A Pairwise Approach for Model Merging

  • Mohammed BoubakirEmail author
  • Allaoua Chaoui
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 1)


There are several software engineering activities that require merging a set of models to produce a single one. In practice, models are often merged in a pairwise way, without considering the order in which models are combined. In this case, the quality of the results is not always guaranteed as it depends on the order of merging. The approach presented in this paper aims to improve the results, by considering the order of merging. It involves an iterative process, which is repeated until merging all models. In each iteration, we first compare the set of input models to measure the similarity degree of each pair of them. Then we combine a subset of these pairs of models, such that the sum of their similarity degrees is maximal.


Model merging Model comparison Maximum weight matching Combining a set of models Compare Match Merge 


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.MISC Laboratory, Faculty of NTIC, Department of Computer Science and Its ApplicationsUniversity Constantine 2-Abdelhamid MehriConstantineAlgeria

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