Fast Client-Driven CFL-Reachability via Regularization-Based Graph Simplification

Context-free language (CFL) reachability is a critical framework for various program analyses, widely adopted despite its computational challenges due to cubic or near-cubic time complexity. This often leads to significant performance degradation in client applications. Notably, in real-world scenarios, clients typically require reachability information only for specific source-to-sink pairs, offering opportunities for targeted optimization. We introduce MoYe, an effective regularization-based graph simplification technique designed to enhance the performance of client-driven CFL-reachability analyses by pruning non-contributing edges—those that do not participate in any specified CFL-reachable paths. MoYe employs a regular approximation to ensure exact reachability results for all designated node pairs and operates linearly with respect to the number of edges in the graph. This lightweight efficiency makes MoYe a valuable pre-processing step that substantially reduces both computational time and memory requirements for CFL-reachability analysis, outperforming a recent leading graph simplification approach. Our evaluations with two prominent CFL-reachability client applications demonstrate that MoYe can substantially improve performance and reduce resource consumption.

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Publication Details

Journal
Proceedings of the ACM on Programming Languages
Published
2025-10-09
DOI
https://doi.org/10.1145/3763065
Primary Topic
Software Testing and Debugging Techniques
Type
article
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article

Fast Client-Driven CFL-Reachability via Regularization-Based Graph Simplification

Jingling Xue, Haofeng Li, Jie Lu, Dongjie He et al.
Proceedings of the ACM on Programming Languages
Software Testing and Debugging Techniques
article

Fast Client-Driven CFL-Reachability via Regularization-Based Graph Simplification

Jingling Xue, Haofeng Li, Jie Lu, Dongjie He, Chenghang Shi, Lian Li
article en

Abstract

Context-free language (CFL) reachability is a critical framework for various program analyses, widely adopted despite its computational challenges due to cubic or near-cubic time complexity. This often leads to significant performance degradation in client applications. Notably, in real-world scenarios, clients typically require reachability information only for specific source-to-sink pairs, offering opportunities for targeted optimization. We introduce MoYe, an effective regularization-based graph simplification technique designed to enhance the performance of client-driven CFL-reachability analyses by pruning non-contributing edges—those that do not participate in any specified CFL-reachable paths. MoYe employs a regular approximation to ensure exact reachability results for all designated node pairs and operates linearly with respect to the number of edges in the graph. This lightweight efficiency makes MoYe a valuable pre-processing step that substantially reduces both computational time and memory requirements for CFL-reachability analysis, outperforming a recent leading graph simplification approach. Our evaluations with two prominent CFL-reachability client applications demonstrate that MoYe can substantially improve performance and reduce resource consumption.

Proceedings of the ACM on Programming LanguagesVol. 9(OOPSLA2)
Chongqing University (CN), UNSW Sydney (AU), Institute of Computing Technology (CN), University of Chinese Academy of Sciences (CN)
Openalex Percentile: Top 71%
Software Testing and Debugging Techniques
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Fast Client-Driven CFL-Reachability via Regularization-Based Graph Simplification — Jingling Xue, Haofeng Li, et al. · Proceedings of the ACM on Programming Languages (2025) | TGRS Research Map | TGRS