ICGT 2010: Graph Transformations pp 27-42 | Cite as

Graph Transformation Units Guided by a SAT Solver

  • Hans-Jörg Kreowski
  • Sabine Kuske
  • Robert Wille
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6372)

Abstract

Graph transformation units are rule-based devices to model graph algorithms, graph processes, and the dynamics of systems the states of which are represented by graphs. Given a graph, various rules are applicable at various matches in general, but not any choice leads to a proper result so that one faces the problem of nondeterminism. As countermeasure, graph transformation units provide the generic concept of control conditions which allow one to cut down the nondeterminism and to choose the proper rule applications out of all possible ones. In this paper, we propose an alternative approach. For a special type of graph transformation units including the solution of many NP-complete and NP-hard problems, the successful derivations from initial to terminal graphs are described by propositional formulas. In this way, it becomes possible to use a SAT solver to find out whether there is a successful derivation for some initial graph or not and how it is built up in the positive case.

Keywords

Transformation Unit Regular Expression Graph Transformation Propositional Formula Rule Application 
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.
    Biere, A., Cimatti, A., Clarke, E., Fujita, M., Zhu, Y.: Symbolic model checking using SAT procedures instead of BDDs. In: Design Automation Conf., pp. 317–320 (1999)Google Scholar
  2. 2.
    Biere, A., Heule, M., van Maaren, H., Walsh, T. (eds.): Handbook of Satisfiability, Frontiers in Artificial Intelligence and Applications, vol. 185. IOS Press, Amsterdam (2009)Google Scholar
  3. 3.
    Carnegie Mellon University, Graph Coloring Instances, http://mat.gsia.cmu.edu/COLOR/instances.html:
  4. 4.
    Cook, S.A.: The complexity of theorem-proving procedures. In: Proc. Third ACM Symposium on Theory of Computing, pp. 151–158 (1971)Google Scholar
  5. 5.
    Corradini, A., Ehrig, H., Heckel, R., Löwe, M., Montanari, U., Rossi, F.: Algebraic approaches to graph transformation part I: Basic concepts and double pushout approach. In: Rozenberg, G. (ed.) Handbook of Graph Grammars and Computing by Graph Transformation. Foundations, vol. 1, pp. 163–245. World Scientific, Singapore (1997)CrossRefGoogle Scholar
  6. 6.
    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
  7. 7.
    Ehrig, H., Ehrig, K., Prange, U., Taentzer, G. (eds.): Fundamentals of Algebraic Graph Transformation. Springer, Heidelberg (2006)MATHGoogle Scholar
  8. 8.
    Ganai, M., Gupta, A.: SAT-Based Scalable Formal Verification Solutions. Series on Integrated Circuits and Systems. Springer, Heidelberg (2007)MATHCrossRefGoogle Scholar
  9. 9.
    Hölscher, K., Klempien-Hinrichs, R., Knirsch, P.: Undecidable control conditions in graph transformation units. Electronic Notes in Theoretical Computer Science 195, 95–111 (2008)CrossRefGoogle Scholar
  10. 10.
    Kreowski, H.-J., Kuske, S.: Graph transformation units with interleaving semantics. Formal Aspects of Computing 11(6), 690–723 (1999)MATHCrossRefGoogle Scholar
  11. 11.
    Kreowski, H.-J., Kuske, S., Rozenberg, G.: Graph transformation units – an overview. In: Degano, P., De Nicola, R., Meseguer, J. (eds.) Concurrency, Graphs and Models. LNCS, vol. 5065, pp. 57–75. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  12. 12.
    Kuske, S.: More about control conditions for transformation units. In: Ehrig, H., Engels, G., Kreowski, H.-J., Rozenberg, G. (eds.) TAGT 1998. LNCS, vol. 1764, pp. 323–337. Springer, Heidelberg (2000)Google Scholar
  13. 13.
    Litovski, I., Métivier, Y., Sopena, É.: Graph relabelling systems and distributed algorithms. In: Ehrig, H., Kreowski, H.-J., Montanari, U., Rozenberg, G. (eds.) Handbook of Graph Grammars and Computing by Graph Transformation. Concurrency, Parallelism, and Distribution, vol. 3, pp. 1–56. World Scientific, Singapore (1999)Google Scholar
  14. 14.
    Marques-Silva, J., Lynce, I.: Towards robust CNF encodings of cardinality constraints. In: Bessière, C. (ed.) CP 2007. LNCS, vol. 4741, pp. 483–497. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  15. 15.
    Soeken, M., Wille, R., Kuhlmann, M., Gogolla, M., Drechsler, R.: Verifying UML/OCL models using Boolean satisfiability. In: Design, Automation and Test in Europe, pp. 1341–1344 (2010)Google Scholar
  16. 16.
    Tseitin, G.: On the complexity of derivation in propositional calculus. In: Studies in Constructive Mathematics and Mathematical Logic, Part 2, pp. 115–125 (1968); Reprinted in: Siekmann, J., Wrightson, G. (eds.): Automation of Reasoning, vol. 2, pp. 466–483. Springer, Berlin (1983)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Hans-Jörg Kreowski
    • 1
  • Sabine Kuske
    • 1
  • Robert Wille
    • 1
  1. 1.Department of Computer ScienceUniversity of BremenBremenGermany

Personalised recommendations