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When Dataflow Analysis Meets Large Language Models
Feb. 19, 2024, 5:42 a.m. | Chengpeng Wang, Wuqi Zhang, Zian Su, Xiangzhe Xu, Xiaoheng Xie, Xiangyu Zhang
cs.LG updates on arXiv.org arxiv.org
Abstract: Dataflow analysis is a powerful code analysis technique that reasons dependencies between program values, offering support for code optimization, program comprehension, and bug detection. Existing approaches require the successful compilation of the subject program and customizations for downstream applications. This paper introduces LLMDFA, an LLM-powered dataflow analysis framework that analyzes arbitrary code snippets without requiring a compilation infrastructure and automatically synthesizes downstream applications. Inspired by summary-based dataflow analysis, LLMDFA decomposes the problem into three sub-problems, …
abstract analysis applications arxiv code code analysis compilation cs.lg cs.pl cs.se dataflow dependencies detection framework language language models large language large language models llm optimization paper support type values
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