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Automated Metamodel/Model Co-evolution Using a Multi-objective Optimization Approach

  • Wael Kessentini
  • Houari Sahraoui
  • Manuel Wimmer
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9764)

Abstract

We propose a generic automated approach for the metamodel/model co-evolution. The proposed technique refines an initial model to make it as conformant as possible to the new metamodel version by finding the best compromise between three objectives, namely minimizing (i) the non-conformities with new metamodel version, (ii) the changes to existing models, and (iii) the loss of information. Consequently, we view the co-evolution as a multi-objective optimization problem, and solve it using the NSGA-II algorithm. We successfully validated our approach on the evolution of the well-known UML state machine metamodel. The results confirm the effectiveness of our approach with average precision and recall respectively higher than 87 % and 89 %.

Keywords

Metamodel/model co-evolution Model migration Coupled evolution NSGA-II 

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Wael Kessentini
    • 1
  • Houari Sahraoui
    • 1
  • Manuel Wimmer
    • 2
  1. 1.DIROUniversity of MontrealMontrealCanada
  2. 2.Business Informatics GroupVienna University of TechnologyViennaAustria

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