This document contains some useful information for debugging:
- The Swift compiler.
- Intermediate output of the Swift Compiler.
- Swift applications at runtime.
Please feel free to add any useful tips that one finds to this document for the benefit of all Swift developers.
Table of Contents
- Debugging the Compiler Itself
- Debugging the Compiler Build
- Debugging the Compiler Driver
- Debugging Swift Executables
- Debugging LLDB failures
- Compiler Tools/Options for Bug Hunting
Often, the first step to debug a compiler problem is to re-run the compiler with a command line, which comes from a crash trace or a build log.
The script split-cmdline
in utils/dev-scripts
splits a command line
into multiple lines. This is helpful to understand and edit long command lines.
The most important thing when debugging the compiler is to examine the IR. Here is how to dump the IR after the main phases of the Swift compiler (assuming you are compiling with optimizations enabled):
- Parser To print the AST after parsing:
swiftc -dump-ast -O file.swift
- SILGen To print the SIL immediately after SILGen:
swiftc -emit-silgen -O file.swift
- Mandatory SIL passes To print the SIL after the mandatory passes:
swiftc -emit-sil -Onone file.swift
Well, this is not quite true, because the compiler is running some passes for -Onone after the mandatory passes, too. But for most purposes you will get what you want to see.
- Performance SIL passes To print the SIL after the complete SIL optimization pipeline:
swiftc -emit-sil -O file.swift
- Debug info in SIL To print debug info from
file.swift
in SIL:
swiftc -g -emit-sil -O file.swift
- IRGen To print the LLVM IR after IR generation:
swiftc -emit-ir -Xfrontend -disable-llvm-optzns -O file.swift
- LLVM passes To print the LLVM IR after LLVM passes:
swiftc -emit-ir -O file.swift
- Code generation To print the final generated code:
swiftc -S -O file.swift
Compilation stops at the phase where you print the output. So if you want to
print the SIL and the LLVM IR, you have to run the compiler twice.
The output of all these dump options (except -dump-ast
) can be redirected
with an additional -o <file>
option.
When changing the type checker and various SIL passes, one can cause a series of cascading diagnostics (errors/warnings) to be emitted. Since Swift does not by default assert when emitting such diagnostics, it becomes difficult to know where to stop in the debugger. Rather than trying to guess/check if one has an asserts swift compiler, one can use the following options to cause the diagnostic engine to assert on the first error/warning:
-Xllvm -swift-diagnostics-assert-on-error=1
-Xllvm -swift-diagnostics-assert-on-warning=1
These allow one to dump a stack trace of where the diagnostic is being emitted (if run without a debugger) or drop into the debugger if a debugger is attached.
Some diagnostics rely heavily on format string arguments, so it can be difficult
to find their implementation by searching for parts of the emitted message in
the codebase. To print the corresponding diagnostic name at the end of each
emitted message, use the -Xfrontend -debug-diagnostic-names
argument.
To enable logging in the type checker, use the following argument: -Xfrontend -debug-constraints
.
This will cause the typechecker to log its internal state as it solves
constraints and present the final type checked solution, e.g.:
---Constraint solving at [test.swift:3:1 - line:3:1]---
---Initial constraints for the given expression---
(integer_literal_expr type='$T0' location=test.swift:3:1 range=[test.swift:3:1 - line:3:1] value=0 builtin_initializer=**NULL** initializer=**NULL**)
Score: <default 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0>
Type Variables:
($T0 [attributes: [literal: integer]] [with possible bindings: (default type of literal) Int]) @ locator@0x13e009800 [IntegerLiteral@test.swift:3:1]
Inactive Constraints:
$T0 literal conforms to ExpressibleByIntegerLiteral @ locator@0x13e009800 [IntegerLiteral@test.swift:3:1]
(Potential Binding(s):
($T0 [attributes: [literal: integer]] [with possible bindings: (default type of literal) Int])
(attempting type variable $T0 := Int
(considering: $T0 literal conforms to ExpressibleByIntegerLiteral @ locator@0x13e009800 [IntegerLiteral@test.swift:3:1]
(simplification result:
(removed constraint: $T0 literal conforms to ExpressibleByIntegerLiteral @ locator@0x13e009800 [IntegerLiteral@test.swift:3:1])
)
(outcome: simplified)
)
(Changes:
(Newly Bound:
> $T0 := Int
)
(Removed Constraint:
> $T0 literal conforms to ExpressibleByIntegerLiteral @ locator@0x13e009800 [IntegerLiteral@test.swift:3:1]
)
)
(found solution: <default 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0>)
)
---Solver statistics---
Total number of scopes explored: 2
Maximum depth reached while exploring solutions: 2
Time: 2.164000e+00ms
---Solution---
Fixed score: <default 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0>
Type variables:
$T0 as Int @ locator@0x13e009800 [IntegerLiteral@test.swift:3:1]
---Type-checked expression---
(integer_literal_expr type='Int' location=test.swift:3:1 range=[test.swift:3:1 - line:3:1] value=0 builtin_initializer=Swift.(file).Int.init(_builtinIntegerLiteral:) initializer=**NULL**)
When using swift LLDB REPL, one can dump the same output for each
expression as one evaluates the expression by enabling constraints debugging by
passing the flag -Xfrontend -debug-constraints
:
$ swift repl -Xfrontend -debug-constraints
1> let foo = 1
Often it is not sufficient to dump the SIL at the beginning or end of the optimization pipeline. The SILPassManager supports useful options to dump the SIL also between pass runs.
