Construction of abstract domains for heterogeneous properties (Position Paper)

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Abstract

The aim of static analysis is to infer invariants about programs that are tight enough to establish semantic properties, like the absence of run-time errors. In the last decades, several branches of the static analysis of imperative programs have made significant progress, such as in the inference of numeric invariants or the computation of data structures properties (using pointer abstractions or shape analyzers). Although simultaneous inference of shape-numeric invariants is often needed, this case is especially challenging and less well explored. Notably, simultaneous shape-numeric inference raises complex issues in the design of the static analyzer itself.We study the modular construction of static analyzers, based on combinations of atomic abstract domains to describe several kinds of memory properties and value properties.

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Rival, X., Toubhans, A., & Chang, B. Y. E. (2014). Construction of abstract domains for heterogeneous properties (Position Paper). In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8803, pp. 489–492). Springer Verlag. https://doi.org/10.1007/978-3-662-45231-8_40

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