diff --git a/.buildkite/pipeline.yml b/.buildkite/pipeline.yml
index 8b40b454..bc4d8274 100644
--- a/.buildkite/pipeline.yml
+++ b/.buildkite/pipeline.yml
@@ -1,17 +1,4 @@
 steps:
-  - label: ":julia: Run tests on 1.6 LTS"
-    plugins:
-      - JuliaCI/julia#v1:
-          version: "1.6"
-      - JuliaCI/julia-test#v1:
-           coverage: false
-    agents:
-      queue: "juliagpu"
-      cuda: "*"
-    timeout_in_minutes: 60
-    # Don't run Buildkite if the commit message includes the text [skip tests]
-    if: build.message !~ /\[skip tests\]/
-
   - label: ":julia: Run tests on Julia-latest"
     plugins:
       - JuliaCI/julia#v1:
diff --git a/.github/dependabot.yml b/.github/dependabot.yml
index 700707ce..1e8a051e 100644
--- a/.github/dependabot.yml
+++ b/.github/dependabot.yml
@@ -5,3 +5,6 @@ updates:
     directory: "/" # Location of package manifests
     schedule:
       interval: "weekly"
+    ignore:
+      - dependency-name: "crate-ci/typos"
+        update-types: ["version-update:semver-patch"]
diff --git a/.github/workflows/CI.yml b/.github/workflows/CI.yml
index 7452a0c8..ff10977c 100644
--- a/.github/workflows/CI.yml
+++ b/.github/workflows/CI.yml
@@ -1,70 +1,44 @@
 name: CI
-env:
-  DATADEPS_ALWAYS_ACCEPT: true
 on:
-  push:
-    branches: '*'
+  pull_request:
+    branches:
+      - main
     paths-ignore:
       - 'docs/**'
-    tags: '*'
-  pull_request:
+  push:
+    branches:
+      - main
     paths-ignore:
       - 'docs/**'
-concurrency:
-  # Skip intermediate builds: always.
-  # Cancel intermediate builds: only if it is a pull request build.
-  group: ${{ github.workflow }}-${{ github.ref }}
-  cancel-in-progress: ${{ startsWith(github.ref, 'refs/pull/') }}
+  schedule:
+    - cron: '17 14 * * 5'
 jobs:
   test:
-    name: Julia ${{ matrix.version }} - ${{ matrix.os }} - ${{ matrix.arch }} - ${{ github.event_name }}
     runs-on: ${{ matrix.os }}
     strategy:
       fail-fast: false
       matrix:
+        group:
+          - Core
         version:
-          - '1.6'
           - '1'
-          # - 'nightly'
         os:
           - ubuntu-latest
+          - macos-latest
           - windows-latest
-        arch:
-          - x64
     steps:
       - uses: actions/checkout@v4
       - uses: julia-actions/setup-julia@v1
         with:
           version: ${{ matrix.version }}
-          arch: ${{ matrix.arch }}
       - uses: julia-actions/cache@v1
+        with:
+          token: ${{ secrets.GITHUB_TOKEN }}
       - uses: julia-actions/julia-buildpkg@v1
       - uses: julia-actions/julia-runtest@v1
-      - uses: julia-actions/julia-processcoverage@v1
-      - uses: codecov/codecov-action@v3
-        with:
-          files: lcov.info
-  docs:
-    name: Documentation
-    runs-on: ubuntu-latest
-    permissions:
-      contents: write
-    steps:
-      - uses: actions/checkout@v4
-      - uses: julia-actions/setup-julia@v1
         with:
-          version: '1'
-      - uses: julia-actions/julia-buildpkg@v1
-      - uses: julia-actions/julia-docdeploy@v1
-        env:
-          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
-      - run: |
-          julia --project=docs --code-coverage=user -e '
-            using Documenter: DocMeta, doctest
-            using NeuralOperators
-            DocMeta.setdocmeta!(NeuralOperators, :DocTestSetup, :(using NeuralOperators); recursive=true)
-            doctest(NeuralOperators)'
+          depwarn: error
       - uses: julia-actions/julia-processcoverage@v1
       - uses: codecov/codecov-action@v3
