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KOZÁK, D. STANCU, C. WIMMER, C. WÜRTHINGER, T.
Original Title
Scaling Type-Based Points-to Analysis with Saturation
Type
conference paper
Language
English
Original 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.
Keywords
points-to analysis, static analysis, pointer analysis, Java, GraalVM
Authors
KOZÁK, D.; STANCU, C.; WIMMER, C.; WÜRTHINGER, T.
Released
24. 4. 2024
Location
New York
ISBN
2475-1421
Periodical
Proceedings of the ACM on Programming Languages
Year of study
8
State
United States of America
Pages from
990
Pages to
1013
Pages count
24
BibTex
@inproceedings{BUT189291, author="KOZÁK, D. and STANCU, C. and WIMMER, C. and WÜRTHINGER, T.", title="Scaling Type-Based Points-to Analysis with Saturation", booktitle="Proceedings of the ACM on Programming Languages", year="2024", journal="Proceedings of the ACM on Programming Languages", volume="8", pages="990--1013", address="New York", doi="10.1145/3656417", issn="2475-1421" }