Scaling Type-Based Points-to Analysis with Saturation

Author:

Wimmer Christian1ORCID,Stancu Codrut2ORCID,Kozak David3ORCID,Würthinger Thomas2ORCID

Affiliation:

1. Oracle Labs, Redwood Shores, USA

2. Oracle Labs, Zurich, Switzerland

3. Brno University of Technology, Brno, Czechia / Oracle Labs, Brno, Czechia

Abstract

Designing a whole-program static analysis requires trade-offs between precision and scalability. While a context-insensitive points-to analysis is often considered a good compromise, it still has non-linear complexity that leads to scalability problems when analyzing large applications. On the other hand, rapid type analysis scales well but lacks precision. We use saturation in a context-insensitive type-based points-to analysis to make it as scalable as a rapid type analysis, while preserving most of the precision of the points-to analysis. With saturation, the points-to analysis only propagates small points-to sets for variables. If a variable can have more values than a certain threshold, the variable and all its usages are considered saturated and no longer analyzed. Our implementation in the points-to analysis of GraalVM Native Image, a closed-world approach to build standalone binaries for Java applications, shows that saturation allows GraalVM Native Image to analyze large Java applications with hundreds of thousands of methods in less than two ‍minutes.

Funder

Czech Science Foundation

FIT BUT

Publisher

Association for Computing Machinery (ACM)

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Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Finding Cuts in Static Analysis Graphs to Debloat Software;Proceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis;2024-09-11

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