A short (non-exhaustive) list of SIL printing options:
-
-Xllvm '-sil-print-function=SWIFT_MANGLED_NAME'
: Print the specified function after each pass which modifies the function. Note that for module passes, the function is printed if the pass changed any function (the pass manager doesn't know which functions a module pass has changed). Multiple functions can be specified as a comma separated list. -
-Xllvm '-sil-print-functions=NAME'
: Like-sil-print-function
, except that functions are selected if NAME is contained in their mangled names. -
-Xllvm -sil-print-all
: Print all functions when ever a function pass modifies a function and print the entire module if a module pass modifies the SILModule. -
-Xllvm -sil-print-around=$PASS_NAME
: Print the SIL before and after a pass with name$PASS_NAME
runs on a function or module. By default it prints the whole module. To print only specific functions, add-sil-print-function
and/or-sil-print-functions
. -
-Xllvm -sil-print-before=$PASS_NAME
: Like-sil-print-around
, but prints the SIL only before the specified pass runs. -
-Xllvm -sil-print-after=$PASS_NAME
: Like-sil-print-around
, but prints the SIL only after the specified pass did run.
NOTE: This may emit a lot of text to stderr, so be sure to pipe the output to a file.
If one builds swift using ninja and wants to dump the SIL of the stdlib using some of the SIL dumping options from the previous section, one can use the following one-liner:
ninja -t commands | grep swiftc | grep Swift.o | grep " -c "
This should give one a single command line that one can use for Swift.o, perfect for applying the previous sections options to.
When debugging the Swift compiler with LLDB (or Xcode, of course), there is
even a more powerful way to examine the data in the compiler, e.g. the SIL.
Following LLVM's dump() convention, many SIL classes (as well as AST classes)
provide a dump() function. You can call the dump function with LLDB's
expression --
or print
or p
command.
For example, to examine a SIL instruction:
(lldb) p Inst->dump()
%12 = struct_extract %10 : $UnsafeMutablePointer<X>, #UnsafeMutablePointer._rawValue // user: %13
To dump a whole function at the beginning of a function pass:
(lldb) p getFunction()->dump()
SIL modules and even functions can get very large. Often it is more convenient to dump their contents into a file and open the file in a separate editor. This can be done with:
(lldb) p getFunction()->dump("myfunction.sil")
You can also dump the CFG (control flow graph) of a function:
(lldb) p Func->viewCFG()
This opens a preview window containing the CFG of the function. To continue debugging press -C on the LLDB prompt. Note that this only works in Xcode if the PATH variable in the scheme's environment setting contains the path to the dot tool.
swift/Basic/Debug.h includes macros to help contributors declare these methods
with the proper attributes to ensure they'll be available in the debugger. In
particular, if you see SWIFT_DEBUG_DUMP
in a class declaration, that class
has a dump()
method you can call.
The compiler provides a way to debug and profile on SIL level. To enable SIL debugging add the front-end option -sil-based-debuginfo together with -g. Example:
swiftc -g -Xfrontend -sil-based-debuginfo -O test.swift -o a.out
This writes the SIL after optimizations into a file and generates debug info for it. In the debugger and profiler you can then see the SIL code instead of the Swift source code. For details see the SILDebugInfoGenerator pass.
To enable SIL debugging and profiling for the Swift standard library, use
the build-script-impl option --build-sil-debugging-stdlib
.
ViewCFG (./utils/viewcfg
) is a script that parses a textual CFG (e.g. a llvm
or sil function) and displays a .dot file of the CFG. Since the parsing is done
using regular expressions (i.e. ignoring language semantics), ViewCFG can:
- Parse both SIL and LLVM IR
- Parse blocks and functions without needing to know contextual information. Ex: types and declarations.
The script assumes that the relevant text is passed in via stdin and uses open to display the .dot file.
Additional, both emacs and vim integration is provided. For vim integration add the following commands to your .vimrc:
com! -nargs=? Funccfg silent ?{$?,/^}/w !viewcfg <args>
com! -range -nargs=? Viewcfg silent <line1>,<line2>w !viewcfg <args>
This will add:
:Funccfg displays the CFG of the current SIL/LLVM function.
:<range>Viewcfg displays the sub-CFG of the selected range.
For emacs users, we provide in sil-mode (./utils/sil-mode.el
) the function:
sil-mode-display-function-cfg
To use this feature, placed the point in the sil function that you want viewcfg
to graph and then run sil-mode-display-function-cfg
. This will cause viewcfg
to be invoked with the sil function body. Note,
sil-mode-display-function-cfg
does not take any arguments.
NOTE viewcfg must be in the $PATH for viewcfg to work.
NOTE Since we use open, .dot files should be associated with the Graphviz app for viewcfg to work.
There is another useful script to view the CFG of a disassembled function:
./utils/dev-scripts/blockifyasm
.
It splits a disassembled function up into basic blocks which can then be
used with viewcfg:
(lldb) disassemble
<copy-paste output to file.s>
$ blockifyasm < file.s | viewcfg
LLDB has very powerful breakpoints, which can be utilized in many ways to debug the compiler and Swift executables. The examples in this section show the LLDB command lines. In Xcode you can set the breakpoint properties by clicking 'Edit breakpoint'.
Let's start with a simple example: sometimes you see a function in the SIL output and you want to know where the function was created in the compiler. In this case you can set a conditional breakpoint in SILFunction constructor and check for the function name in the breakpoint condition:
(lldb) br set -c 'hasName("_TFC3nix1Xd")' -f SILFunction.cpp -l 91
Sometimes you may want to know which optimization inserts, removes or moves a
certain instruction. To find out, set a breakpoint in
ilist_traits<SILInstruction>::addNodeToList
or
ilist_traits<SILInstruction>::removeNodeFromList
, which are defined in
SILInstruction.cpp
.
