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The Seventh QBF Solvers Evaluation (QBFEVAL’10)

  • Claudia Peschiera
  • Luca Pulina
  • Armando Tacchella
  • Uwe Bubeck
  • Oliver Kullmann
  • Inês Lynce
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6175)

Abstract

In this paper we report about QBFEVAL’10, the seventh in a series of events established with the aim of assessing the advancements in reasoning about quantified Boolean formulas (QBFs). The paper discusses the results obtained and the experimental setup, from the criteria used to select QBF instances to the evaluation infrastructure. We also discuss the current state-of-the-art in light of past challenges and we envision future research directions that are motivated by the results of QBFEVAL’10.

Keywords

Boolean Formula Module Extraction Hard Instance Main Track Input Formula 
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.

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References

  1. 1.
    Le Berre, D., Roussel, O., Simon, L.: The SAT 2009 Competition (2009), www.satcompetition.org/2009
  2. 2.
    Sinz, C.: Sat-race (2008), baldur.iti.uka.de/sat-race-2008
  3. 3.
    Barrett, C., Deters, M., Oliveras, A., Stump, A.: Design and results of the 4th annual satisfiability modulo theories competition (SMT-COMP 2008) (to appear, 2008)Google Scholar
  4. 4.
    Long, D., Fox, M.: The 3rd International Planning Competition: Results and Analysis. Artificial Intelligence Research 20, 1–59 (2003)CrossRefzbMATHGoogle Scholar
  5. 5.
    Kontchakov, R., Pulina, L., Sattler, U., Schneider, T., Selmer, P., Wolter, F., Zakharyaschev, M.: Minimal Module Extraction from DL-Lite Ontologies using QBF Solvers. In: Proc. of IJCAI 2009, pp. 836–841 (2009)Google Scholar
  6. 6.
    Le Berre, D., Simon, L., Tacchella, A.: Challenges in the QBF arena: the SAT’03 evaluation of QBF solvers. In: Giunchiglia, E., Tacchella, A. (eds.) SAT 2003. LNCS, vol. 2919, pp. 468–485. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  7. 7.
    Narizzano, M., Pulina, L., Tacchella, A.: Ranking and Reputation Sytems in the QBF competition. In: Proc. of AI*IA 2007, pp. 97–108 (2007)Google Scholar
  8. 8.
    Pigorsch, F., Scholl, C.: Exploiting structure in an aig based qbf solver. In: Proc. of DATE 2009, pp. 1596–1601 (2009)Google Scholar
  9. 9.
    Pulina, L., Tacchella, A.: A self-adaptive multi-engine solver for quantified Boolean formulas. Constraints 14(1), 80–116 (2009)MathSciNetCrossRefzbMATHGoogle Scholar
  10. 10.
    Goultiaeva, A., Iverson, V., Bacchus, F.: Beyond CNF: A Circuit-Based QBF Solver. In: Kullmann, O. (ed.) SAT 2009. LNCS, vol. 5584, pp. 412–426. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  11. 11.
    Lonsing, F., Biere, A.: Efficiently Representing Existential Dependency Sets for Expansion-based QBF Solvers. Electronic Notes in Theoretical Computer Science 251, 83–95 (2009)CrossRefzbMATHGoogle Scholar
  12. 12.
    Lonsing, F., Biere, A.: Nenofex: Expanding nnf for qbf solving. In: Kleine Büning, H., Zhao, X. (eds.) SAT 2008. LNCS, vol. 4996, pp. 196–210. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  13. 13.
    Lewis, M., Schubert, T., Becker, B.: QMiraXT–A Multithreaded QBF Solver. In: Methoden und Beschreibungssprachen zur Modellierung und Verifikation von Schaltungen und Systemen (2009)Google Scholar
  14. 14.
    Egly, U., Seidl, M., Woltran, S.: A solver for QBFs in negation normal form. Constraints 14(1), 38–79 (2009)MathSciNetCrossRefzbMATHGoogle Scholar
  15. 15.
    Biere, A.: Resolve and Expand. In: Hoos, H., Mitchell, D.G. (eds.) SAT 2004. LNCS, vol. 3542, pp. 59–70. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  16. 16.
    Giunchiglia, E., Marin, P., Narizzano, M.: Preprocessing Techniques for QBFs. In: Proc. of 15th RCRA workshop (2008)Google Scholar
  17. 17.
    Giunchiglia, E., Narizzano, M., Tacchella, A.: Clause-Term Resolution and Learning in Quantified Boolean Logic Satisfiability. Artificial Intelligence Research 26, 371–416 (2006)MathSciNetzbMATHGoogle Scholar
  18. 18.
    Pulina, L., Tacchella, A.: A structural approach to reasoning with quantified Boolean formulas. In: Proc. of IJCAI 2009, pp. 596–602 (2009)Google Scholar
  19. 19.
    Peschiera, C., Pulina, L., Tacchella, A.: Seventh QBF solvers evaluation, QBFEVAL (2010), http://www.qbfeval.org/2010
  20. 20.
    Giunchiglia, E., Narizzano, M., Pulina, L., Tacchella, A.: Quantified Boolean Formulas satisfiability library, QBFLIB (2001), http://www.qbflib.org
  21. 21.
    Cook, B., Kroening, D., Rümmer, P., Wintersteiger, C.M.: Ranking function synthesis for bit-vector relations. In: Proc. of TACAS 2010 (to appear, 2010)Google Scholar
  22. 22.
    Pulina, L., Tacchella, A.: Treewidth: a useful marker of empirical hardness in quantified Boolean logic encodings. In: Cervesato, I., Veith, H., Voronkov, A. (eds.) LPAR 2008. LNCS (LNAI), vol. 5330, pp. 528–542. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  23. 23.
    Chen, H., Interian, Y.: A Model for Generating Random Quantified Boolean Formulas. In: Proc. of IJCAI 2005, pp. 66–71 (2005)Google Scholar
  24. 24.
    Yu, Y., Malik, S.: Verifying the Correctness of Quantified Boolean Formula(QBF) Solvers: Theory and Practice. In: Proc. of ASP-DAC 2005, pp. 1047–1051 (2005)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Claudia Peschiera
    • 1
  • Luca Pulina
    • 1
  • Armando Tacchella
    • 1
  • Uwe Bubeck
    • 2
  • Oliver Kullmann
    • 3
  • Inês Lynce
    • 4
  1. 1.DISTUniversity of GenoaGenovaItaly
  2. 2.Computer Science Inst.University of PaderbornPaderbornGermany
  3. 3.Computer Science Dept.Swansea UniversitySwanseaUnited Kingdom
  4. 4.INESC-ID/ISTTechnical University of LisbonLisbonPortugal

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