BigDataflow: A Distributed Interprocedural Dataflow Analysis Framework

Zewen Sun, Duanchen Xu,Yiyu Zhang, Yun Qi, Yueyang Wang,Zhiqiang Zuo,Zhaokang Wang,Yue Li,Xuandong Li,Qingda Lu, Wenwen Peng,Shengjian Guo

PROCEEDINGS OF THE 31ST ACM JOINT MEETING EUROPEAN SOFTWARE ENGINEERING CONFERENCE AND SYMPOSIUM ON THE FOUNDATIONS OF SOFTWARE ENGINEERING, ESEC/FSE 2023(2023)

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摘要
Apart from forming the backbone of compiler optimization, static dataflow analysis has been widely applied in a vast variety of applications, such as bug detection, privacy analysis, program comprehension, etc. Despite its importance, performing interprocedural dataflow analysis on large-scale programs is well known to be challenging. In this paper, we propose a novel distributed analysis framework supporting the general interprocedural dataflow analysis. Inspired by large-scale graph processing, we devise a dedicated distributed worklist algorithm tailored for interprocedural dataflow analysis. We implement the algorithm and develop a distributed framework called BigDataflow running on a large-scale cluster. The experimental results validate the promising performance of BigDataflow - it can finish analyzing the program of millions lines of code in minutes. Compared with the state-of-the-art, BigDataflow achieves much more analysis efficiency.
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关键词
interprocedural dataflow analysis,distributed computing
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