The following command sets a breakpoint which stops if a strong_retain
instruction is removed:
(lldb) br set -c 'I->getKind() == ValueKind::StrongRetainInst' -f SILInstruction.cpp -l 63
The condition can be made more precise e.g. by also testing in which function this happens:
(lldb) br set -c 'I->getKind() == ValueKind::StrongRetainInst &&
I->getFunction()->hasName("_TFC3nix1Xd")'
-f SILInstruction.cpp -l 63
Let's assume the breakpoint hits somewhere in the middle of compiling a large
file. This is the point where the problem appears. But often you want to break
a little bit earlier, e.g. at the entrance of the optimization's run
function.
To achieve this, set another breakpoint and add breakpoint commands:
(lldb) br set -n GlobalARCOpts::run
Breakpoint 2
(lldb) br com add 2
> p int $n = $n + 1
> c
> DONE
Run the program (this can take quite a bit longer than before). When the first breakpoint hits see what value $n has:
(lldb) p $n
(int) $n = 5
Now remove the breakpoint commands from the second breakpoint (or create a new one) and set the ignore count to $n minus one:
(lldb) br delete 2
(lldb) br set -i 4 -n GlobalARCOpts::run
Run your program again and the breakpoint hits just before the first breakpoint.
Another method for accomplishing the same task is to set the ignore count of the breakpoint to a large number, i.e.:
(lldb) br set -i 9999999 -n GlobalARCOpts::run
Then whenever the debugger stops next time (due to hitting another breakpoint/crash/assert) you can list the current breakpoints:
(lldb) br list
1: name = 'GlobalARCOpts::run', locations = 1, resolved = 1, hit count = 85 Options: ignore: 1 enabled
which will then show you the number of times that each breakpoint was hit. In
this case, we know that GlobalARCOpts::run
was hit 85 times. So, now
we know to ignore swift_getGenericMetadata 84 times, i.e.:
(lldb) br set -i 84 -n GlobalARCOpts::run
A final trick is that one can use the -R option to stop at a relative assembly address in lldb. Specifically, lldb resolves the breakpoint normally and then just adds the argument -R to the address. So for instance, if I want to stop at the address at +38 in the function with the name 'foo', I would write:
(lldb) br set -R 38 -n foo
Then lldb would add 38 to the offset of foo and break there. This is really useful in contexts where one wants to set a breakpoint at an assembly address that is stable across multiple different invocations of lldb.
LLDB has powerful capabilities of scripting in Python among other languages. An often overlooked, but very useful technique is the -s command to lldb. This essentially acts as a pseudo-stdin of commands that lldb will read commands from. Each time lldb hits a stopping point (i.e. a breakpoint or a crash/assert), it will run the earliest command that has not been run yet. As an example of this consider the following script (which without any loss of generality will be called test.lldb):
env DYLD_INSERT_LIBRARIES=/usr/lib/libgmalloc.dylib
break set -n swift_getGenericMetadata
break mod 1 -i 83
process launch -- --stdlib-unittest-in-process --stdlib-unittest-filter "DefaultedForwardMutableCollection<OpaqueValue<Int>>.Type.subscript(_: Range)/Set/semantics"
break set -l 224
c
expr pattern->CreateFunction
break set -a $0
c
dis -f
TODO: Change this example to apply to the Swift compiler instead of to the stdlib unittests.
Then by running lldb test -s test.lldb
, lldb will:
- Enable guard malloc.
- Set a break point on swift_getGenericMetadata and set it to be ignored for 83 hits.
- Launch the application and stop at swift_getGenericMetadata after 83 hits have been ignored.
- In the same file as swift_getGenericMetadata introduce a new breakpoint at line 224 and continue.
- When we break at line 224 in that file, evaluate an expression pointer.
- Set a breakpoint at the address of the expression pointer and continue.
- When we hit the breakpoint set at the function pointer's address, disassemble the function that the function pointer was passed to.
Using LLDB scripts can enable one to use complex debugger workflows without needing to retype the various commands perfectly every time.
If you've ever found yourself repeatedly entering a complex sequence of commands within a debug session, consider using custom lldb commands. Custom commands are a handy way to automate debugging tasks.
For example, say we need a command that prints the contents of the register
rax
and then steps to the next instruction. Here's how to define that
command within a debug session:
(lldb) script
Python Interactive Interpreter. To exit, type 'quit()', 'exit()' or Ctrl-D.
>>> def custom_step():
... print "rax =", lldb.frame.FindRegister("rax")
... lldb.thread.StepInstruction(True)
...
>>> ^D
You can call this function using the script
command, or via an alias:
(lldb) script custom_step()
rax = ...
<debugger steps to the next instruction>
(lldb) command alias cs script custom_step()
(lldb) cs
rax = ...
<debugger steps to the next instruction>
Printing registers and single-stepping are by no means the only things you can do with custom commands. The LLDB Python API surfaces a lot of useful functionality, such as arbitrary expression evaluation.
There are some pre-defined custom commands which can be especially useful while
debugging the swift compiler. These commands live in
swift/utils/lldb/lldbToolBox.py
. There is a wrapper script available in
SWIFT_BINARY_DIR/bin/lldb-with-tools
which launches lldb with those
commands loaded.
