Construction of Abstract Domains for Heterogeneous Properties (Position Paper)

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.

The research leading to these results has received funding from the European Research Council under the FP7 grant agreement 278673, Project MemCAD and the United States National Science Foundation under grant CCF-1055066.