Towards Automated Inconsistency Handling in Design Models

  • Marcos Aurélio Almeida da Silva
  • Alix Mougenot
  • Xavier Blanc
  • Reda Bendraou
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6051)


The increasing adoption of MDE (Model Driven Engineering) favored the use of large models of different types. It turns out that when the modeled system gets larger, simply computing a list of inconsistencies (as provided by existing techniques for inconsistency handling) gets less and less effective when it comes to actually fixing them. In fact, the inconsistency handling task (i.e. deciding what needs to be done in order to restore consistency) remains largely manual. This work is a step towards its automatization. We propose a method for the generation of repair plans for an inconsistent model. In our approach, the depth of the explored search space is configurable in order to cope with the underlying combinatorial characteristic of this problem and to avoid overwhelming the designer with large plans that can not be fully checked before being applied.


Detection Rule Meta Object Facility Repair Plan Model Drive Engineer Model Inconsistency 
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.


  1. 1.
    Selic, B.: The pragmatics of model-driven development. IEEE Software 20(5), 19–25 (2003)CrossRefGoogle Scholar
  2. 2.
    Hessellund, A., Czarnecki, K., Wasowski, A.: Guided development with multiple domain-specific languages. In: Engels, G., Opdyke, B., Schmidt, D.C., Weil, F. (eds.) MODELS 2007. LNCS, vol. 4735, pp. 46–60. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  3. 3.
    Balzer, R.: Tolerating inconsistency. In: Proc. Int’ Conf. Software engineering (ICSE 1991), vol. 1, pp. 158–165 (1991)Google Scholar
  4. 4.
    Spanoudakis, G., Zisman, A.: Inconsistency management in software engineering: Survey and open research issues. In: Handbook of Software Engineering and Knowledge Engineering, pp. 329–380. World Scientific, SingaporeGoogle Scholar
  5. 5.
    Van Der Straeten, R., Mens, T., Simmonds, J., Jonckers, V.: Using description logics to maintain consistency between UML models. In: Stevens, P., Whittle, J., Booch, G. (eds.) UML 2003. LNCS, vol. 2863, pp. 326–340. Springer, Heidelberg (2003)Google Scholar
  6. 6.
    Mens, T., et al.: Detecting and resolving model inconsistencies using transformation dependency analysis. In: Nierstrasz, O., Whittle, J., Harel, D., Reggio, G. (eds.) MoDELS 2006. LNCS, vol. 4199, pp. 200–214. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  7. 7.
    Elaasar, M., Brian, L.: An overview of UML consistency management. Technical Report SCE-04-18 (August 2004)Google Scholar
  8. 8.
    Blanc, X., Mougenot, A., Mounier, I., Mens, T.: Detecting model inconsistency through operation-based model construction. In: Robby (ed.) Proc. Int’l Conf. Software engineering (ICSE 2008), vol. 1, pp. 511–520. ACM, New York (2008)CrossRefGoogle Scholar
  9. 9.
    Nentwich, C., Emmerich, W., Finkelstein, A.: Consistency management with repair actions. In: Proc. Int’l Conf. Software Engineering (ICSE 2003), Washington, DC, USA, pp. 455–464. IEEE Computer Society, Los Alamitos (2003)Google Scholar
  10. 10.
    OMG: Unified Modeling Language: Super Structure version 2.1 (January 2006)Google Scholar
  11. 11.
    OMG: Meta Object Facility (MOF) 2.0 Core Specification (January 2006)Google Scholar
  12. 12.
    Egyed, A., Letier, E., Finkelstein, A.: Generating and evaluating choices for fixing inconsistencies in UML design models. In: Proc. ACM/IEEE Int’l Conf. Automated Software Engineering (ASE 2008), pp. 99–108. ACM, New York (2008)CrossRefGoogle Scholar
  13. 13.
    Russell, S.J., Norvig, P.: Artificial Intelligence: A Modern Approach. Pearson Education, London (2003)Google Scholar
  14. 14.
    Mougenot, A., Darrasse, A., Blanc, X.: Uniform random generation of huge metamodel instances. In: Paige, R.F., Hartman, A., Rensink, A. (eds.) ECMDA-FA 2009. LNCS, vol. 5562, pp. 130–145. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  15. 15.
    Dam, K.H., Winikoff, M.: Generation of repair plans for change propagation. In: Luck, M., Padgham, L. (eds.) AOSE 2007. LNCS, vol. 4951, pp. 132–146. Springer, Heidelberg (2008)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Marcos Aurélio Almeida da Silva
    • 1
  • Alix Mougenot
    • 1
  • Xavier Blanc
    • 1
  • Reda Bendraou
    • 1
  1. 1.LIP6, UPMC Paris UniversitasFrance

Personalised recommendations