Efficient points-to analysis for whole-program analysis

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Abstract

To function on programs written in languages such as C that make extensive use of pointers, automated software engineering tools re- quire safe alias information. Existing alias-analysis techniques that are sufficiently efficient for analysis on large software systems may provide alias information that is too imprecise for tools that use it: The imprecision of the alias information may (1) reduce the precision of the information provided by the tools and (2) increase the cost of the tools. This paper presents a flow-insensitive, context-sensitive points-to analysis algorithm that computes alias information that is almost as precise as that computed by Andersen's algorithm { the most precise flow- And context- insensitive algorithm { and almost as efficient as Steensgaard's algorithm { the most efficient flow- And context-insensitive algorithm. Our empirical studies show that our algorithm scales to large programs better than Andersen's algorithm and show that flow-insensitive alias analysis algorithms, such as our algorithm and Andersen's algorithm, can compute alias information that is close in precision to that computed by the more expensive flow- And context-sensitive alias analysis algorithms. © Springer-Verlag Berlin Heidelberg 1999.

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APA

Liang, D., & Harrold, M. J. (1999). Efficient points-to analysis for whole-program analysis. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1687 LNCS, pp. 199–215). Springer Verlag. https://doi.org/10.1007/3-540-48166-4_13

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