Behavioural model fusion: an overview of challenges

  • Authors:

  • Shiva Nejati;Marsha Chechik

  • Affiliations:

  • University of Toronto, Toronto, ON, Canada;University of Toronto, Toronto, ON, Canada

  • Venue:
  • Proceedings of the 2008 international workshop on Models in software engineering
  • Year:
  • 2008

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Abstract

In large-scale model-based development, developers periodically need to combine collections of interrelated models. These models may capture different features of a system, describe alternative perspectives on a single feature, or express ways in which different features may alter one another's structure or behaviour. We refer to the process of combining a set of interrelated models as model fusion. In this position paper, we provide an overview of our work on two key fusion activities, merging and composition, for behavioural models. The practical basis of our work comes from two case studies that we conducted using models from the telecommunications domain. We illustrate our work using these case studies, summarize the results our research has led to so far, and describe the future research challenges.