JavaSMT: A Unified Interface for SMT Solvers in Java

  • Egor George Karpenkov
  • Karlheinz Friedberger
  • Dirk Beyer
Conference paper
First Online:
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9971)

Abstract

Satisfiability Modulo Theory (SMT) solvers received a lot of attention in the research community in the last decade, and consequently their expressiveness and performance have significantly improved. In the areas of program analysis and model checking, many of the newly developed tools rely on SMT solving. The SMT-LIB initiative defines a common format for communication with an SMT solver. However, tool developers often prefer to use the solver API instead, because many features offered by SMT solvers such as interpolation, optimization, and formula introspection are not supported by SMT-LIB directly. Additionally, using SMT-LIB for communication incurs a performance overhead, because all the queries to the solver have to be serialized to strings. Yet using the API directly creates the problem of a solver lock-in, which makes evaluating a tool with different solvers very difficult. We present JavaSMT, a library that exposes a solver-independent API layer for SMT solving. Our library aims to close the gap between API-based and SMT-LIB-based communication, by offering a large set of features with minimal performance overhead. JavaSMT has been used internally in CPAchecker since inception, and has been heavily tested in different verification algorithms. The library is available from its Github website https://github.com/sosy-lab/java-smt.

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Notes

Acknowledgements

The authors thank P. Wendler for valuable discussions on design decisions and principles behind JavaSMT, and all JavaSMT contributors for their programming efforts.

References

  1. 1.
    Cimatti, A., Griggio, A., Schaafsma, B.J., Sebastiani, R.: The MathSAT5 SMT Solver. In: Piterman, N., Smolka, S.A. (eds.) Tools and Algorithms for the Construction and Analysis of Systems. LNCS, vol. 7795, pp. 93–107. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  2. 2.
    Bradley, A.R.: SAT-based model checking without unrolling. In: Jhala, R., Schmidt, D. (eds.) VMCAI 2011. LNCS, vol. 6538, pp. 70–87. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  3. 3.
    Barrett, C., Fontaine, P., Tinelli, C.: The SMT-LIB Standard: Version 2.5. Technical report. Department of Computer Science, University of Iowa (2015). www.SMT-LIB.org
  4. 4.
    Flanagan, C., Leino, K.R.M.: Houdini, an annotation assistant for ESC/Java. In: Oliveira, J.N., Zave, P. (eds.) FME 2001. LNCS, vol. 2021, pp. 500–517. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  5. 5.
    Beyer, D.: Reliable and reproducible competition results with BenchExec and witnesses (Report on SV-COMP 2016). In: Chechik, M., Raskin, J.-F. (eds.) TACAS 2016. LNCS, vol. 9636, pp. 887–904. Springer, Heidelberg (2016)CrossRefGoogle Scholar
  6. 6.
    Beyer, D., Keremoglu, M.E.: CPAchecker: A tool for configurable software verification. In: Gopalakrishnan, G., Qadeer, S. (eds.) CAV 2011. LNCS, vol. 6806, pp. 184–190. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  7. 7.
    Cok, D.R.: The jSMTLIB User Guide (2013). http://smtlib.github.io/jSMTLIB/jSMTLIBUserGuide.pdf. Accessed 10 Feb 2016
  8. 8.
    Karpenkov, E.G., Monniaux, D., Wendler, P.: Program analysis with local policy iteration. In: Jobstmann, B., Leino, K.R.M. (eds.) VMCAI 2016. LNCS, vol. 9583, pp. 127–146. Springer, Heidelberg (2016)CrossRefGoogle Scholar
  9. 9.
    Gamma, E., Helm, R., Johnson, R., Vlissides, J.: Design Patterns: Elements of Reusable Object-Oriented Software. Addison-Wesley, Boston (1995)MATHGoogle Scholar
  10. 10.
    Bloch, J.: Effective Java (The Java Series), 2nd edn. Prentice Hall, Upper Saddle River (2008)Google Scholar
  11. 11.
    Christ, J., Hoenicke, J.: Interpolation in SMTLIB 2.0 (2012). https://ultimate.informatik.uni-freiburg.de/smtinterpol/proposal.pdf. Accessed 10 Feb 2016
  12. 12.
    Christ, J., Hoenicke, J., Nutz, A.: SMTInterpol: An interpolating SMT solver. In: Donaldson, A., Parker, D. (eds.) SPIN 2012. LNCS, vol. 7385, pp. 248–254. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  13. 13.
    Luckow, K., Dimjašević, M., Giannakopoulou, D., Howar, F., Isberner, M., Kahsai, T., Rakamarić, Z., Raman, V.: jDart: A dynamic symbolic analysis framework. In: Chechik, M., Raskin, J.-F. (eds.) TACAS 2016. LNCS, vol. 9636, pp. 442–459. Springer, Heidelberg (2016)CrossRefGoogle Scholar
  14. 14.
    de Moura, L., Bjørner, N.: Z3: An efficient SMT solver. In: Ramakrishnan, C.R., Rehof, J. (eds.) TACAS 2008. LNCS, vol. 4963, pp. 337–340. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  15. 15.
    Gario, M., Micheli, A.: PySMT: A solver-agnostic library for fast prototyping of SMT-based algorithms. In: SMT 2015 (2015)Google Scholar
  16. 16.
    Rümmer, P.: E-matching with free variables. In: Bjørner, N., Voronkov, A. (eds.) LPAR 2012. LNCS, vol. 7180, pp. 359–374. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  17. 17.
    Sebastiani, R., Trentin, P.: OptiMathSAT: A tool for optimization modulo theories. In: Kröening, D., Păsăreanu, C.S. (eds.) CAV 2015. LNCS, vol. 9206, pp. 447–454. Springer, Heidelberg (2015)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Egor George Karpenkov
    • 1
    • 2
  • Karlheinz Friedberger
    • 3
  • Dirk Beyer
    • 3
  1. 1.Univ. Grenoble Alpes, VERIMAGGrenobleFrance
  2. 2.CNRS, VERIMAGGrenobleFrance
  3. 3.University of PassauPassauGermany

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