Psyche is a compiler frontend for the C programming language. Psyche-C is specifically designed for the implementation of static analysis tools. These are the distinct features that make Psyche-C rather unique:

• Clean separation between the syntactic and semantic compiler phases.
• Both algorithmic- and heuristic-based syntax disambiguation strategies.
• Independent of #include, with type inference for missing struct, union, enum, and typedef.
• API inspired by that of the Roslyn .NET compiler.
• A parser's AST resembling that of the LLVM's Clang frontend.

Applications:

• Enabling, on incomplete source-code, static analysis techniques that require fully-typed programs.
• Compiling partial code (e.g., a snippet retrieved from a bug tracker) for object-code inspection.
• Generating test-input data for a function in isolation (without its dependencies).
• Quick prototyping of an algorithm, without the need of explicit types.

NOTE: The master branch is going through a major overhaul; it's expected that syntax analysis (parsing and AST construction) already is functional, though. The original version of Psyche-C is available in this branch.

While Psyche-C is primarily used as a library for the implementation of static analysis tools, it still is a compiler frontend, and may also be used as an ordinary C parser through the cnippet driver adaptor.

// node.c
void f()
{
    T v = 0;
    v->value = 42;
    v->next = v;
}

If you compile the above snippet with GCC or Clang, you'd see the diagnostic "declaration forTis not available". But with cnippet the compilation would succeed: a definition for T is inferred.

• The Doxygen-generated API.
• HOW-TO blog posts:
  • Dumping a C program’s AST with Psyche-C
    Visualizando a AST de um programa C com o Psyche-C
• An online interface that offers a glimpse of Psyche-C's functionality.
• Articles:
  • Programming in C with type inference
    Programando em C com inferência de tipos usando PsycheC.

Except for type inference, which is written in Haskell, Psyche-C is written in C++17; cnippet is written in Python 3.

To build:

cmake CMakeLists.txt && make -j 4

To run the tests:

./test-suite

• Type Inference for C: Applications to the Static Analysis of Incomplete Programs
  ACM Transactions on Programming Languages and Systems — TOPLAS, Volume 42, Issue 3, Artible No. 15, Dec. 2020.

• Inference of static semantics for incomplete C programs
  Proceedings of the ACM on Programming Languages, Volume 2, Issue POPL, Jan. 2018, Article No. 29.

• AnghaBench: a Suite with One Million Compilable C Benchmarks for Code-Size Reduction
  Proceedings of the IEEE/ACM International Symposium on Code Generation and Optimization — CGO, 2021.

• Generation of in-bounds inputs for arrays in memory-unsafe languages
  Proceedings of the IEEE/ACM International Symposium on Code Generation and Optimization — CGO, Feb. 2019, p. 136-148.

• Automatic annotation of tasks in structured code
  Proceedings of the International Conference on Parallel Architectures and Compilation Techniques — PACT, Nov. 2018, Article No. 31.

• Synthesis of Benchmarks for the C Programming Language by Mining Software Repositories
  Proceedings of the Simpósio Brasileiro de Linguagens de Programacao — SBLP, Sep. 2019.