> Monomorphizer<'interner> {
             ast::Type::Slice(element_type) => {
                 ast::Expression::Literal(ast::Literal::Array(ast::ArrayLiteral {
                     contents: vec![],
-                    element_type: *element_type.clone(),
+                    typ: ast::Type::Slice(element_type.clone()),
                 }))
             }
             ast::Type::MutableReference(element) => {
@@ -1059,7 +983,7 @@ impl<'interner> Monomorphizer<'interner> {
 fn unwrap_tuple_type(typ: &HirType) -> Vec<HirType> {
     match typ {
         HirType::Tuple(fields) => fields.clone(),
-        HirType::TypeVariable(binding) => match &*binding.borrow() {
+        HirType::TypeVariable(binding, TypeVariableKind::Normal) => match &*binding.borrow() {
             TypeBinding::Bound(binding) => unwrap_tuple_type(binding),
             TypeBinding::Unbound(_) => unreachable!(),
         },
@@ -1070,7 +994,7 @@ fn unwrap_tuple_type(typ: &HirType) -> Vec<HirType> {
 fn unwrap_struct_type(typ: &HirType) -> Vec<(String, HirType)> {
     match typ {
         HirType::Struct(def, args) => def.borrow().get_fields(args),
-        HirType::TypeVariable(binding) => match &*binding.borrow() {
+        HirType::TypeVariable(binding, TypeVariableKind::Normal) => match &*binding.borrow() {
             TypeBinding::Bound(binding) => unwrap_struct_type(binding),
             TypeBinding::Unbound(_) => unreachable!(),
         },
@@ -1078,20 +1002,6 @@ fn unwrap_struct_type(typ: &HirType) -> Vec<(String, HirType)> {
     }
 }
 
-fn unwrap_array_element_type(typ: &HirType) -> HirType {
-    match typ {
-        HirType::Array(_, elem) => *elem.clone(),
-        HirType::Slice(elem) => *elem.clone(),
-        HirType::TypeVariable(binding) => match &*binding.borrow() {
-            TypeBinding::Bound(binding) => unwrap_array_element_type(binding),
-            TypeBinding::Unbound(_) => unreachable!(),
-        },
-        other => {
-            unreachable!("unwrap_array_element_type: expected an array or slice, found {:?}", other)
-        }
-    }
-}
-
 fn perform_instantiation_bindings(bindings: &TypeBindings) {
     for (var, binding) in bindings.values() {
         *var.borrow_mut() = TypeBinding::Bound(binding.clone());
diff --git a/crates/noirc_frontend/src/node_interner.rs b/crates/noirc_frontend/src/node_interner.rs
index f37daf45136..f01c5f22a50 100644
--- a/crates/noirc_frontend/src/node_interner.rs
+++ b/crates/noirc_frontend/src/node_interner.rs
@@ -17,7 +17,7 @@ use crate::hir_def::{
     function::{FuncMeta, HirFunction},
     stmt::HirStatement,
 };
-use crate::{Shared, TypeBinding, TypeBindings, TypeVariable, TypeVariableId};
+use crate::{Shared, TypeBinding, TypeBindings, TypeVariable, TypeVariableId, TypeVariableKind};
 
 /// The node interner is the central storage location of all nodes in Noir's Hir (the
 /// various node types can be found in hir_def). The interner is also used to collect
@@ -70,10 +70,6 @@ pub struct NodeInterner {
 
     /// Methods on primitive types defined in the stdlib.
     primitive_methods: HashMap<(TypeMethodKey, String), FuncId>,
-
-    /// TODO(#1850): This is technical debt that should be removed once we fully move over
-    /// to the new SSA pass which does have slices enabled
-    pub enable_slices: bool,
 }
 
 #[derive(Debug, Clone, Copy, Eq, PartialEq, Hash)]
@@ -253,7 +249,6 @@ impl Default for NodeInterner {
             globals: HashMap::new(),
             struct_methods: HashMap::new(),
             primitive_methods: HashMap::new(),
-            enable_slices: false,
         };
 
