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Please use this identifier to cite or link to this item: http://hdl.handle.net/10119/9784

Title: Stacking-based context-sensitive points-to analysis for java
Authors: Li, Xin
Ogawa, Mizuhito
Keywords: Points-to analaysis
Weighted pushdown model checking
Issue Date: 2009/10/20
Publisher: Springer
Magazine name: Lecture Notes in Computer Science
Volume: 6405/2011
Start page: 133
End page: 149
DOI: 10.1007/978-3-642-19237-1_14
Abstract: Points-to analysis for Java infers heap objects that a reference variable can point to. Existing practiced context-sensitive points-to analyses are cloning-based, with an inherent limit to handle recursive procedure calls and being hard to scale under deep cloning. This paper presents a stacking-based context-sensitive points-to analysis for Java, by deriving the analysis as weighted pushdown model checking problems. To generate a tractable model for model checking, instead of passing global variables as parameters along procedure calls and returns, we model the heap memory with a global data structure that stores and loads global references with synchronized points-to information on-demand. To accelerate the analysis, we propose a two-staged iterative procedure that combines local exploration for lightening most of iterations and global update for guaranteeing soundness. In particular, summary transition rules that carry cached data flows are carefully introduced to trigger each local exploration, which boosts the convergence with retaining the precision. Empirical studies show that, our analysis scales well to Java benchmarks of significant size, and achieved in average 2.5X speedup in the two-staged analysis framework.
Rights: This is the author-created version of Springer, Xin Li, Mizuhito Ogawa, Lecture Notes in Computer Science, 6405/2011, 2009, 133-149. The original publication is available at www.springerlink.com, http://dx.doi.org/10.1007/978-3-642-19237-1_14
URI: http://hdl.handle.net/10119/9784
Material Type: author
Appears in Collections:b10-1. 雑誌掲載論文 (Journal Articles)

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