Advertisement

JTACO: Test Execution for Faster Bounded Verification

  • Alexander Kampmann
  • Juan Pablo Galeotti
  • Andreas Zeller
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8570)

Abstract

In bounded program verification a finite set of execution traces is exhaustively checked in order to find violations to a given specification (i.e. errors). SAT-based bounded verifiers rely on SAT-Solvers as their back-end decision procedure, accounting for most of the execution time due to their exponential time complexity.

In this paper we sketch a novel approach to improve SAT-based bounded verification. As modern SAT-Solvers work by augmenting partial assignments, the key idea is to translate some of these partial assignments into JUnit test cases during the SAT-Solving process. If the execution of the generated test cases succeeds in finding an error, the SAT-Solver is promptly stopped.

We implemented our approach in JTACO, an extension to the TACO bounded verifier, and evaluate our prototype by verifying parameterized unit tests of several complex data structures.

Keywords

Propositional Variable Execution Trace Propositional Formula Generate Test Case Binary Search Tree 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Bech, K., Gamma, E.: JUnit: A programmer-oriented testing framework for Java (May 2014), http://junit.org
  2. 2.
    Chalin, P., Kiniry, J.R., Leavens, G.T., Poll, E.: Beyond assertions: Advanced specification and verification with JML and ESC/Java2. In: de Boer, F.S., Bonsangue, M.M., Graf, S., de Roever, W.-P. (eds.) FMCO 2005. LNCS, vol. 4111, pp. 342–363. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  3. 3.
    Clarke, E., Kroning, D., Lerda, F.: A tool for checking ANSI-C programs. In: Jensen, K., Podelski, A. (eds.) TACAS 2004. LNCS, vol. 2988, pp. 168–176. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  4. 4.
    Davis, M., Logemann, G., Loveland, D.W.: A machine program for theorem-proving. Commun. ACM 5(7), 394–397 (1962)CrossRefzbMATHMathSciNetGoogle Scholar
  5. 5.
    Dennis, G., Yessenov, K., Jackson, D.: Bounded verification of voting software. In: Shankar, N., Woodcock, J. (eds.) VSTTE 2008. LNCS, vol. 5295, pp. 130–145. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  6. 6.
    D’Ippolito, N., Frias, M.F., Galeotti, J.P., Lanzarotti, E., Mera, S.: Alloy+HotCore: A fast approximation to unsat core. In: Frappier, M., Glässer, U., Khurshid, S., Laleau, R., Reeves, S. (eds.) ABZ 2010. LNCS, vol. 5977, pp. 160–173. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  7. 7.
    Eén, N., Sörensson, N.: An extensible SAT-solver. In: Giunchiglia, E., Tacchella, A. (eds.) SAT 2003. LNCS, vol. 2919, pp. 502–518. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  8. 8.
    Galeotti, J.P., Rosner, N., Pombo, C.L., Frias, M.F.: Analysis of invariants for efficient bounded verification. In: Tonella, P., Orso, A. (eds.) ISSTA, pp. 25–36. ACM (2010)Google Scholar
  9. 9.
    Hamadi, Y., Jabbour, S., Sais, L.: ManySAT: a parallel SAT solver. JSAT 6(4), 245–262 (2009)zbMATHGoogle Scholar
  10. 10.
    Ivančić, F., Yang, Z., Ganai, M.K., Gupta, A., Shlyakhter, I., Ashar, P.: F-Soft: Software verification platform. In: Etessami, K., Rajamani, S.K. (eds.) CAV 2005. LNCS, vol. 3576, pp. 301–306. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  11. 11.
    Jackson, D.: Software Abstractions: Logic, Language, and Analysis, revised edition. The MIT Press (2012)Google Scholar
  12. 12.
    Near, J.P., Jackson, D.: Rubicon: bounded verification of web applications. In: Tracz, W., Robillard, M.P., Bultan, T. (eds.) SIGSOFT FSE, p. 60. ACM (2012)Google Scholar
  13. 13.
    Parrino, B.C., Galeotti, J.P., Garbervetsky, D., Frias, M.F.: TacoFlow: optimizing sat program verification using dataflow analysis. SoSyM: Software and Systems Modeling (2014)Google Scholar
  14. 14.
    Rosner, N., Galeotti, J.P., Bermúdez, S., Blas, G.M., Rosso, S.P.D., Pizzagalli, L., Zemín, L., Frias, M.F.: Parallel bounded analysis in code with rich invariants by refinement of field bounds. In: Pezzè, M., Harman, M. (eds.) ISSTA, pp. 23–33. ACM (2013)Google Scholar
  15. 15.
    Torlak, E., Chang, F.S.H., Jackson, D.: Finding minimal unsatisfiable cores of declarative specifications. In: Cuellar, J., Maibaum, T., Sere, K. (eds.) FM 2008. LNCS, vol. 5014, pp. 326–341. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  16. 16.
    Xie, Y., Aiken, A.: Saturn: A scalable framework for error detection using boolean satisfiability. ACM Trans. Program. Lang. Syst. 29(3) (2007)Google Scholar
  17. 17.
    Yessenov, K.: A light-weight specification language for bounded program verification. Master’s thesis, MIT (2009)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Alexander Kampmann
    • 2
  • Juan Pablo Galeotti
    • 1
  • Andreas Zeller
    • 1
  1. 1.Software Engineering ChairSaarland UniversitySaarbrückenGermany
  2. 2.Saarbrücken Graduate School of Computer ScienceSaarland UniversitySaarbrückenGermany

Personalised recommendations