         with:
-          file: lcov.info
+          file: lcov.info
\ No newline at end of file
diff --git a/.github/workflows/Documentation.yml b/.github/workflows/Documentation.yml
new file mode 100644
index 00000000..2797d6e2
--- /dev/null
+++ b/.github/workflows/Documentation.yml
@@ -0,0 +1,37 @@
+name: Documentation
+
+on:
+  push:
+    branches:
+      - main
+      - 'release-'
+    tags: '*'
+  pull_request:
+  schedule:
+    - cron: '17 14 * * 5'
+jobs:
+  build:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+      - uses: julia-actions/setup-julia@latest
+        with:
+          version: '1'
+      - name: Install dependencies
+        run: julia --project=docs/ -e 'using Pkg; Pkg.develop(PackageSpec(path=pwd())); Pkg.instantiate()'
+      - name: Build and deploy
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} # For authentication with GitHub Actions token
+          DOCUMENTER_KEY: ${{ secrets.DOCUMENTER_KEY }} # For authentication with SSH deploy key
+        run: julia --project=docs/ --code-coverage=user docs/make.jl
+      - name: Doctest     
+        run: |
+          julia --project=docs --code-coverage=user -e '
+            using Documenter: DocMeta, doctest
+            using NeuralOperators
+            DocMeta.setdocmeta!(NeuralOperators, :DocTestSetup, :(using NeuralOperators); recursive=true)
+            doctest(NeuralOperators)'
+      - uses: julia-actions/julia-processcoverage@v1
+      - uses: codecov/codecov-action@v3
+        with:
+          file: lcov.info
diff --git a/.github/workflows/Downgrade.yml b/.github/workflows/Downgrade.yml
new file mode 100644
index 00000000..aadf1e62
--- /dev/null
+++ b/.github/workflows/Downgrade.yml
@@ -0,0 +1,41 @@
+name: Downgrade
+on:
+  pull_request:
+    branches:
+      - main
+    paths-ignore:
+      - 'docs/**'
+  push:
+    branches:
+      - main
+    paths-ignore:
+      - 'docs/**'
+  schedule:
+    - cron: '17 14 * * 5'
+jobs:
+  test:
+    runs-on: ${{ matrix.os }}
+    strategy:
+      fail-fast: false
+      matrix:
+        group:
+          - Core
+        version:
+          - '1'
+        os:
+          - ubuntu-latest
+          - macos-latest
+          - windows-latest
+    steps:
+      - uses: actions/checkout@v4
+      - uses: julia-actions/setup-julia@v1
+        with:
+          version: ${{ matrix.version }}
+      - uses: cjdoris/julia-downgrade-compat-action@v1
+        with:
+          skip: Pkg,TOML
+      - uses: julia-actions/cache@v1
+        with:
+          token: ${{ secrets.GITHUB_TOKEN }}
+      - uses: julia-actions/julia-buildpkg@v1
+      - uses: julia-actions/julia-runtest@v1
\ No newline at end of file
diff --git a/.github/workflows/SpellCheck.yml b/.github/workflows/SpellCheck.yml
new file mode 100644
index 00000000..599253c8
--- /dev/null
+++ b/.github/workflows/SpellCheck.yml
@@ -0,0 +1,13 @@
+name: Spell Check
+
+on: [pull_request]
+
+jobs:
+  typos-check:
+    name: Spell Check with Typos
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout Actions Repository
+        uses: actions/checkout@v3
+      - name: Check spelling
+        uses: crate-ci/typos@v1.16.23 
\ No newline at end of file
diff --git a/.typos.toml b/.typos.toml
new file mode 100644
index 00000000..79b68a4c
--- /dev/null
+++ b/.typos.toml
@@ -0,0 +1 @@
+[default.extend-words]
\ No newline at end of file
diff --git a/Project.toml b/Project.toml
index dae1364c..a5a5a2ab 100644
--- a/Project.toml
+++ b/Project.toml
@@ -5,32 +5,34 @@ version = "0.4.7"
 
