Abstract
We improve the policy iteration-based algorithm for value set analysis by giving a new heuristic for policy selection based on a local static analysis. In particular, we detect loops in the program and perform an analysis to discover the relative changes of variables in the loop, that is, whether a variable is constant or whether its value rises, falls or both. We use these relative changes to improve the old heuristic, achieving better (that is, smaller) fixed points than the original approach.
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CITATION STYLE
Völker, M., & Kowalewski, S. (2019). A Change-Based Heuristic for Static Analysis with Policy Iteration. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11822 LNCS, pp. 73–95). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-32304-2_5
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