An Efficient Abstract Domain for Not Necessarily Closed Polyhedra

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Abstract

We present a construction of the abstract domain of NNC (not necessarily topologically closed) polyhedra based on a recently introduced variant of the double description representation and conversion procedure. We describe the implementation of the operators needed to interface the new abstract domain with commonly available static analysis tools, highlighting the efficiency gains enabled by the new representation. We also reconsider the widening operator for NNC polyhedra, proposing a more appropriate specification based on the semantics of the domain elements, rather than their low level representation details. Finally, we provide an experimental evaluation comparing the efficiency of the new abstract domain with respect to more classical implementations.

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Becchi, A., & Zaffanella, E. (2018). An Efficient Abstract Domain for Not Necessarily Closed Polyhedra. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11002 LNCS, pp. 146–165). Springer Verlag. https://doi.org/10.1007/978-3-319-99725-4_11

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