         // An empty block expression is used often, we add this into the `node` on startup
@@ -478,10 +473,20 @@ impl NodeInterner {
         }
     }
 
+    /// Retrieves the definition where the given id was defined.
+    /// This will panic if given DefinitionId::dummy_id. Use try_definition for
+    /// any call with a possibly undefined variable.
     pub fn definition(&self, id: DefinitionId) -> &DefinitionInfo {
         &self.definitions[id.0]
     }
 
+    /// Tries to retrieve the given id's definition.
+    /// This function should be used during name resolution or type checking when we cannot be sure
+    /// all variables have corresponding definitions (in case of an error in the user's code).
+    pub fn try_definition(&self, id: DefinitionId) -> Option<&DefinitionInfo> {
+        self.definitions.get(id.0)
+    }
+
     /// Returns the name of the definition
     ///
     /// This is needed as the Environment needs to map variable names to witness indices
@@ -603,7 +608,6 @@ enum TypeMethodKey {
     /// accept only fields or integers, it is just that their names may not clash.
     FieldOrInt,
     Array,
-    Slice,
     Bool,
     String,
     Unit,
@@ -617,9 +621,8 @@ fn get_type_method_key(typ: &Type) -> Option<TypeMethodKey> {
     match &typ {
         Type::FieldElement(_) => Some(FieldOrInt),
         Type::Array(_, _) => Some(Array),
-        Type::Slice(_) => Some(Slice),
         Type::Integer(_, _, _) => Some(FieldOrInt),
-        Type::PolymorphicInteger(_, _) => Some(FieldOrInt),
+        Type::TypeVariable(_, TypeVariableKind::IntegerOrField(_)) => Some(FieldOrInt),
         Type::Bool(_) => Some(Bool),
         Type::String(_) => Some(String),
         Type::Unit => Some(Unit),
@@ -628,11 +631,12 @@ fn get_type_method_key(typ: &Type) -> Option<TypeMethodKey> {
         Type::MutableReference(element) => get_type_method_key(element),
 
         // We do not support adding methods to these types
-        Type::TypeVariable(_)
+        Type::TypeVariable(_, _)
         | Type::NamedGeneric(_, _)
         | Type::Forall(_, _)
         | Type::Constant(_)
         | Type::Error
+        | Type::NotConstant
         | Type::Struct(_, _) => None,
     }
 }
diff --git a/crates/noirc_frontend/src/parser/errors.rs b/crates/noirc_frontend/src/parser/errors.rs
index 0f0d8e15809..9b072d83b09 100644
--- a/crates/noirc_frontend/src/parser/errors.rs
+++ b/crates/noirc_frontend/src/parser/errors.rs
@@ -13,6 +13,8 @@ use super::labels::ParsingRuleLabel;
 pub enum ParserErrorReason {
     #[error("Unexpected '{0}', expected a field name")]
     ExpectedFieldName(Token),
+    #[error("expected a pattern but found a type - {0}")]
+    ExpectedPatternButFoundType(Token),
     #[error("Expected a ; separating these two statements")]
     MissingSeparatingSemi,
     #[error("constrain keyword is deprecated")]
@@ -70,6 +72,14 @@ impl ParserError {
         error.reason = Some(reason);
         error
     }
+
+    pub fn found(&self) -> &Token {
+        &self.found
+    }
+
+    pub fn span(&self) -> Span {
+        self.span
+    }
 }
 
 impl std::fmt::Display for ParserError {
@@ -107,6 +117,9 @@ impl From<ParserError> for Diagnostic {
                         "The 'constrain' keyword has been deprecated. Please use the 'assert' function instead.".into(),
                         error.span,
                     ),
+                    reason @ ParserErrorReason::ExpectedPatternButFoundType(ty) => {
+                        Diagnostic::simple_error(reason.to_string(), format!("{ty} is a type and cannot be used as a variable name"), error.span)
+                    }
                     other => {
 
