A Modular Approach to MaxSAT Modulo Theories

  • Alessandro Cimatti
  • Alberto Griggio
  • Bastiaan Joost Schaafsma
  • Roberto Sebastiani
Conference paper

DOI: 10.1007/978-3-642-39071-5_12

Part of the Lecture Notes in Computer Science book series (LNCS, volume 7962)
Cite this paper as:
Cimatti A., Griggio A., Schaafsma B.J., Sebastiani R. (2013) A Modular Approach to MaxSAT Modulo Theories. In: Järvisalo M., Van Gelder A. (eds) Theory and Applications of Satisfiability Testing – SAT 2013. SAT 2013. Lecture Notes in Computer Science, vol 7962. Springer, Berlin, Heidelberg

Abstract

In this paper we present a novel “modular” approach for (weighted partial) MaxSAT Modulo Theories. The main idea is to combine a lazy SMT solver with a purely-propositional (weighted partial) MaxSAT solver, by making them exchange information iteratively: the former produces an increasing set of theory lemmas which are used by the latter to progressively refine an approximation of the final subset of the soft clauses, which is eventually returned as output.

The approach has several practical features. First, it is independent from the theories addressed. Second, it is simple to implement and to update, since both SMT and MaxSAT solvers can be used as blackboxes. Third, it can be interfaced with external MaxSAT and SMT solvers in a plug-and-play manner, so that to benefit for free of tools which are or will be made available.

We have implemented our approach on top of the MathSAT5 SMT solver and of a selection of external MaxSAT solvers, and we have evaluated it by means of an extensive empirical test on SMT-LIB benchmarks. The results confirm the validity and potential of this approach.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Alessandro Cimatti
    • 1
  • Alberto Griggio
    • 1
  • Bastiaan Joost Schaafsma
    • 1
    • 2
  • Roberto Sebastiani
    • 2
  1. 1.FBK-IRSTTrentoItaly
  2. 2.DISIUniversity of TrentoItaly

Personalised recommendations