Module-Aware Context Sensitive Pointer Analysis

The Java Platform Module System (JPMS) has found widespread applications since introduced in Java 9. However, existing pointer analyses fail to leverage the semantics of JPMS. This paper presents a novel module-aware approach to improving the performance of pointer analysis. We model the semantics o...

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Vydáno v:Proceedings / International Conference on Software Engineering s. 1819 - 1831
Hlavní autoři: Li, Haofeng, Shi, Chenghang, Lu, Jie, Li, Lian, Zhao, Zixuan
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 26.04.2025
Témata:
Analytical models
Benchmark testing
Context modeling
Context Sensitivity
Java
JPMS
Pointer Analysis
Semantics
Sensitivity
Software engineering
ISSN:1558-1225
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Shrnutí:The Java Platform Module System (JPMS) has found widespread applications since introduced in Java 9. However, existing pointer analyses fail to leverage the semantics of JPMS. This paper presents a novel module-aware approach to improving the performance of pointer analysis. We model the semantics of keywords provides and uses in JPMS to recover missing points-to relations. We design a module-aware context-sensitive analysis, which can propagate and apply critical contexts (by exploiting modularity) to balance precision and efficiency better. We have implemented our module-aware pointer analysis named MPA in TAI - E and conducted extensive experiments to compare it with standard object-sensitivity. The evaluation results demonstrate that MPA finds more reachable methods and enhances existing context-sensitive approaches, striking a good balance between efficiency and precision. MPA can increase the number of reachable methods up to 90.9× (lombok) under the same analysis. Performance-wise, MPA is nearly as fast as context-insensitivity for most benchmarks, while its precision is superior to that of 1-object-sensitivity on average.
ISSN:1558-1225
DOI:10.1109/ICSE55347.2025.00227