                         Diagnostic::simple_error(format!("{other}"), String::new(), error.span)
diff --git a/crates/noirc_frontend/src/parser/parser.rs b/crates/noirc_frontend/src/parser/parser.rs
index 3f9fe31f414..c6d84416975 100644
--- a/crates/noirc_frontend/src/parser/parser.rs
+++ b/crates/noirc_frontend/src/parser/parser.rs
@@ -35,9 +35,9 @@ use crate::parser::{force, ignore_then_commit, statement_recovery};
 use crate::token::{Attribute, Keyword, Token, TokenKind};
 use crate::{
     BinaryOp, BinaryOpKind, BlockExpression, CompTime, ConstrainStatement, FunctionDefinition,
-    Ident, IfExpression, InfixExpression, LValue, Lambda, NoirFunction, NoirStruct, NoirTrait,
-    Path, PathKind, Pattern, Recoverable, TraitConstraint, TraitImpl, TraitImplItem, TraitItem,
-    TypeImpl, UnaryOp, UnresolvedTypeExpression, UseTree, UseTreeKind,
+    Ident, IfExpression, InfixExpression, LValue, Lambda, Literal, NoirFunction, NoirStruct,
+    NoirTrait, Path, PathKind, Pattern, Recoverable, TraitConstraint, TraitImpl, TraitImplItem,
+    TraitItem, TypeImpl, UnaryOp, UnresolvedTypeExpression, UseTree, UseTreeKind,
 };
 
 use chumsky::prelude::*;
@@ -683,7 +683,16 @@ where
 
 fn pattern() -> impl NoirParser<Pattern> {
     recursive(|pattern| {
-        let ident_pattern = ident().map(Pattern::Identifier);
+        let ident_pattern = ident().map(Pattern::Identifier).map_err(|mut error| {
+            if matches!(error.found(), Token::IntType(..)) {
+                error = ParserError::with_reason(
+                    ParserErrorReason::ExpectedPatternButFoundType(error.found().clone()),
+                    error.span(),
+                );
+            }
+
+            error
+        });
 
         let mut_pattern = keyword(Keyword::Mut)
             .ignore_then(pattern.clone())
@@ -788,6 +797,7 @@ fn parse_type_inner(
         string_type(),
         named_type(recursive_type_parser.clone()),
         array_type(recursive_type_parser.clone()),
+        recursive_type_parser.clone().delimited_by(just(Token::LeftParen), just(Token::RightParen)),
         tuple_type(recursive_type_parser.clone()),
         function_type(recursive_type_parser.clone()),
         mutable_reference_type(recursive_type_parser),
@@ -893,7 +903,13 @@ where
     T: NoirParser<UnresolvedType>,
 {
     let fields = type_parser.separated_by(just(Token::Comma)).allow_trailing();
-    parenthesized(fields).map(UnresolvedType::Tuple)
+    parenthesized(fields).map(|fields| {
+        if fields.is_empty() {
+            UnresolvedType::Unit
+        } else {
+            UnresolvedType::Tuple(fields)
+        }
+    })
 }
 
 fn function_type<T>(type_parser: T) -> impl NoirParser<UnresolvedType>
@@ -1251,7 +1267,7 @@ where
 {
     just(Token::Star)
         .ignore_then(term_parser)
-        .map(|rhs| ExpressionKind::prefix(UnaryOp::Dereference, rhs))
+        .map(|rhs| ExpressionKind::prefix(UnaryOp::Dereference { implicitly_added: false }, rhs))
 }
 