A command named sequence
is included in lldbToolBox. sequence
runs
multiple semicolon separated commands together as one command. This can be used
to define custom commands using just other lldb commands. For example,
custom_step()
function defined above could be defined as:
(lldb) command alias cs sequence p/x $rax; stepi
Similar to SIL, one can configure LLVM to dump the llvm-ir at various points in the pipeline. Here is a quick summary of the various options:
-Xllvm -print-before=$PASS_ID
: Print the LLVM IR before a specified LLVM pass runs.-Xllvm -print-before-all
: Print the LLVM IR before each pass runs.-Xllvm -print-after-all
: Print the LLVM IR after each pass runs.-Xllvm -filter-print-funcs=$FUNC_NAME_1,$FUNC_NAME_2,...,$FUNC_NAME_N
: When printing IR for functions for print-[before|after]-all options, Only print the IR for functions whose name is in this comma separated list.
Understanding layout of compiler-generated metadata can sometimes involve looking at assembly and object code.
Here's how to generate assembly or object code:
# Emit assembly in Intel syntax (AT&T syntax is the default)
swiftc tmp.swift -emit-assembly -Xllvm -x86-asm-syntax=intel -o tmp.S
# Emit object code
swiftc tmp.swift -emit-object -o tmp.o
Understanding mangled names can be hard though: swift demangle
to the rescue!
swiftc tmp.swift -emit-assembly -Xllvm -x86-asm-syntax=intel -o - \
| swift demangle > tmp-demangled.S
swiftc tmp.swift -emit-object -o tmp.o
# Look at where different symbols are located, sorting by address (-n)
# and displaying section names (-m)
nm -n -m tmp.o | swift demangle > tmp.txt
# Inspect disassembly of an existing dylib (AT&T syntax is the default)
objdump -d -macho --x86-asm-syntax=intel /path/to/libcake.dylib \
| swift demangle > libcake.S
Some bugs only manifest in WMO, and may involve complicated Xcode projects.
Moreover, Xcode may be passing arguments via -filelist
and expecting outputs via -output-filelist
, and those file lists
may be in temporary directories.
If you want to inspect assembly or object code for individual files when compiling under WMO, you can mimic this by doing the following:
# Assuming all .swift files from the MyProject/Sources directory
# need to be included
find MyProject/Sources -name '*.swift' -type f > input-files.txt
# In some cases, projects may use multiple files with the same
# name but in different directories (for different schemes),
# which can be a problem. Having a file list makes working around
# this convenient as you can manually edit out the files
# that are not of interest at this stage.
mkdir Output
# 1. -output-filelist doesn't recreate a subdirectory structure,
# so first strip out directories
# 2. map .swift files to assembly files
sed -e 's|.*/|Output/|;s|\.swift|.S|' input-files.txt > output-files.txt
# Save command-line arguments from Xcode's 'CompileSwiftSources' phase in
# the build log to a file for convenience, say args.txt.
#
# -sdk /path/to/sdk <... other args ...>
xcrun swift-frontend @args.txt \
-filelist input-files.txt \
-output-filelist output-files.txt \
-O -whole-module-optimization \
-emit-assembly
If you are manually calling swift-frontend
without an Xcode invocation to
use as a template, you will need to at least add
-sdk "$(xcrun --show-sdk-path macosx)"
(if compiling for macOS),
and -I /path/to/includedir
to include necessary swift modules and interfaces.
On macOS, one might be interested in debugging multi-architecture binaries
such as universal binaries. By default nm
will show symbols from all
architectures, so a universal binary might look funny due to two copies of
everything. Use nm -arch
to look at a specific architecture:
nm -n -m -arch x86_64 path/to/libcake.dylib | swift demangle
TODO: This section should mention information about non-macOS platforms: maybe we can have a table with rows for use cases and columns for platforms (macOS, Linux, Windows), and the cells would be tool names. We could also mention platforms next to the tool names.
In the previous sub-sections, we've seen how using different tools can make working with assembly and object code much nicer. Here is a short listing of commonly used tools on macOS, along with some example use cases:
-
Miscellaneous:
-
strings
: Find printable strings in a binary file. -
Potential use cases: If you're building a binary in multiple configurations, and forgot which binary corresponds to which configuration, you can look through the output of
strings
to identify differences. -
c++filt
: The C++ equivalent ofswift-demangle
.- Potential use cases: Looking at the generated code for the Swift runtime, investigating C++ interop issues.
-
Linking:
libtool
: A tool to create static and dynamic libraries. Generally, it's easier to instead askswiftc
to link files, but potentially handy as a higher-level alternative told
,ar
andlipo
.
-
Debug info:
dwarfdump
: Extract debug info in human-readable form.- Potential use cases: If you want to quickly check if two binaries
are identical, you can compare their UUIDs. For on-disk binaries,
you can obtain the UUID using
dwarfdump --uuid
For binaries loaded by a running application, you can obtain the UUID usingimage list
in LLDB.
- Potential use cases: If you want to quickly check if two binaries
are identical, you can compare their UUIDs. For on-disk binaries,
you can obtain the UUID using
-
objdump
: Dump object files. Some examples of usingobjdump
are documented in the previous subsection. If you have a Swift compiler build, you can usellvm-objdump
from$LLVM_BUILD_DIR/bin
instead of using the systemobjdump
.Compared to other tools on this list,
objdump
packs a LOT of functionality; it can show information about sections, relocations and more. It also supports many flags to format and filter the output. -
Linker information (symbol table, sections, binding):
nm
: Display symbol tables. Some examples of usingnm
are documented in the previous subsection.size
: Get high-level information about sections in a binary, such as the sizes of sections and where they are located.dyldinfo
: Display information used by dyld, such as which dylibs an image depends on.install_name_tool
: Change the name for a dynamic shared library, and query or modify the runpath search paths (aka 'rpaths') it uses.
