Dynamic program analyses are essential to creating safe, reliable, and productive computing environments. However, these analyses are challenging and time-consuming to construct due to the low-level optimization required to achieve acceptable performance. Consequently, many analyses are often never realized, or have inefficient implementations. In this work we argue that many analyses can and should be constructed with a high-level description language, leaving the burden of low-level optimizations to the analysis instrumentation system itself. We propose a novel language for dynamic analysis called ALDA. ALDA leverages common structuring of dynamic analyses to provide a simple and high-level description for dynamic analyses. Through restricting the supported behaviors to only essential operations in dynamic analyses, an optimizing compiler for ALDA can create analysis implementations with performance on-par to hand-tuned analyses. To demonstrate ALDA’s universality and efficiency, we create an optimizing compiler for ALDA targeting the LLVM instrumentation framework named ALDAcc. We use ALDAcc to construct 8 different dynamic analysis algorithms, including the popular MemorySanitizer analysis, and show their construction is succinct and simple. By comparing two of them (Eraser and MemorySanitizer) with their hand-tuned implementations, we show that ALDAcc’s optimized analyses are comparable to hand-tuned implementations.

@inproceedings{ChengD22,
  title = {Creating concise and efficient dynamic analyses with ALDA},
  author = {Xiang Cheng and David Devecsery},
  booktitle = {ASPLOS},
  year = {2022},
  doi = {10.1145/3503222.3507760}
}