 /// Atoms are parameterized on whether constructor expressions are allowed or not.
@@ -1303,8 +1319,14 @@ fn tuple<P>(expr_parser: P) -> impl NoirParser<Expression>
 where
     P: ExprParser,
 {
-    parenthesized(expression_list(expr_parser))
-        .map_with_span(|elements, span| Expression::new(ExpressionKind::Tuple(elements), span))
+    parenthesized(expression_list(expr_parser)).map_with_span(|elements, span| {
+        let kind = if elements.is_empty() {
+            ExpressionKind::Literal(Literal::Unit)
+        } else {
+            ExpressionKind::Tuple(elements)
+        };
+        Expression::new(kind, span)
+    })
 }
 
 fn field_name() -> impl NoirParser<Ident> {
@@ -1662,7 +1684,7 @@ mod test {
         // Let statements are not type checked here, so the parser will accept as
         // long as it is a type. Other statements such as Public are type checked
         // Because for now, they can only have one type
-        parse_all(declaration(expression()), vec!["let x = y", "let x : u8 = y"]);
+        parse_all(declaration(expression()), vec!["let _ = 42", "let x = y", "let x : u8 = y"]);
     }
 
     #[test]
diff --git a/crates/wasm/Cargo.toml b/crates/wasm/Cargo.toml
index 5c139d96164..2b834318168 100644
--- a/crates/wasm/Cargo.toml
+++ b/crates/wasm/Cargo.toml
@@ -13,6 +13,7 @@ crate-type = ["cdylib"]
 [dependencies]
 
 acvm.workspace = true
+fm.workspace = true
 noirc_driver.workspace = true
 noirc_frontend.workspace = true
 wasm-bindgen.workspace = true
@@ -27,4 +28,4 @@ gloo-utils = { version = "0.1", features = ["serde"] }
 getrandom = { version = "*", features = ["js"] }
 
 [build-dependencies]
-build-data = "0.1.3"
\ No newline at end of file
+build-data = "0.1.3"
diff --git a/crates/wasm/package.json b/crates/wasm/package.json
index 67fda7abd90..4aa881ddea6 100644
--- a/crates/wasm/package.json
+++ b/crates/wasm/package.json
@@ -3,7 +3,7 @@
   "collaborators": [
     "The Noir Team <team@noir-lang.org>"
   ],
-  "version": "0.8.0",
+  "version": "0.9.0",
   "files": [
     "nodejs",
     "web",
@@ -14,7 +14,7 @@
   "module": "./web/noir_wasm.js",
   "sideEffects": false,
   "peerDependencies": {
-    "@noir-lang/noir-source-resolver": "1.1.2"
+    "@noir-lang/noir-source-resolver": "1.1.3"
   },
   "repository": {
     "type": "git",
diff --git a/crates/wasm/src/compile.rs b/crates/wasm/src/compile.rs
index 1218bbe5d0d..c940f0ce246 100644
--- a/crates/wasm/src/compile.rs
+++ b/crates/wasm/src/compile.rs
@@ -1,4 +1,5 @@
 use acvm::acir::circuit::Circuit;
+use fm::FileManager;
 use gloo_utils::format::JsValueSerdeExt;
 use log::debug;
 use noirc_driver::{
@@ -6,11 +7,11 @@ use noirc_driver::{
     propagate_dep, CompileOptions, CompiledContract,
 };
 use noirc_frontend::{
-    graph::{CrateName, CrateType},
+    graph::{CrateGraph, CrateType},
     hir::Context,
 };
 use serde::{Deserialize, Serialize};
-use std::path::PathBuf;
+use std::path::Path;
 use wasm_bindgen::prelude::*;
 
 #[derive(Debug, Serialize, Deserialize)]
@@ -61,10 +62,10 @@ impl Default for WASMCompileOptions {
 }
 
 fn add_noir_lib(context: &mut Context, crate_name: &str) {
-    let path_to_lib = PathBuf::from(&crate_name).join("lib.nr");
-    let library_crate = create_non_local_crate(context, path_to_lib, CrateType::Library);
+    let path_to_lib = Path::new(&crate_name).join("lib.nr");
+    let library_crate = create_non_local_crate(context, &path_to_lib, CrateType::Library);
 
-    propagate_dep(context, library_crate, &CrateName::new(crate_name).unwrap());
+    propagate_dep(context, library_crate, &crate_name.parse().unwrap());
 }
 