-
Multi-architecture binaries:
lipo
: A tool that can be used to create, inspect and dissect universal binaries.- Potential use cases: If you have a universal binary on an
Apple Silicon Mac, but want to quickly test if the issue would reproduce
on
x86_64
, you can extract thex86_64
slice by usinglipo
. Thex86_64
binary will automatically run under Rosetta 2.
- Potential use cases: If you have a universal binary on an
Apple Silicon Mac, but want to quickly test if the issue would reproduce
on
If a compiled executable is crashing when built with optimizations, but not crashing when built with -Onone, it's most likely one of the SIL optimizations which causes the miscompile.
Currently there is no tool to automatically identify the bad optimization, but it's quite easy to do this manually:
-
Add the compiler option
-Xllvm -sil-opt-pass-count=<n>
, where<n>
is the number of optimizations to run. -
Bisect: find n where the executable crashes, but does not crash with n-1. First just try n = 10, 100, 1000, 10000, etc. to find an upper bound). Then can either bisect the invocation by hand or place the invocation into a script and use
./llvm-project/llvm/utils/bisect
to automatically bisect based on the scripts error code. Example invocation:bisect --start=0 --end=10000 ./invoke_swift_passing_N.sh "%(count)s"
-
Add another option
-Xllvm -sil-print-last
. The output can be large, so it's best to redirect stderr to a file (2> output
). The output contains the SIL before and after the bad optimization. -
Copy the two functions from the output into separate files and compare both files. Try to figure out what the optimization pass did wrong. To simplify the comparison, it's sometimes helpful to replace all SIL values (e.g.
%27
) with a constant string (e.g.%x
). -
If the bad optimization is SILCombine or SimplifyCFG (which do a lot of transformations in a single run) it's helpful to continue bisecting on the sub-pass number. The option
-Xllvm -sil-opt-pass-count=<n>.<m>
can be used for that, wherem
is the sub-pass number.
For bisecting pass counts in large projects, the pass counts can be read from
a configuration file using the -Xllvm -sil-pass-count-config-file=<file>
option. For details see the comment for SILPassCountConfigFile
in the pass
manager sources.
git-bisect
is a useful tool for finding where a regression was
introduced. Sadly git-bisect
does not handle long lived branches
and will in fact choose commits from upstream branches that may be
missing important content from the downstream branch. As an example,
consider a situation where one has the following straw man commit flow
graph:
github/main -> github/tensorflow
In this case if one attempts to use git-bisect
on
github/tensorflow, git-bisect
will sometimes choose commits from
github/main resulting in one being unable to compile/test specific
tensorflow code that has not been upstreamed yet. Even worse, what if
we are trying to bisect in between two that were branched from
github/tensorflow and have had subsequent commits cherry-picked on
top. Without any loss of generality, lets call those two tags
tag-tensorflow-bad
and tag-tensorflow-good
. Since both of
these tags have had commits cherry-picked on top, they are technically
not even on the github/tensorflow branch, but rather in a certain
sense are a tag of a feature branch from main/tensorflow. So,
git-bisect
doesn't even have a clear history to bisect on in
multiple ways.
With those constraints in mind, we can bisect! We just need to be
careful how we do it. Lets assume that we have a test script called
test.sh
that indicates error by the error code. With that in hand,
we need to compute the least common ancestor of the good/bad
commits. This is traditionally called the "merge base" of the
commits. We can compute this as so:
TAG_MERGE_BASE=$(git merge-base tags/tag-tensorflow-bad tags/tag-tensorflow-good)
Given that both tags were taken from the feature branch, the reader
can prove to themselves that this commit is guaranteed to be on
github/tensorflow
and not github/main
since all commits from
github/main
are forwarded using git merges.
Then lets assume that we checked out $TAG_MERGE_BASE
and then ran
test.sh
and did not hit any error. Ok, we can not bisect. Sadly,
as mentioned above if we run git-bisect in between $TAG_MERGE_BASE
and tags/tag-tensorflow-bad
, git-bisect
will sometimes choose
commits from github/main
which would cause test.sh
to fail
if we are testing tensorflow specific code! To work around this
problem, we need to start our bisect and then tell git-bisect
to
ignore those commits by using the skip sub command:
git bisect start tags/tag-tensorflow-bad $TAG_MERGE_BASE
for rev in $(git rev-list $TAG_MERGE_BASE..tags/tag-tensorflow-bad --merges --first-parent); do
git rev-list $rev^2 --not $rev^
done | xargs git bisect skip
Once this has been done, one uses git-bisect
normally. One thing
to be aware of is that git-bisect
will return a good/bad commits
on the feature branch and if one of those commits is a merge from the
upstream branch, one will need to analyze the range of commits from
upstream for the bad commit afterwards. The commit range in the merge
should be relatively small though compared with the large git history
one just bisected.
There is functionality provided in ./swift/utils/bug_reducer/bug_reducer.py for reducing SIL test cases by:
- Producing intermediate sib files that only require some of the passes to trigger the crasher.
- Reducing the size of the sil test case by extracting functions or partitioning a module into unoptimized and optimized modules.
For more information and a high level example, see: ./swift/utils/bug_reducer/README.md.
When bisecting it might be necessary to run the update-checkout
script
each time you change shas. To do this you can pass --match-timestamp
to automatically checkout match the timestamp of the apple/swift
repo
across the other repos.
A "dry-run" invocation of the build-script
(using the --dry-run
flag) will
print the commands that would be executed in a given build, without executing
them. A dry-run script invocation output can be used to inspect the build stages
of a given build-script
configuration, or create script corresponding to one
such configuration.