 [deps]
 CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba"
-CUDAKernels = "72cfdca4-0801-4ab0-bf6a-d52aa10adc57"
 ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
 FFTW = "7a1cc6ca-52ef-59f5-83cd-3a7055c09341"
 Flux = "587475ba-b771-5e3f-ad9e-33799f191a9c"
 GeometricFlux = "7e08b658-56d3-11e9-2997-919d5b31e4ea"
-KernelAbstractions = "63c18a36-062a-441e-b654-da1e3ab1ce7c"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 Tullio = "bc48ee85-29a4-5162-ae0b-a64e1601d4bc"
 Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f"
 
 [compat]
-CUDA = "3, 4, 5"
-CUDAKernels = "0.3, 0.4"
-ChainRulesCore = "1"
-FFTW = "1"
-Flux = "0.13"
-GeometricFlux = "0.13"
-KernelAbstractions = "0.7, 0.8"
-Statistics = "1"
-Tullio = "0.3"
-Zygote = "0.6"
-julia = "1.6"
+Aqua = "0.8"
+CUDA = "3.5, 4, 5"
+ChainRulesCore = "1.15"
+FFTW = "1.3.0"
+Flux = "0.13.4"
+GeometricFlux = "0.13.5"
+Graphs = "1.6"
+SafeTestsets = "0.1"
+Statistics = "1.10"
+Test = "1"
+Tullio = "0.3.1"
+Zygote = "0.6.61"
+julia = "1.10"
 
 [extras]
+Aqua = "4c88cf16-eb10-579e-8560-4a9242c79595"
 Graphs = "86223c79-3864-5bf0-83f7-82e725a168b6"
+SafeTestsets = "1bc83da4-3b8d-516f-aca4-4fe02f6d838f"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [targets]
-test = ["Graphs", "Test"]
+test = ["Aqua", "Graphs", "SafeTestsets", "Test"]
diff --git a/src/NeuralOperators.jl b/src/NeuralOperators.jl
index 22c317f2..fa15c088 100644
--- a/src/NeuralOperators.jl
+++ b/src/NeuralOperators.jl
@@ -4,8 +4,6 @@ using Flux
 using FFTW
 using Tullio
 using CUDA
-using CUDAKernels
-using KernelAbstractions
 using Zygote
 using ChainRulesCore
 using GeometricFlux
diff --git a/src/Transform/chebyshev_transform.jl b/src/Transform/chebyshev_transform.jl
index e83a9fff..9771e609 100644
--- a/src/Transform/chebyshev_transform.jl
+++ b/src/Transform/chebyshev_transform.jl
@@ -1,14 +1,14 @@
 export ChebyshevTransform
 
-struct ChebyshevTransform{N, S} <: AbstractTransform
-    modes::NTuple{N, S} # N == ndims(x)
+struct ChebyshevTransform{nMinus1, S} <: AbstractTransform
+    modes::Tuple{S,Vararg{S,nMinus1}} # nMinus1 == ndims(x)-1
 end
 
-Base.ndims(::ChebyshevTransform{N}) where {N} = N
+Base.ndims(::ChebyshevTransform{nMinus1}) where {nMinus1} = nMinus1 + 1
 Base.eltype(::Type{ChebyshevTransform}) = Float32
 
-function transform(t::ChebyshevTransform{N}, 𝐱::AbstractArray) where {N}
-    return FFTW.r2r(𝐱, FFTW.REDFT10, 1:N) # [size(x)..., in_chs, batch]
+function transform(t::ChebyshevTransform{nMinus1}, 𝐱::AbstractArray) where {nMinus1}
+    return FFTW.r2r(𝐱, FFTW.REDFT10, 1:(nMinus1+1)) # [size(x)..., in_chs, batch]
 end
 
 function truncate_modes(t::ChebyshevTransform, 𝐱̂::AbstractArray)
@@ -31,7 +31,7 @@ function ∇r2r(Δ::AbstractArray{T}, kind, dims) where {T}
     # derivative of r2r turns out to be r2r
     Δx = FFTW.r2r(Δ, kind, dims)
 
-    # rank 4 correction: needs @bischtob to elaborate the reason using this. 
+    # rank 4 correction: needs @bischtob to elaborate the reason using this.
     # (M,) = size(Δ)[dims]
     # a1 = fill!(similar(Δ, M), one(T))
     # CUDA.@allowscalar a1[1] = a1[end] = zero(T)
diff --git a/src/Transform/fourier_transform.jl b/src/Transform/fourier_transform.jl
index bab74918..d5ebe777 100644
--- a/src/Transform/fourier_transform.jl
+++ b/src/Transform/fourier_transform.jl
@@ -1,10 +1,10 @@
 export FourierTransform
 
-struct FourierTransform{N, S} <: AbstractTransform
-    modes::NTuple{N, S} # N == ndims(x)
+struct FourierTransform{nMinus1, S} <: AbstractTransform
+    modes::Tuple{S,Vararg{S,nMinus1}} # nMinus1 == ndims(x)-1
 end
 
