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Cloning-based context-sensitive pointer alias analysis using binary decision diagrams

Whaley, John, Lam, Monica S.·2004·Proceedings of the ACM SIGPLAN 2004 conference on Programming language design and implementation

Abstract

This paper presents the first scalable context-sensitive, inclusion-based pointer alias analysis for Java programs. Our approach to context sensitivity is to create a clone of a method for every context of interest, and run a context-insensitive algorithm over the expanded call graph to get context-sensitive results. For precision, we generate a clone for every acyclic path through a program's call graph, treating methods in a strongly connected component as a single node. Normally, this formulation is hopelessly intractable as a call graph often has 10 acyclic paths or more. We show that these exponential relations can be computed efficiently using binary decision diagrams (BDDs). Key to the scalability of the technique is a context numbering scheme that exposes the commonalities across contexts. We applied our algorithm to the most popular applications available on Sourceforge, and found that the largest programs, with hundreds of thousands of Java bytecodes, can be analyzed in under 20 minutes. This paper shows that...

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Metadata

Authors
Whaley, J., & Lam, M. S.
Venue
Proceedings of the ACM SIGPLAN 2004 conference on Programming language design and implementation
Publisher
ACM
Published
2004-06-09
Pages
131-144
ISSN
1531-7102 (ISSN-L)
OpenAlex
W2158600037
Cited by
582
References
0
FWCI
32.09
Type
conference paper
Language
en
Open access
closed

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CoChat. (2026). Citation check: Cloning-based context-sensitive pointer alias analysis using binary decision diagrams. https://app.cochat.ai/papers/10.1145/996841.996859
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Whaley, J., & Lam, M. S. (2004). Cloning-based context-sensitive pointer alias analysis using binary decision diagrams. Proceedings of the ACM SIGPLAN 2004 conference on Programming language design and implementation. https://doi.org/10.1145/996841.996859

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