The Swift compiler uses a standalone compiler-driver application written in
Swift: swift-driver. When building the
compiler using build-script
, by default, the standalone driver will be built
first, using the host toolchain, if the host toolchain contains a Swift
compiler. If the host toolchain does not contain Swift, a warning is emitted and
the legacy compiler-driver (integrated in the C++ code-base) will be used. In
the future, a host toolchain containing a Swift compiler may become mandatory.
Once the compiler is built, the compiler build directory (swift-<OS>-<ARCH>
)
is updated with a symlink to the standalone driver, ensuring calls to the build
directory's swift
and swiftc
always forward to the standalone driver.
For more information about the driver, see: github.com/apple/swift-driver/blob/main/README.md
What's the difference between invoking 'swiftc' vs. 'swift-driver' at the top level?
Today, swift
and swiftc
are symbolic links to the compiler binary
(swift-frontend
). Invoking swiftc
causes the executable to detects that it
is a compiler-driver invocation, and not a direct compiler-frontend invocation,
by examining the invoked program's name. The compiler frontend can be invoked
directly by invoking the swift-frontend
executable, or passing in the
-frontend
option to swiftc
.
The standalone Compiler Driver is
installed as a separate swift-driver
executable in the Swift toolchain's bin
directory. When a user launches the compiler by invoking swiftc
, the C++ based
compiler executable forwards the invocation to the swift-driver
executable if
one is found alongside it. This forwarding mechanism is in-place temporarily, to
allow for an easy fallback to the legacy driver via one of the two escape
hatches:
-disallow-use-new-driver
command line flagSWIFT_USE_OLD_DRIVER
environment variable
If the user is to directly invoke the swift-driver
executable, the behaviour
should be the same as invoking the swiftc
executable, but without the option
for a legacy driver fallback.
Once the legacy driver is deprecated, swift
and swiftc
executables will
become symbolic links to the swift-driver
executable directly.
Will 'swiftc ... -###' always print the same set of commands for the old/new driver? Do they call 'swift-frontend' the same way?
The standalone Compiler Driver is meant
to be a direct drop-in replacement for the C++-based legacy driver. It has the
exact same command-line interface. The expectation is that its behaviour closely
matches the legacy driver; however, during, and after the transition to the new
driver being the default its behaviour may start to diverge from the legacy
driver as par for the course of its evolution and gaining new features, etc.
Today, broadly-speaking, sets of swift-frontend
invocations generated by the
two drivers are expected to be very similar.
One can build the compiler that does not rely on the standalone driver and
instead uses the legacy, built-in driver using the build-script
option:
--skip-early-swift-driver
.
The Swift compiler can currently be invoked in an execution mode that will use the legacy C++-based compiler driver using one of the following two options:
- Passing
-disallow-use-new-driver
argument to theswiftc
invocation - Setting the
SWIFT_USE_OLD_DRIVER
environment variable
A "dry-run" invocation of the build-script
can be used to
examine the SwiftDriver build stage and commands, without executing it. For
example:
$ utils/build-script --release-debuginfo --dry-run
+ mkdir -p /SwiftWorkspace/build/Ninja-RelWithDebInfoAssert
--- Building earlyswiftdriver ---
+ /SwiftWorkspace/swift-driver/Utilities/build-script-helper.py build --package-path /SwiftWorkspace/swift-driver --build-path /SwiftWorkspace/build/Ninja-RelWithDebInfoAssert/earlyswiftdriver-macosx-x86_64 --configuration release --toolchain /Applications/Xcode.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr --ninja-bin /Applications/Xcode.app/Contents/Developer/usr/local/bin/ninja --cmake-bin /Applications/Xcode.app/Contents/Developer/usr/local/bin/cmake --local_compiler_build
Building the standard library for: swift-test-stdlib-macosx-x86_64
...
One of the first steps is an invocation of the driver's
build-script-helper.py
script which specifies that the driver us to be built
(build
) using the host toolchain (--toolchain
) to a specified location
(--build-path
).
In order to create a Swift compiler installation (--install-swift
), the
standalone driver must be built as a separate build product using the
just-built Swift compiler and toolchain (the ones built in the same
build-script
invocation, preceding the SwiftDriver build product). The
additional build product is added to the build by specifying the
--swift-driver
option of the build-script
. The driver product is installed
into the resulting toolchain installation by specifying the
--install-swift-driver
option of the build-script
.
Note, a "dry-run" build-script
invocation when installing the standalone
driver will demonstrate the commands required to build and install the driver as
a standalone build product:
$ utils/build-script --release-debuginfo --dry-run --swift-driver --install-swift-driver
...
