Detecting Complex Changes During Metamodel Evolution

  • Djamel Eddine Khelladi
  • Regina Hebig
  • Reda Bendraou
  • Jacques Robin
  • Marie-Pierre Gervais
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9097)

Abstract

Evolution of metamodels can be represented at the finest grain by the trace of atomic changes: add, delete, and update elements. For many applications, like automatic correction of models when the metamodel evolves, a higher grained trace must be inferred, composed of complex changes, each one aggregating several atomic changes. Complex change detection is a challenging task since multiple sequences of atomic changes may define a single user intention and complex changes may overlap over the atomic change trace. In this paper, we propose a detection engine of complex changes that simultaneously addresses these two challenges of variability and overlap. We introduce three ranking heuristics to help users to decide which overlapping complex changes are likely to be correct. We describe an evaluation of our approach that allow reaching full recall. The precision is improved by our heuristics from 63% and 71% up to 91% and 100% in some cases.

Keywords

Metamodel Evolution Complex change Detection 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Djamel Eddine Khelladi
    • 1
  • Regina Hebig
    • 1
  • Reda Bendraou
    • 1
  • Jacques Robin
    • 1
  • Marie-Pierre Gervais
    • 1
    • 2
  1. 1.Sorbonne Universités, UPMC Univ Paris 06, UMR 7606ParisFrance
  2. 2.Université Paris Ouest Nanterre La DefenseNanterreFrance

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