BigDataflow: A Distributed Interprocedural Dataflow Analysis Framework
Abstract
Abstract: 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.
BibTeX
@inproceedings{Sun-al:FSE23,
author = {Zewen Sun and
Duanchen Xu and
Yiyu Zhang and
Yun Qi and
Yueyang Wang and
Zhiqiang Zuo and
Zhaokang Wang and
Yue Li and
Xuandong Li and
Qingda Lu and
Wenwen Peng and
Shengjian Guo},
title = {{BigDataflow:} A Distributed Interprocedural Dataflow Analysis Framework},
booktitle = {{ESEC/SIGSOFT} {FSE}},
pages = {1431--1443},
publisher = {{ACM}},
year = {2023},
}