Constraint solving for interpolation

  • Authors:
  • Andrey Rybalchenko;Viorica Sofronie-Stokkermans

  • Affiliations:
  • Technische Universität München, Germany;Max Planck Institute for Informatics, Saarbrücken, Germany

  • Venue:
  • Journal of Symbolic Computation
  • Year:
  • 2010

Quantified Score

Hi-index 0.00

Visualization

Abstract

Interpolation is an important component of recent methods for program verification. It provides a natural and effective means for computing the 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 a black-box fashion. We provide experimental evidence of the practical applicability of our algorithm.