Publication detail

Scaling Type-Based Points-to Analysis with Saturation

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

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",
  pages="990--1013",
  address="New York",
  doi="10.1145/3656417"
}