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Constraint Solving for Interpolation

  • Conference paper
Verification, Model Checking, and Abstract Interpretation (VMCAI 2007)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4349))

Abstract

Interpolation is an important component of recent methods for program verification. It provides a natural and effective means for computing separation between the sets of ‘good’ and ‘bad’ states. The existing algorithms for interpolant generation are proof-based: They require explicit construction of proofs, from which interpolants can be computed. Construction of such proofs is a difficult task. We propose an algorithm for the generation of interpolants for the combined theory of linear arithmetic and uninterpreted function symbols that does not require a priori constructed proofs to derive interpolants. It uses a reduction of the problem to constraint solving in linear arithmetic, which allows application of existing highly optimized Linear Programming solvers in black-box fashion. We provide experimental evidence of the practical applicability of our algorithm.

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Authors and Affiliations

  1. Ecole Polytechnique Fédérale de Lausanne,  

    Andrey Rybalchenko

  2. Max-Planck-Institut für Informatik, Saarbrücken,  

    Andrey Rybalchenko & Viorica Sofronie-Stokkermans

Authors
  1. Andrey Rybalchenko
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  2. Viorica Sofronie-Stokkermans
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Byron Cook Andreas Podelski

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Rybalchenko, A., Sofronie-Stokkermans, V. (2007). Constraint Solving for Interpolation. In: Cook, B., Podelski, A. (eds) Verification, Model Checking, and Abstract Interpretation. VMCAI 2007. Lecture Notes in Computer Science, vol 4349. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69738-1_25

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  • DOI: https://doi.org/10.1007/978-3-540-69738-1_25

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-69735-0

  • Online ISBN: 978-3-540-69738-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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