Compilers are part of the foundation upon which software systems are built; they need to be as correct as possible. This paper is about stress-testing loop optimizers; it presents a major reimplementation of Yet Another Random Program Generator (YARPGen), an open-source generative compiler fuzzer. This new version has found 122 bugs, both in compilers for data-parallel languages, such as the Intel® Implicit SPMD Program Compiler and the Intel® oneAPI DPC++ compiler, and in C++ compilers such as GCC and Clang/LLVM. The first main contribution of our work is a novel method for statically avoiding undefined behavior when generating loops; the resulting programs conform to the relevant language standard, enabling automated testing. The second main contribution is a collection of mechanisms for increasing the diversity of generated loop code; in our evaluation, we demonstrate that these make it possible to trigger loop optimizations significantly more often, providing opportunities to discover bugs in the optimizers.

@article{paperbot1994,
  title = {Fuzzing Loop Optimizations in Compilers for C++ and Data-Parallel Languages},
  author = {Vsevolod Livinskii and Dmitry Babokin and John Regehr},
  journal = {Proceedings of the ACM on Programming Languages},
  volume = {7},
  number = {PLDI},
  year = {2023},
  doi = {10.1145/3591295}
}