Advertisement

CSIsat: Interpolation for LA+EUF

Tool Paper
  • Dirk Beyer
  • Damien Zufferey
  • Rupak Majumdar
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5123)

Abstract

We present CSIsat, an interpolating decision procedure for the quantifier-free theory of rational linear arithmetic and equality with uninterpreted function symbols. Our implementation combines the efficiency of linear programming for solving the arithmetic part with the efficiency of a SAT solver to reason about the boolean structure. We evaluate the efficiency of our tool on benchmarks from software verification. Binaries and the source code of CSIsat are publicly available as free software.

References

  1. 1.
    Biere, A.: PicoSAT essentials. JSAT (submitted, 2008) Google Scholar
  2. 2.
    Bozzano, M., Bruttomesso, R., Cimatti, A., Junttila, T.A., Ranise, S., Rossum, P.v., Sebastiani, R.: Efficient satisfiability modulo theories via delayed theory combination. In: Etessami, K., Rajamani, S.K. (eds.) CAV 2005. LNCS, vol. 3576, pp. 335–349. Springer, Heidelberg (2005)Google Scholar
  3. 3.
    Cimatti, A., Griggio, A., Sebastiani, R.: Efficient interpolant generation in satisfiability modulo theories. In: Ramakrishnan, C.R., Rehof, J. (eds.) TACAS 2008. LNCS, vol. 4963, pp. 397–412. Springer, Heidelberg (2008)Google Scholar
  4. 4.
    Craig, W.: Linear reasoning. A new form of the Herbrand-Gentzen theorem. J. Symb. Log. 22(3), 250–268 (1957)zbMATHCrossRefMathSciNetGoogle Scholar
  5. 5.
    Holzbaur, C.: OFAI clp(q,r) Manual, Edition 1.3.3. Austrian Research Institute for Artificial Intelligence, Vienna, TR-95-09 (1995) Google Scholar
  6. 6.
    McMillan, K.L.: An interpolating theorem prover. Theor. Comput. Sci. 345(1), 101–121 (2005)zbMATHCrossRefMathSciNetGoogle Scholar
  7. 7.
    Nelson, G., Oppen, D.C.: Fast decision procedures based on congruence closure. J. ACM 27(2), 356–364 (1980)zbMATHMathSciNetGoogle Scholar
  8. 8.
    Nieuwenhuis, R., Oliveras, A., Tinelli, C.: Solving SAT and SAT modulo theories: From an abstract Davis-Putnam-Logemann-Loveland procedure to DPLL(T). J. ACM 53(6), 937–977 (2006)CrossRefMathSciNetGoogle Scholar
  9. 9.
    Rybalchenko, A., Sofronie-Stokkermans, V.: Constraint Solving for Interpolation. In: Cook, B., Podelski, A. (eds.) VMCAI 2007. LNCS, vol. 4349, pp. 346–362. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  10. 10.
    Yorsh, G., Musuvathi, M.: A combination method for generating interpolants. In: Nieuwenhuis, R. (ed.) CADE 2005. LNCS (LNAI), vol. 3632, pp. 353–368. Springer, Heidelberg (2005)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Dirk Beyer
    • 1
  • Damien Zufferey
    • 2
  • Rupak Majumdar
    • 3
  1. 1.Simon Fraser UniversityCanada
  2. 2.EPFLSwitzerland
  3. 3.UCLAUSA

Personalised recommendations