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Issue No.06 - Nov.-Dec. (2012 vol.38)
pp: 1355-1375
Shiva Nejati , Simula Research Laboratory, Lysaker
Mehrdad Sabetzadeh , Simula Research Laboratory, Lysaker
Marsha Chechik , University of Toronto, Toronto
Steve Easterbrook , University of Toronto, Toronto
Pamela Zave , AT&T Laboratories-Research, Florham Park
Model Management addresses the problem of managing an evolving collection of models by capturing the relationships between models and providing well-defined operators to manipulate them. In this paper, we describe two such operators for manipulating feature specifications described using hierarchical state machine models: Match, for finding correspondences between models, and Merge, for combining models with respect to known or hypothesized correspondences between them. Our Match operator is heuristic, making use of both static and behavioral properties of the models to improve the accuracy of matching. Our Merge operator preserves the hierarchical structure of the input models, and handles differences in behavior through parameterization. This enables us to automatically construct merges that preserve the semantics of hierarchical state machines. We report on tool support for our Match and Merge operators, and illustrate and evaluate our work by applying these operators to a set of telecommunication features built by AT&T.
Computational modeling, Semantics, Hierarchical systems, Pragmatics, Parameterization, Electronic mail, Voice mail, parameterization, Model management, match, merge, hierarchical state machines, statecharts, behavior preservation, variability modeling
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