-Base.ndims(::FourierTransform{N}) where {N} = N
+Base.ndims(::FourierTransform{nMinus1}) where {nMinus1} = nMinus1+1
 Base.eltype(::Type{FourierTransform}) = ComplexF32
 
 function transform(ft::FourierTransform, 𝐱::AbstractArray)
diff --git a/test/DeepONet/DeepONet.jl b/test/DeepONet/DeepONet.jl
index 80244ce4..8a7fd558 100644
--- a/test/DeepONet/DeepONet.jl
+++ b/test/DeepONet/DeepONet.jl
@@ -1,3 +1,6 @@
+using NeuralOperators
+using CUDA; CUDA.allowscalar(false)
+using Flux
 @testset "DeepONet" begin
     @testset "proper construction" begin
         deeponet = DeepONet((32, 64, 72), (24, 48, 72), σ, tanh)
diff --git a/test/FNO/FNO.jl b/test/FNO/FNO.jl
index bfad873c..44d9a438 100644
--- a/test/FNO/FNO.jl
+++ b/test/FNO/FNO.jl
@@ -1,3 +1,5 @@
+using NeuralOperators
+using Flux
 @testset "FourierNeuralOperator" begin
     m = FourierNeuralOperator()
 
diff --git a/test/NOMAD/NOMAD.jl b/test/NOMAD/NOMAD.jl
index 9b46296b..76ad3f99 100644
--- a/test/NOMAD/NOMAD.jl
+++ b/test/NOMAD/NOMAD.jl
@@ -1,3 +1,5 @@
+using NeuralOperators
+using Flux
 @testset "NOMAD" begin
     @testset "proper construction" begin
         nomad = NOMAD((32, 64, 72), (24, 48, 72), σ, tanh)
diff --git a/test/Transform/Transform.jl b/test/Transform/Transform.jl
deleted file mode 100644
index d5ff9a67..00000000
--- a/test/Transform/Transform.jl
+++ /dev/null
@@ -1,4 +0,0 @@
-@testset "Transform" begin
-    include("fourier_transform.jl")
-    include("chebyshev_transform.jl")
-end
diff --git a/test/Transform/chebyshev_transform.jl b/test/Transform/chebyshev_transform.jl
deleted file mode 100644
index b15ff9df..00000000
--- a/test/Transform/chebyshev_transform.jl
+++ /dev/null
@@ -1,16 +0,0 @@
-@testset "Chebyshev transform" begin
-    ch = 6
-    batch = 7
-    𝐱 = rand(30, 40, 50, ch, batch)
-
-    t = ChebyshevTransform((3, 4, 5))
-
-    @test ndims(t) == 3
-    @test size(transform(t, 𝐱)) == (30, 40, 50, ch, batch)
-    @test size(truncate_modes(t, transform(t, 𝐱))) == (3, 4, 5, ch, batch)
-    @test size(inverse(t, truncate_modes(t, transform(t, 𝐱)), size(𝐱))) ==
-          (3, 4, 5, ch, batch)
-
-    g = gradient(x -> sum(inverse(t, truncate_modes(t, transform(t, x)), size(𝐱))), 𝐱)
-    @test size(g[1]) == (30, 40, 50, ch, batch)
-end
diff --git a/test/Transform/fourier_transform.jl b/test/Transform/fourier_transform.jl
deleted file mode 100644
index 4583906a..00000000
--- a/test/Transform/fourier_transform.jl
+++ /dev/null
@@ -1,22 +0,0 @@
-@testset "Fourier transform" begin
-    ch = 6
-    batch = 7
-    𝐱 = rand(30, 40, 50, ch, batch)
-
-    ft = FourierTransform((3, 4, 5))
-
-    @test size(transform(ft, 𝐱)) == (16, 40, 50, ch, batch)
-    @test size(truncate_modes(ft, transform(ft, 𝐱))) == (3, 4, 5, ch, batch)
-    @test size(inverse(ft,
-                       NeuralOperators.pad_modes(truncate_modes(ft, transform(ft, 𝐱)),
-                                                 size(transform(ft, 𝐱))),
-                       size(𝐱))) == (30, 40, 50, ch, batch)
-
-    g = Zygote.gradient(x -> sum(inverse(ft,
-                                         NeuralOperators.pad_modes(truncate_modes(ft,
-                                                                                  transform(ft,
-                                                                                            x)),
-                                                                   (16, 40, 50, ch, batch)),
