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
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.
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Cited by top-tier papers3
- IncIDFA: An Efficient and Generic Algorithm for Incremental Iterative Dataflow AnalysisAman Nougrahiya, V. Krishna NandivadaOOPSLA 2025 · 4 citations
- Diatom: Polylithic Binary Lifting with Data-Flow Summaries and Type-Aware IR LinkingAnshunkang Zhou, Charles ZhangOOPSLA 2026 · 1 citation
- Urbanite: A Dataflow-Based Framework for Human-AI Interactive Alignment in Urban Visual AnalyticsGustavo Moreira, Leonardo Ferreira, Carolina Veiga, Maryam Hosseini et al.IEEE VIS 2025 · 1 citation
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