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Cloning-based context-sensitive pointer alias analysis using binary decision diagrams
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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Cited by
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The essence of command injection attacks in web applications
Su, Z., & Wassermann, G. (2006) · Conference record of the 33rd ACM SIGPLAN-SIGACT symposium on Principles of programming languages · doi:10.1145/1111037.1111070 · Cited by 515
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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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- 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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