A Relationship-Driven Framework for Model Merging

  • Authors:
  • Mehrdad Sabetzadeh;Shiva Nejati;Steve Easterbrook;Marsha Chechik

  • Affiliations:
  • University of Toronto, Canada;University of Toronto, Canada;University of Toronto, Canada;University of Toronto, Canada

  • Venue:
  • MISE '07 Proceedings of the International Workshop on Modeling in Software Engineering
  • Year:
  • 2007

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Abstract

A key problem in model-based development is merging a set of distributed models into a single seamless model. To merge a set of models, we need to know how they are related. In this position paper, we discuss the methodological aspects of describing the relationships between models. We argue that relationships between models should be treated as first-class artifacts in the merge problem and propose a general framework for model merging based on this argument. We illustrate the usefulness of our framework by instantiating it to the state-machine modelling domain and developing a flexible tool for merging state-machines.