-                                         (30, 40, 50, ch, batch))), 𝐱)
-    @test size(g[1]) == (30, 40, 50, ch, batch)
-end
diff --git a/test/chebyshev_transform.jl b/test/chebyshev_transform.jl
new file mode 100644
index 00000000..4ef84b80
--- /dev/null
+++ b/test/chebyshev_transform.jl
@@ -0,0 +1,13 @@
+using NeuralOperators
+using Zygote
+ch = 6
+batch = 7
+𝐱 = rand(30, 40, 50, ch, batch)
+t = ChebyshevTransform((3, 4, 5))
+@test ndims(t) == 3
+@test size(transform(t, 𝐱)) == (30, 40, 50, ch, batch)
+@test size(truncate_modes(t, transform(t, 𝐱))) == (3, 4, 5, ch, batch)
+@test size(inverse(t, truncate_modes(t, transform(t, 𝐱)), size(𝐱))) ==
+      (3, 4, 5, ch, batch)
+g = gradient(x -> sum(inverse(t, truncate_modes(t, transform(t, x)), size(𝐱))), 𝐱)
+@test size(g[1]) == (30, 40, 50, ch, batch)
diff --git a/test/fourier_transform.jl b/test/fourier_transform.jl
new file mode 100644
index 00000000..77f3e695
--- /dev/null
+++ b/test/fourier_transform.jl
@@ -0,0 +1,19 @@
+using NeuralOperators
+using Zygote
+ch = 6
+batch = 7
+𝐱 = rand(30, 40, 50, ch, batch)
+ft = FourierTransform((3, 4, 5))
+@test size(transform(ft, 𝐱)) == (16, 40, 50, ch, batch)
+@test size(truncate_modes(ft, transform(ft, 𝐱))) == (3, 4, 5, ch, batch)
+@test size(inverse(ft,
+                   NeuralOperators.pad_modes(truncate_modes(ft, transform(ft, 𝐱)),
+                                             size(transform(ft, 𝐱))),
+                   size(𝐱))) == (30, 40, 50, ch, batch)
+g = Zygote.gradient(x -> sum(inverse(ft,
+                                     NeuralOperators.pad_modes(truncate_modes(ft,
+                                                                              transform(ft,
+                                                                                        x)),
+                                                               (16, 40, 50, ch, batch)),
+                                     (30, 40, 50, ch, batch))), 𝐱)
+@test size(g[1]) == (30, 40, 50, ch, batch)
diff --git a/test/graph_kernel.jl b/test/graph_kernel.jl
index 743257ce..b11b48e8 100644
--- a/test/graph_kernel.jl
+++ b/test/graph_kernel.jl
@@ -1,24 +1,26 @@
-@testset "GraphKernel" begin
-    batch_size = 5
-    channel = 1
-    coord_dim = 2
-    N = 10
+using NeuralOperators
+using Flux
+using Graphs
+using GeometricFlux
+batch_size = 5
+channel = 1
+coord_dim = 2
+N = 10
 
-    graph = grid([N, N])
-    𝐱 = rand(Float32, channel, nv(graph), batch_size)
-    κ = Dense(2(coord_dim + channel), abs2(channel), relu)
-    κ_in_dim, κ_out_dim = 2(coord_dim + channel), abs2(channel)
+graph = grid([N, N])
+𝐱 = rand(Float32, channel, nv(graph), batch_size)
+κ = Dense(2(coord_dim + channel), abs2(channel), relu)
+κ_in_dim, κ_out_dim = 2(coord_dim + channel), abs2(channel)
 
-    @testset "layer without graph" begin
-        pf = rand(Float32, coord_dim, nv(graph), batch_size)
-        pf = vcat(𝐱, pf)
-        l = GraphKernel(κ, channel)
-        fg = FeaturedGraph(graph, nf = 𝐱, pf = pf)
-        fg_ = l(fg)
-        @test size(node_feature(fg_)) == (channel, nv(graph), batch_size)
-        @test_throws MethodError l(𝐱)
+@testset "layer without graph" begin
+    pf = rand(Float32, coord_dim, nv(graph), batch_size)
+    pf = vcat(𝐱, pf)
+    l = GraphKernel(κ, channel)
+    fg = FeaturedGraph(graph, nf = 𝐱, pf = pf)
+    fg_ = l(fg)
+    @test size(node_feature(fg_)) == (channel, nv(graph), batch_size)
+    @test_throws MethodError l(𝐱)
 