--- Cleaning swiftdriver ---
+ /SwiftWorkspace/swift-driver/Utilities/build-script-helper.py clean --package-path /SwiftWorkspace/swift-driver --build-path /SwiftWorkspace/build/Ninja-RelWithDebInfoAssert/swiftdriver-macosx-x86_64 --configuration release --toolchain /SwiftWorkspace/build/Ninja-RelWithDebInfoAssert/toolchain-macosx-x86_64/Applications/Xcode.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr --ninja-bin /Applications/Xcode.app/Contents/Developer/usr/local/bin/ninja --cmake-bin /Applications/Xcode.app/Contents/Developer/usr/local/bin/cmake
--- Building swiftdriver ---
+ /SwiftWorkspace/swift-driver/Utilities/build-script-helper.py build --package-path /SwiftWorkspace/swift-driver --build-path /SwiftWorkspace/build/Ninja-RelWithDebInfoAssert/swiftdriver-macosx-x86_64 --configuration release --toolchain /SwiftWorkspace/build/Ninja-RelWithDebInfoAssert/toolchain-macosx-x86_64/Applications/Xcode.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr --ninja-bin /Applications/Xcode.app/Contents/Developer/usr/local/bin/ninja --cmake-bin /Applications/Xcode.app/Contents/Developer/usr/local/bin/cmake
--- Installing swiftdriver ---
+ /SwiftWorkspace/swift-driver/Utilities/build-script-helper.py install --package-path /SwiftWorkspace/swift-driver --build-path /SwiftWorkspace/build/Ninja-RelWithDebInfoAssert/swiftdriver-macosx-x
86_64 --configuration release --toolchain /SwiftWorkspace/build/Ninja-RelWithDebInfoAssert/toolchain-macosx-x86_64/Applications/Xcode.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr --ninja-bin /Applications/Xcode.app/Contents/Developer/usr/local/bin/ninja --cmake-bin /Applications/Xcode.app/Contents/Developer/usr/local/bin/cmake
These invocations of the driver's build-script-helper.py
script specify the
individual build actions (clean
, build
, install
), the product build path
(--build-path
), and the just-built toolchain which should be used
(--toolchain
).
One can use the previous tips for debugging the Swift compiler with Swift executables as well. Here are some additional useful techniques that one can use in Swift executables.
One problem that often comes up when debugging Swift code in LLDB is that LLDB shows the demangled name instead of the mangled name. This can lead to mistakes where due to the length of the mangled names one will look at the wrong function. Using the following command, one can find the mangled name of the function in the current frame:
(lldb) image lookup -va $pc
Address: CollectionType3[0x0000000100004db0] (CollectionType3.__TEXT.__text + 16000)
Summary: CollectionType3`ext.CollectionType3.CollectionType3.MutableCollectionType2<A where A: CollectionType3.MutableCollectionType2>.(subscript.materializeForSet : (Swift.Range<A.Index>) -> Swift.MutableSlice<A>).(closure #1)
Module: file = "/Volumes/Files/work/solon/build/build-swift/validation-test-macosx-x86_64/stdlib/Output/CollectionType.swift.gyb.tmp/CollectionType3", arch = "x86_64"
Symbol: id = {0x0000008c}, range = [0x0000000100004db0-0x00000001000056f0), name="ext.CollectionType3.CollectionType3.MutableCollectionType2<A where A: CollectionType3.MutableCollectionType2>.(subscript.materializeForSet : (Swift.Range<A.Index>) -> Swift.MutableSlice<A>).(closure #1)", mangled="_TFFeRq_15CollectionType322MutableCollectionType2_S_S0_m9subscriptFGVs5Rangeqq_s16MutableIndexable5Index_GVs12MutableSliceq__U_FTBpRBBRQPS0_MS4__T_"
One can perform manual symbolication of a crash log or an executable using LLDB without running the actual executable. For a detailed guide on how to do this, see: https://lldb.llvm.org/symbolication.html.
The malloc_history
tool (macOS only) shows the history of malloc
and free
calls for a particular pointer. To enable malloc_history, you must run the
target process with the environment variable MallocStackLogging=1. Then you can
see the allocation history of any pointer:
malloc_history YourProcessName 0x12345678
By default, this will show a compact call stack representation for each event that puts everything on a single line. For a more readable but larger representation, pass -callTree.
This works even when you have the process paused in the debugger!
The leaks
tool (macOS only) can do more than just find leaks. You can use its
pointer tracing engine to show you where a particular block is referenced:
leaks YourProcessName --trace=0x12345678
Like malloc_history, this works even when you're in the middle of debugging the process.
Sometimes you just want to know some basic info about the region of memory an
address is in. The memory region
lldb command will print out basic info about
the region containing a pointer, such as its permissions and whether it's stack,
heap, or a loaded image.
lldb comes with a heap script that offers powerful tools to search for pointers:
(lldb) p (id)[NSApplication sharedApplication]
(id) $0 = 0x00007fc50f904ba0
(lldb) script import lldb.macosx.heap
"crashlog" and "save_crashlog" command installed, use the "--help" option for detailed help
"malloc_info", "ptr_refs", "cstr_refs", "find_variable", and "objc_refs" commands have been installed, use the "--help" options on these commands for detailed help.
(lldb) ptr_refs 0x00007fc50f904ba0
0x0000600003a49580: malloc( 48) -> 0x600003a49560 + 32
0x0000600003a6cfe0: malloc( 48) -> 0x600003a6cfc0 + 32
0x0000600001f80190: malloc( 112) -> 0x600001f80150 + 64 NSMenuItem55 bytes after NSMenuItem
0x0000600001f80270: malloc( 112) -> 0x600001f80230 + 64 NSMenuItem55 bytes after NSMenuItem
0x0000600001f80350: malloc( 112) -> 0x600001f80310 + 64 NSMenuItem55 bytes after NSMenuItem
...
lldb's x
command is cryptic but extremely useful for printing out memory
contents. Example:
(lldb) x/5a `(Class)objc_getClass("NSString")`
0x7fff83f6d660: 0x00007fff83f709f0 (void *)0x00007fff8c6550f0: NSObject
0x7fff83f6d668: 0x00007fff8c655118 (void *)0x00007fff8c6550f0: NSObject
0x7fff83f6d670: 0x000060000089c500 -> 0x00007fff2d49c550 "_getCString:maxLength:encoding:"
0x7fff83f6d678: 0x000580100000000f
0x7fff83f6d680: 0x000060000348e784
Let's unpack the command a bit. The 5
says that we want to print five entries.
a
means to print them as addresses, which gives you some automatic symbol
lookups and pointer chasing as we see here. Finally, we give it the address. The
backticks around the expression tells it to evaluate that expression and use the
result as the address. Another example:
(lldb) x/10xb 0x000060000089c500
0x60000089c500: 0x50 0xc5 0x49 0x2d 0xff 0x7f 0x00 0x00
0x60000089c508: 0x77 0x63
Here, x
means to print the values as hex, and b
means to print byte by byte.
