We introduce a new technique for dramatically improving the performance of inclusion-based points-to analysis, by using bisimilarity in order to detect pointer equivalences before constraint resolution. We present the design and correctness proof of this technique, along with an implementation prototype, and a series of benchmarks. The benchmarks indicate that our technique dramatically improves the scalability of inclusion-based points-to analysis, beating the current leading offline optimizations for inclusion-based points-to analysis. © 2009 Springer.
CITATION STYLE
Simon, L. (2009). Optimizing pointer analysis using bisimilarity. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5673 LNCS, pp. 222–237). https://doi.org/10.1007/978-3-642-03237-0_16
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