[clangd] Check if macro is already in the IdentifierTable before loading it

Having nested macros in the C code could cause clangd to fail an assert in clang::Preprocessor::setLoadedMacroDirective() and crash.

 #1 0x00000000007ace30 PrintStackTraceSignalHandler(void*) /qdelacru/llvm-project/llvm/lib/Support/Unix/Signals.inc:632:1
 #2 0x00000000007aaded llvm::sys::RunSignalHandlers() /qdelacru/llvm-project/llvm/lib/Support/Signals.cpp:76:20
 #3 0x00000000007ac7c1 SignalHandler(int) /qdelacru/llvm-project/llvm/lib/Support/Unix/Signals.inc:407:1
 #4 0x00007f096604db20 __restore_rt (/lib64/libpthread.so.0+0x12b20)
 #5 0x00007f0964b307ff raise (/lib64/libc.so.6+0x377ff)
 #6 0x00007f0964b1ac35 abort (/lib64/libc.so.6+0x21c35)
 #7 0x00007f0964b1ab09 _nl_load_domain.cold.0 (/lib64/libc.so.6+0x21b09)
 #8 0x00007f0964b28de6 (/lib64/libc.so.6+0x2fde6)
 #9 0x0000000001004d1a clang::Preprocessor::setLoadedMacroDirective(clang::IdentifierInfo*, clang::MacroDirective*, clang::MacroDirective*) /qdelacru/llvm-project/clang/lib/Lex/PPMacroExpansion.cpp:116:5

An example of the code that causes the assert failure:
```
...
```

During code completion in clangd, the macros will be loaded in loadMainFilePreambleMacros() by iterating over the macro names and calling PreambleIdentifiers->get(). Since these macro names are store in a StringSet (has StringMap underlying container), the order of the iterator is not guaranteed to be same as the order seen in the source code.

When clangd is trying to resolve nested macros it sometimes attempts to load them out of order which causes a macro to be stored twice. In the example above, ECHO2 macro gets resolved first, but since it uses another macro that has not been resolved it will try to resolve/store that as well. Now there are two MacroDirectives stored in the Preprocessor, ECHO and ECHO2. When clangd tries to load the next macro, ECHO, the preprocessor fails an assert in clang::Preprocessor::setLoadedMacroDirective() because there is already a MacroDirective stored for that macro name.

In this diff, I check if the macro is already inside the IdentifierTable and if it is skip it so that it is not resolved twice.

Reviewed By: kadircet

Differential Revision: https://reviews.llvm.org/D101870
2 files changed
tree: d335b30cdf1e98413d53a7ccd115db2feaad44ae
  1. .github/
  2. clang/
  3. clang-tools-extra/
  4. compiler-rt/
  5. debuginfo-tests/
  6. flang/
  7. libc/
  8. libclc/
  9. libcxx/
  10. libcxxabi/
  11. libunwind/
  12. lld/
  13. lldb/
  14. llvm/
  15. mlir/
  16. openmp/
  17. parallel-libs/
  18. polly/
  19. pstl/
  20. runtimes/
  21. utils/
  22. .arcconfig
  23. .arclint
  24. .clang-format
  25. .clang-tidy
  26. .git-blame-ignore-revs
  27. .gitignore
  28. CONTRIBUTING.md
  29. README.md
README.md

The LLVM Compiler Infrastructure

This directory and its sub-directories contain source code for LLVM, a toolkit for the construction of highly optimized compilers, optimizers, and run-time environments.

The README briefly describes how to get started with building LLVM. For more information on how to contribute to the LLVM project, please take a look at the Contributing to LLVM guide.

Getting Started with the LLVM System

Taken from https://llvm.org/docs/GettingStarted.html.

Overview

Welcome to the LLVM project!

The LLVM project has multiple components. The core of the project is itself called “LLVM”. This contains all of the tools, libraries, and header files needed to process intermediate representations and converts it into object files. Tools include an assembler, disassembler, bitcode analyzer, and bitcode optimizer. It also contains basic regression tests.

C-like languages use the Clang front end. This component compiles C, C++, Objective-C, and Objective-C++ code into LLVM bitcode -- and from there into object files, using LLVM.

Other components include: the libc++ C++ standard library, the LLD linker, and more.

Getting the Source Code and Building LLVM

The LLVM Getting Started documentation may be out of date. The Clang Getting Started page might have more accurate information.

This is an example work-flow and configuration to get and build the LLVM source:

  1. Checkout LLVM (including related sub-projects like Clang):

    • git clone https://github.com/llvm/llvm-project.git

    • Or, on windows, git clone --config core.autocrlf=false https://github.com/llvm/llvm-project.git

  2. Configure and build LLVM and Clang:

    • cd llvm-project

    • cmake -S llvm -B build -G <generator> [options]

      Some common build system generators are:

      • Ninja --- for generating Ninja build files. Most llvm developers use Ninja.
      • Unix Makefiles --- for generating make-compatible parallel makefiles.
      • Visual Studio --- for generating Visual Studio projects and solutions.
      • Xcode --- for generating Xcode projects.

      Some Common options:

      • -DLLVM_ENABLE_PROJECTS='...' --- semicolon-separated list of the LLVM sub-projects you'd like to additionally build. Can include any of: clang, clang-tools-extra, libcxx, libcxxabi, libunwind, lldb, compiler-rt, lld, polly, or debuginfo-tests.

        For example, to build LLVM, Clang, libcxx, and libcxxabi, use -DLLVM_ENABLE_PROJECTS="clang;libcxx;libcxxabi".

      • -DCMAKE_INSTALL_PREFIX=directory --- Specify for directory the full path name of where you want the LLVM tools and libraries to be installed (default /usr/local).

      • -DCMAKE_BUILD_TYPE=type --- Valid options for type are Debug, Release, RelWithDebInfo, and MinSizeRel. Default is Debug.

      • -DLLVM_ENABLE_ASSERTIONS=On --- Compile with assertion checks enabled (default is Yes for Debug builds, No for all other build types).

    • cmake --build build [-- [options] <target>] or your build system specified above directly.

      • The default target (i.e. ninja or make) will build all of LLVM.

      • The check-all target (i.e. ninja check-all) will run the regression tests to ensure everything is in working order.

      • CMake will generate targets for each tool and library, and most LLVM sub-projects generate their own check-<project> target.

      • Running a serial build will be slow. To improve speed, try running a parallel build. That's done by default in Ninja; for make, use the option -j NNN, where NNN is the number of parallel jobs, e.g. the number of CPUs you have.

    • For more information see CMake

Consult the Getting Started with LLVM page for detailed information on configuring and compiling LLVM. You can visit Directory Layout to learn about the layout of the source code tree.