The following specifiers are available:
- o - octal
- x - hexadecimal
- d - decimal
- u - unsigned decimal
- t - binary
- f - floating point
- a - address
- c - char
- s - string
- i - instruction
- b - byte
- h - halfword (16-bit value)
- w - word (32-bit value)
- g - giant word (64-bit value)
When debugging programs on Windows, sometimes one will run into an error message with a mysterious error code. E.x.:
note: command had no output on stdout or stderr
error: command failed with exit status: 0xc0000135
These on windows are called HRESULT values. In the case above, the HRESULT is telling me that a DLL was not found. I discovered this by running the Microsoft provided System Error Code Lookup Tool. After running this tool with the relevant error code on a windows machine, I got back the following result:
# for hex 0xc0000135 / decimal -1073741515
STATUS_DLL_NOT_FOUND ntstatus.h
# The code execution cannot proceed because %hs was not
# found. Reinstalling the program may fix this problem.
# as an HRESULT: Severity: FAILURE (1), FACILITY_NULL (0x0), Code 0x135
# for hex 0x135 / decimal 309
ERROR_NOTIFICATION_GUID_ALREADY_DEFINED winerror.h
# The specified file already has a notification GUID
# associated with it.
Some relevant Microsoft documentation:
- https://learn.microsoft.com/en-us/windows/win32/seccrypto/common-hresult-values
- https://learn.microsoft.com/en-us/openspecs/windows_protocols/ms-erref/0642cb2f-2075-4469-918c-4441e69c548a
- https://learn.microsoft.com/en-us/windows/win32/debug/system-error-codes--0-499-
Sometimes one needs to be able to while debugging actually debug LLDB and its interaction with Swift itself. Some examples of problems where this can come up are:
- Compiler bugs when LLDB attempts to evaluate an expression. (expression debugging)
- Swift variables being shown with no types. (type debugging)
To gain further insight into these sorts of failures, we use LLDB log categories. LLDB log categories provide introspection by causing LLDB to dump verbose information relevant to the category into the log as it works. The two log channels that are useful for debugging Swift issues are the "types" and "expression" log channels.
For more details about any of the information below, please run:
(lldb) help log enable
The "types" log reports on LLDB's process of constructing SwiftASTContexts and errors that may occur. The two main tasks here are:
-
Constructing the SwiftASTContext for a specific single Swift module. This is used to implement frame local variable dumping via the lldb
frame variable
command, as well as the Xcode locals view. On failure, local variables will not have types. -
Building a SwiftASTContext in which to run Swift expressions using the "expression" command. Upon failure, one will see an error like: "Shared Swift state for has developed fatal errors and is being discarded."
These errors can be debugged by turning on the types log:
(lldb) log enable -f /tmp/lldb-types-log.txt lldb types
That will write the types log to the file passed to the -f option.
NOTE Module loading can happen as a side-effect of other operations in lldb (e.g. the "file" command). To be sure that one has enabled logging before /any/ module loading has occurred, place the command into either:
~/.lldbinit
$PWD/.lldbinit
This will ensure that the type import command is run before /any/ modules are imported.
The "expression" log reports on the process of wrapping, parsing, SILGen'ing, JITing, and inserting an expression into the current Swift module. Since this can only be triggered by the user manually evaluating expression, this can be turned on at any point before evaluating an expression. To enable expression logging, first run:
(lldb) log enable -f /tmp/lldb-expr-log.txt lldb expression
and then evaluate the expression. The expression log dumps, in order, the following non-exhaustive list of state:
- The unparsed, textual expression passed to the compiler.
- The parsed expression.
- The initial SILGen.
- SILGen after SILLinking has occurred.
- SILGen after SILLinking and Guaranteed Optimizations have occurred.
- The resulting LLVM IR.
- The assembly code that will be used by the JIT.
NOTE LLDB runs a handful of preparatory expressions that it uses to set up for running Swift expressions. These can make the expression logs hard to read especially if one evaluates multiple expressions with the logging enabled. In such a situation, run all expressions before the bad expression, turn on the logging, and only then run the bad expression.
Note, you can also turn on more than one log at a time as well, e.x.:
(lldb) log enable -f /tmp/lldb-types-log.txt lldb types expression
Recent versions of LLVM package the tool clang-tidy
. This can be used in
combination with a json compilation database to run static analyzer checks as
well as cleanups/modernizations on a code-base. Swift's cmake invocation by
default creates one of these json databases at the root path of the swift host
build, for example on macOS:
$PATH_TO_BUILD/swift-macosx-$(uname -m)/compile_commands.json
Using this file, one invokes clang-tidy
on a specific file in the codebase
as follows:
clang-tidy -p=$PATH_TO_BUILD/swift-macosx-$(uname -m)/compile_commands.json $FULL_PATH_TO_FILE
One can also use shell regex to visit multiple files in the same directory. Example:
clang-tidy -p=$PATH_TO_BUILD/swift-macosx-$(uname -m)/compile_commands.json $FULL_PATH_TO_DIR/*.cpp