-        g = gradient(() -> sum(node_feature(l(fg))), Flux.params(l))
-        @test length(g.grads) == 5
-    end
+    g = gradient(() -> sum(node_feature(l(fg))), Flux.params(l))
+    @test length(g.grads) == 5
 end
diff --git a/test/loss.jl b/test/loss.jl
index bac34f88..525d6762 100644
--- a/test/loss.jl
+++ b/test/loss.jl
@@ -1,10 +1,7 @@
-@testset "loss" begin
-    𝐲 = rand(1, 3, 3, 5)
-    𝐲̂ = rand(1, 3, 3, 5)
-
-    feature_dims = 2:3
-    loss = sum(.√(sum(abs2, 𝐲̂ - 𝐲, dims = feature_dims)))
-    y_norm = sum(.√(sum(abs2, 𝐲, dims = feature_dims)))
-
-    @test l₂loss(𝐲̂, 𝐲) ≈ loss / y_norm
-end
+using NeuralOperators
+𝐲 = rand(1, 3, 3, 5)
+𝐲̂ = rand(1, 3, 3, 5)
+feature_dims = 2:3
+loss = sum(.√(sum(abs2, 𝐲̂ - 𝐲, dims = feature_dims)))
+y_norm = sum(.√(sum(abs2, 𝐲, dims = feature_dims)))
+@test l₂loss(𝐲̂, 𝐲) ≈ loss / y_norm
diff --git a/test/operator_kernel.jl b/test/operator_kernel.jl
index c64396bc..33a77e26 100644
--- a/test/operator_kernel.jl
+++ b/test/operator_kernel.jl
@@ -1,3 +1,5 @@
+using NeuralOperators
+using Flux
 @testset "1D OperatorConv" begin
     modes = (16,)
     ch = 64 => 128
diff --git a/test/qa.jl b/test/qa.jl
new file mode 100644
index 00000000..6bdd5eda
--- /dev/null
+++ b/test/qa.jl
@@ -0,0 +1,11 @@
+using NeuralOperators, Aqua
+@testset "Aqua" begin
+    Aqua.find_persistent_tasks_deps(NeuralOperators)
+    Aqua.test_ambiguities(NeuralOperators, recursive = false)
+    Aqua.test_deps_compat(NeuralOperators)
+    Aqua.test_piracies(NeuralOperators, broken = true)
+    Aqua.test_project_extras(NeuralOperators)
+    Aqua.test_stale_deps(NeuralOperators)
+    Aqua.test_unbound_args(NeuralOperators)
+    Aqua.test_undefined_exports(NeuralOperators)
+end
diff --git a/test/runtests.jl b/test/runtests.jl
index 6ffe561a..385c392d 100644
--- a/test/runtests.jl
+++ b/test/runtests.jl
@@ -1,24 +1,18 @@
-using NeuralOperators
-using CUDA
-using Flux
-using GeometricFlux
-using Graphs
-using Zygote
-using Test
-
-CUDA.allowscalar(false)
+using SafeTestsets, Test
 
 @testset "NeuralOperators.jl" begin
+    @safetestset "Quality Assurance" include("qa.jl")
     # kernels
-    include("Transform/Transform.jl")
-    include("operator_kernel.jl")
-    include("graph_kernel.jl")
-    include("loss.jl")
+    @safetestset "Fourier Transform" include("fourier_transform.jl")
+    @safetestset "Chebyshev Transform" include("chebyshev_transform.jl")
+    @safetestset "operator_kernel.jl" include("operator_kernel.jl")
+    @safetestset "graph kernel" include("graph_kernel.jl")
+    @safetestset "loss" include("loss.jl")
 
     # models
-    include("FNO/FNO.jl")
-    include("DeepONet/DeepONet.jl")
-    include("NOMAD/NOMAD.jl")
+    @safetestset "FNO" include("FNO/FNO.jl")
+    @safetestset "DeepONet" include("DeepONet/DeepONet.jl")
+    @safetestset "NOMAD" include("NOMAD/NOMAD.jl")
 end
 
 #=