NDLI: Behavioural model fusion: an overview of challenges

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Content Provider	ACM Digital Library
Author	Chechik, Marsha Nejati, Shiva
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.
Starting Page	1
Ending Page	6
Page Count	6
File Format	PDF
ISBN	9781605580258
DOI	10.1145/1370731.1370733
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2008-05-10
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Model composition Model matching Model merging Model fusion Behavioural model Model management
Content Type	Text
Resource Type	Article

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Behavioural model fusion: an overview of challenges