 #[wasm_bindgen]
@@ -80,21 +81,25 @@ pub fn compile(args: JsValue) -> JsValue {
 
     debug!("Compiler configuration {:?}", &options);
 
-    let mut context = Context::default();
+    let root = Path::new("/");
+    let fm = FileManager::new(root);
+    let graph = CrateGraph::default();
+    let mut context = Context::new(fm, graph);
 
-    let path = PathBuf::from(&options.entry_point);
+    let path = Path::new(&options.entry_point);
     let crate_id = create_local_crate(&mut context, path, CrateType::Binary);
 
     for dependency in options.optional_dependencies_set {
         add_noir_lib(&mut context, dependency.as_str());
     }
 
-    check_crate(&mut context, false, false).expect("Crate check failed");
+    check_crate(&mut context, crate_id, false).expect("Crate check failed");
 
     if options.contracts {
-        let compiled_contracts = compile_contracts(&mut context, &options.compile_options)
-            .expect("Contract compilation failed")
-            .0;
+        let compiled_contracts =
+            compile_contracts(&mut context, crate_id, &options.compile_options)
+                .expect("Contract compilation failed")
+                .0;
 
         let optimized_contracts: Vec<CompiledContract> =
             compiled_contracts.into_iter().map(optimize_contract).collect();
@@ -102,8 +107,8 @@ pub fn compile(args: JsValue) -> JsValue {
         <JsValue as JsValueSerdeExt>::from_serde(&optimized_contracts).unwrap()
     } else {
         let main = context.get_main_function(&crate_id).expect("Could not find main function!");
-        let mut compiled_program =
-            compile_no_check(&context, &options.compile_options, main).expect("Compilation failed");
+        let mut compiled_program = compile_no_check(&context, true, &options.compile_options, main)
+            .expect("Compilation failed");
 
         compiled_program.circuit = optimize_circuit(compiled_program.circuit);
 
diff --git a/cspell.json b/cspell.json
index 0bd24be47e4..64413c3faf3 100644
--- a/cspell.json
+++ b/cspell.json
@@ -15,6 +15,8 @@
         "combinators",
         "comptime",
         "cranelift",
+        "deflatten",
+        "deflattened",
         "defunctionalize",
         "defunctionalized",
         "defunctionalization",
diff --git a/flake.nix b/flake.nix
index 41081839987..a69c096c3b0 100644
--- a/flake.nix
+++ b/flake.nix
@@ -88,14 +88,7 @@
         BARRETENBERG_BIN_DIR = "${pkgs.barretenberg-wasm}/bin";
       };
 
-      testEnvironment = sharedEnvironment // {
-        # Barretenberg fails if tests are run on multiple threads, so we set the test thread
-        # count to 1 throughout the entire project
-        #
-        # Note: Setting this allows for consistent behavior across build and shells, but is mostly
-        # hidden from the developer - i.e. when they see the command being run via `nix flake check`
-        RUST_TEST_THREADS = "1";
-      };
+      testEnvironment = sharedEnvironment // {};
 
       # The `self.rev` property is only available when the working tree is not dirty
       GIT_COMMIT = if (self ? rev) then self.rev else "unknown";
@@ -124,7 +117,7 @@
 
       sharedArgs = {
         # x-release-please-start-version
-        version = "0.8.0";
+        version = "0.9.0";
         # x-release-please-end
 
         src = pkgs.lib.cleanSourceWith {
diff --git a/noir_stdlib/src/array.nr b/noir_stdlib/src/array.nr
index 9e44aa03fcc..db349317f91 100644
--- a/noir_stdlib/src/array.nr
+++ b/noir_stdlib/src/array.nr
@@ -22,6 +22,15 @@ impl<T, N> [T; N] {
         a
     }
 
