Handling of Call Frame Information (stack frame info).

The root type exposed by this crate is CfiCache, which offers a high-level API to extract CFI from object files and serialize a format that the Breakpad processor can understand.

Background

Call Frame Information (CFI) is used by the processor to improve the quality of stacktraces during stackwalking. When the executable was compiled with frame pointer omission, the call stack does not contain sufficient information to resolve frames on its own. CFI contains programs that can calculate the base address of a frame based on register values of the current frame.

Without CFI, the stackwalker needs to scan the stack memory for values that look like valid base addresses. This frequently yields false-positives.

Symbolic

Symbolic is a library written in Rust which is used at Sentry to implement symbolication of native stack traces, sourcemap handling for minified JavaScript and more. It consists of multiple largely independent crates which are bundled together into a C and Python library so it can be used independently of Rust.

What's in the package

Symbolic provides the following functionality:

• Symbolication based on custom cache files (symcache)
• Symbol cache file generators from:
  • Mach, ELF and PE symbol tables
  • Mach, ELF and PE embedded DWARF data
  • PDB CodeView debug information
  • .NET Portable PDB
  • Breakpad symbol files
  • Unity IL2CPP
• Demangling support
  • C++ (GCC, clang and MSVC)
  • Objective C / Objective C++
  • Rust
  • Swift
• JavaScript sourcemap expansion
  • Basic token mapping
  • Heuristics to find original function names based on minified sources
  • Indexed sourcemap to sourcemap merging
• Proguard function mappings
• Generate Breakpad symbol files from Mach, ELF and PDBs
• Convenient C and Python library
• Processing of Unreal Engine 4 native crash reports
  • Extract and process minidumps
  • Expose logs and UE4 context information

Rust Usage

The Rust crates are published to Crates.io and documentation is available on docs.rs.

Python Usage

Symbolic is hosted on PyPI. It comes as a library with prebuilt wheels for linux and macOS. On other operating systems or when using as rust library, you need to build symbolic manually. It should be compatible with both Python 2 and Python 3.

The python library ships all of the above features in a flat module:

from symbolic import Archive

fat = Archive.open('/path/to/object')
obj = fat.get_object(arch = 'x86_64')
print 'object debug id: {}' % obj.debug_id

C Bindings

Symbolic also offers C bindings, which allow for FFI into arbitrary languages. Have a look at the the Symbolic C-ABI readme for more information.

Source Crates

A lot of functionality exposed by this library come from independent Rust crates for better use:

• sourcemap
• proguard
• gimli
• goblin
• pdb

Building and Development

To build the Rust crate, we require the latest stable Rust, as well as a C++11 compiler. The crate is split into a workspace with multiple features, so when running building or running tests always make sure to pass the --all and --all-features flags.

# Check whether the crate compiles
cargo check --all --all-features

# Run Rust tests
cargo test --all --all-features

We use rustfmt and clippy from the latest stable channel for code formatting and linting. To make sure that these tools are set up correctly and running with the right configuration, use the following make targets:

# Format the entire codebase
make format

# Run clippy on the entire codebase
make lint

Most likely, new functionality also needs to be added to the Python package. This first requires to expose new functions in the C ABI. For this, refer to the Symbolic C-ABI readme.

We highly recommend to develop and test the python package in a virtual environment. Once the ABI has been updated and tested, ensure the virtualenv is active and install the package, which builds the native library. There are two ways to install this:

# Install the release build, recommended:
pip install --editable ./py

# Install the debug build, faster installation but much slower runtime:
SYMBOLIC_DEBUG=1 pip install --editable ./py

For testing, we use ubiquitous pytest. Again, ensure that your virtualenv is active and the latest version of the native library has been installed. Then, run:

# Run tests manually
pytest ./py/tests

# Creates a new virtualenv, installs the release build and runs tests:
make pytest

Examples

The repository contains a few examples that show how to use symbolic to work with debug files and minidumps. Most of these examples can also be used to extract information from such files or verify their integrity:

• dump_cfi: Writes call frame information from an object file to standard out. The output format is Breakpad's STACK records.

• dump_sources: Creates a source archive from all files referenced by an object file. This is now integrated into sentry-cli difutil bundle-sources.

• minidump_stackwalk: Extracts stack traces from a minidump and symbolicates them. A path to a directory containing debug information files can be specified.

• object_debug: Prints basic information about the contents of an object file.

• sourcemapcache_debug: Converts a minified JavaScript file and its corresponding SourceMap into a sourcemapcache and resolves given line/col location.

• symcache_debug: Converts an object file into a symcache and prints its contents. Optionally, this can be used to symbolicate a relative address.

• unreal_engine_crash: Lists files contained within an Unreal Engine 4 crash archive.

To run these examples, use the run script. For example:

./run minidump_stackwalk mini.dmp /path/to/files

Supported Rust Versions

Symbolic tries to not break MSRV compatibility but makes no guarantees about the Rust version. Although you can expect Rust version compatibility of at least 6 months.

The current MSRV is 1.73.

License

Symbolic is licensed under the MIT license. It uses some Apache2 licensed code from Apple for the Swift demangling.