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Exploring Scenario Exploration

  • Nuno Macedo
  • Alcino Cunha
  • Tiago Guimarães
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9033)

Abstract

Model finders are very popular for exploring scenarios, helping users validate specifications by navigating through conforming model instances. To be practical, the semantics of such scenario exploration operations should be formally defined and, ideally, controlled by the users, so that they are able to quickly reach interesting scenarios.

This paper explores the landscape of scenario exploration operations, by formalizing them with a relational model finder. Several scenario exploration operations provided by existing tools are formalized, and new ones are proposed, namely to allow the user to easily explore very similar (or different) scenarios, by attaching preferences to model elements. As a proof-of-concept, such operations were implemented in the popular Alloy Analyzer, further increasing its usefulness for (user-guided) scenario exploration.

Keywords

Minimal Solution Alloy Analyzer Regular Model Model Repair Iteration Operation 
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.

References

  1. 1.
    Anastasakis, K., Bordbar, B., Georg, G., Ray, I.: On challenges of model transformation from UML to Alloy. In: SoSyM, vol. 9, pp. 69–86 (2010)Google Scholar
  2. 2.
    Büttner, F., Egea, M., Cabot, J., Gogolla, M.: Verification of ATL transformations using transformation models and model finders. In: Aoki, T., Taguchi, K. (eds.) ICFEM 2012. LNCS, vol. 7635, pp. 198–213. Springer, Heidelberg (2012)Google Scholar
  3. 3.
    Cunha, A., Garis, A., Riesco, D.: Translating between Alloy specifications and UML class diagrams annotated with OCL. In: SoSyM (2013)Google Scholar
  4. 4.
    Cunha, A., Macedo, N., Guimarães, T.: Target oriented relational model finding. In: Gnesi, S., Rensink, A. (eds.) FASE 2014 (ETAPS). LNCS, vol. 8411, pp. 17–31. Springer, Heidelberg (2014)Google Scholar
  5. 5.
    Garcia, M.: Formalization of QVT-Relations: OCL-based static semantics and Alloy-based validation. In: MDSD 2008, pp. 21–30. Shaker Verlag (2008)Google Scholar
  6. 6.
    Iser, M., Sinz, C., Taghdiri, M.: Minimizing models for tseitin-encoded SAT instances. In: Järvisalo, M., Van Gelder, A. (eds.) SAT 2013. LNCS, vol. 7962, pp. 224–232. Springer, Heidelberg (2013)Google Scholar
  7. 7.
    Jackson, D.: Software Abstractions: Logic, Language, and Analysis. MIT Press, revised edition (2012)Google Scholar
  8. 8.
    Kleiner, M., Del Fabro, M.D., Albert, P.: Model search: Formalizing and automating constraint solving in MDE platforms. In: Kühne, T., Selic, B., Gervais, M.-P., Terrier, F. (eds.) ECMFA 2010. LNCS, vol. 6138, pp. 173–188. Springer, Heidelberg (2010)Google Scholar
  9. 9.
    Koshimura, M., Nabeshima, H., Fujita, H., Hasegawa, R.: Minimal model generation with respect to an atom set. In: FTP 2009, pp. 49–59 (2009)Google Scholar
  10. 10.
    Kuhlmann, M., Gogolla, M.: From UML and OCL to relational logic and back. In: France, R.B., Kazmeier, J., Breu, R., Atkinson, C. (eds.) MODELS 2012. LNCS, vol. 7590, pp. 415–431. Springer, Heidelberg (2012)Google Scholar
  11. 11.
    Macedo, N., Cunha, A.: Implementing QVT-R bidirectional model transformations using alloy. In: Cortellessa, V., Varró, D. (eds.) FASE 2013 (ETAPS 2013). LNCS, vol. 7793, pp. 297–311. Springer, Heidelberg (2013)Google Scholar
  12. 12.
    Macedo, N., Cunha, A.: Least-change bidirectional model transformation with QVT-R and ATL. In: SoSyM (2014) (to appear)Google Scholar
  13. 13.
    Macedo, N., Guimarães, T., Cunha, A.: Model repair and transformation with Echo. In: ASE 2013, pp. 694–697. IEEE (2013)Google Scholar
  14. 14.
    McCune, W.: A Davis-Putnam program and its application to finite first-order model search: quasigroup existence problem. Technical Report ANL/MCS-TM-194, Argonne National Laboratory, Argonne, IL (May 1994)Google Scholar
  15. 15.
    Nelson, T., Saghafi, S., Dougherty, D.J., Fisler, K., Krishnamurthi, S.: Aluminum: principled scenario exploration through minimality. In: ICSE 2013, pp. 232–241. IEEE/ACM (2013)Google Scholar
  16. 16.
    Van Der Straeten, R., Pinna Puissant, J., Mens, T.: Assessing the kodkod model finder for resolving model inconsistencies. In: France, R.B., Kuester, J.M., Bordbar, B., Paige, R.F. (eds.) ECMFA 2011. LNCS, vol. 6698, pp. 69–84. Springer, Heidelberg (2011)Google Scholar
  17. 17.
    Torlak, E., Jackson, D.: Kodkod: A relational model finder. In: Grumberg, O., Huth, M. (eds.) TACAS 2007. LNCS, vol. 4424, pp. 632–647. Springer, Heidelberg (2007)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Nuno Macedo
    • 1
  • Alcino Cunha
    • 1
  • Tiago Guimarães
    • 1
  1. 1.HASLab — High Assurance Software LaboratoryINESC TEC & Universidade do MinhoBragaPortugal

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