+    // Converts an array into a slice.
+    fn as_slice(self) -> [T] {
+        let mut slice = [];
+        for elem in self {
+            slice = slice.push_back(elem);
+        }
+        slice
+    }
+
     // Apply a function to each element of an array, returning a new array
     // containing the mapped elements.
     fn map<U>(self, f: fn(T) -> U) -> [U; N] {
diff --git a/noir_stdlib/src/ecdsa_secp256k1.nr b/noir_stdlib/src/ecdsa_secp256k1.nr
index efeceef5df2..c46380e1988 100644
--- a/noir_stdlib/src/ecdsa_secp256k1.nr
+++ b/noir_stdlib/src/ecdsa_secp256k1.nr
@@ -1,2 +1,2 @@
 #[foreign(ecdsa_secp256k1)]
-fn verify_signature(_public_key_x : [u8; 32], _public_key_y : [u8; 32], _signature: [u8; 64], _message_hash: [u8]) -> bool {}
+fn verify_signature<N>(_public_key_x : [u8; 32], _public_key_y : [u8; 32], _signature: [u8; 64], _message_hash: [u8; N]) -> bool {}
diff --git a/noir_stdlib/src/ecdsa_secp256r1.nr b/noir_stdlib/src/ecdsa_secp256r1.nr
index 44df07d3590..77744384f52 100644
--- a/noir_stdlib/src/ecdsa_secp256r1.nr
+++ b/noir_stdlib/src/ecdsa_secp256r1.nr
@@ -1,2 +1,2 @@
 #[foreign(ecdsa_secp256r1)]
-fn verify_signature(_public_key_x : [u8; 32], _public_key_y : [u8; 32], _signature: [u8; 64], _message_hash: [u8]) -> bool {}
+fn verify_signature<N>(_public_key_x : [u8; 32], _public_key_y : [u8; 32], _signature: [u8; 64], _message_hash: [u8; N]) -> bool {}
diff --git a/noir_stdlib/src/hash/poseidon.nr b/noir_stdlib/src/hash/poseidon.nr
index 416f740bbdf..cb1e34927b4 100644
--- a/noir_stdlib/src/hash/poseidon.nr
+++ b/noir_stdlib/src/hash/poseidon.nr
@@ -101,7 +101,7 @@ fn check_security(rate: Field, width: Field, security: Field) -> bool {
 }
 
 // A*x where A is an n x n matrix in row-major order and x an n-vector
-fn apply_matrix<N>(a: [Field], x: [Field; N]) -> [Field; N] {
+fn apply_matrix<N, M>(a: [Field; M], x: [Field; N]) -> [Field; N] {
     let mut y = x;
 
     for i in 0..x.len() {
diff --git a/noir_stdlib/src/lib.nr b/noir_stdlib/src/lib.nr
index 7629634ac0a..f6c01ecdfaa 100644
--- a/noir_stdlib/src/lib.nr
+++ b/noir_stdlib/src/lib.nr
@@ -15,8 +15,14 @@ mod unsafe;
 mod collections;
 mod compat;
 
-#[builtin(println)]
-fn println<T>(_input : T) {}
+// Oracle calls are required to be wrapped in an unconstrained function
+// Thus, the only argument to the `println` oracle is expected to always be an ident 
+#[oracle(println)]
+unconstrained fn println_oracle<T, A>(_input: T) {}
+
+unconstrained fn println<T>(input: T) {
+    println_oracle(input);
+}
 
 #[foreign(recursive_aggregation)]
 fn verify_proof(_verification_key : [Field], _proof : [Field], _public_inputs : [Field], _key_hash : Field, _input_aggregation_object : [Field]) -> [Field] {}
diff --git a/noir_stdlib/src/merkle.nr b/noir_stdlib/src/merkle.nr
index 1f1a45ffe17..07588a52a5a 100644
--- a/noir_stdlib/src/merkle.nr
+++ b/noir_stdlib/src/merkle.nr
@@ -3,7 +3,7 @@
 // XXX: In the future we can add an arity parameter
 
 // Returns the merkle root of the tree from the provided leaf, its hashpath, using a pedersen hash function.
-fn compute_merkle_root(leaf: Field, index: Field, hash_path: [Field]) -> Field {
+fn compute_merkle_root<N>(leaf: Field, index: Field, hash_path: [Field; N]) -> Field {
     let n = hash_path.len();
     let index_bits = index.to_le_bits(n as u32);
     let mut current = leaf;
@@ -18,4 +18,4 @@ fn compute_merkle_root(leaf: Field, index: Field, hash_path: [Field]) -> Field {
       current = crate::hash::pedersen([hash_left, hash_right])[0];
     };
     current
-}
\ No newline at end of file
+}
diff --git a/noir_stdlib/src/schnorr.nr b/noir_stdlib/src/schnorr.nr
index 5000efd3be4..1e69bcec821 100644
--- a/noir_stdlib/src/schnorr.nr
+++ b/noir_stdlib/src/schnorr.nr
@@ -1,2 +1,2 @@
 #[foreign(schnorr_verify)]
-fn verify_signature(_public_key_x: Field, _public_key_y: Field, _signature: [u8; 64], _message: [u8]) -> bool {}
+fn verify_signature<N>(_public_key_x: Field, _public_key_y: Field, _signature: [u8; 64], _message: [u8; N]) -> bool {}
diff --git a/noir_stdlib/src/slice.nr b/noir_stdlib/src/slice.nr
index 186d535a264..8e344a40f5e 100644
--- a/noir_stdlib/src/slice.nr
+++ b/noir_stdlib/src/slice.nr
@@ -32,74 +32,5 @@ impl<T> [T] {
     /// the removed element
     #[builtin(slice_remove)]
     fn remove(_self: Self, _index: Field) -> (Self, T) { }
- 
-    #[builtin(array_len)]
-    fn len(_self: Self) -> comptime Field {}
-
-    #[builtin(arraysort)]
-    fn sort(_self: Self) -> Self {}
-
-    // Sort with a custom sorting function.
-    fn sort_via(mut a: Self, ordering: fn(T, T) -> bool) -> Self { 
-        for i in 1 .. a.len() {
-            for j in 0..i {
-                if ordering(a[i], a[j]) {
-                    let old_a_j = a[j];
-                    a[j] = a[i];
-                    a[i] = old_a_j;
-                }
-            }
-        }
-        a
-    }
-
-    // Apply a function to each element of a slice, returning a new slice
-    // containing the mapped elements.
-    fn map<U>(self, f: fn(T) -> U) -> [U] {
-        let mut ret: [U] = [];
-        for elem in self {
-            ret = ret.push_back(f(elem));
-        }
-        ret
-    }
-
-    // Apply a function to each element of the slice and an accumulator value,
-    // returning the final accumulated value. This function is also sometimes
-    // called `foldl`, `fold_left`, `reduce`, or `inject`.
-    fn fold<U>(self, mut accumulator: U, f: fn(U, T) -> U) -> U {
-        for elem in self {
-            accumulator = f(accumulator, elem);
-        }
-        accumulator
-    }
-
-    // Apply a function to each element of the slice and an accumulator value,
-    // returning the final accumulated value. Unlike fold, reduce uses the first
-    // element of the given slice as its starting accumulator value.
-    fn reduce(self, f: fn(T, T) -> T) -> T {
-        let mut accumulator = self[0];
-        for i in 1 .. self.len() {
-            accumulator = f(accumulator, self[i]);
-        }
-        accumulator
-    }
-
-    // Returns true if all elements in the array satisfy the predicate
-    fn all(self, predicate: fn(T) -> bool) -> bool {
-        let mut ret = true;
-        for elem in self {
-            ret &= predicate(elem);
-        }
-        ret
-    }
-
-    // Returns true if any element in the array satisfies the predicate
-    fn any(self, predicate: fn(T) -> bool) -> bool {
-        let mut ret = false;
-        for elem in self {
-            ret |= predicate(elem);
-        }
-        ret
-    }
 }