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Templatable Metamodels for Semantic Variation Points

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Model Driven Architecture- Foundations and Applications (ECMDA-FA 2007)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 4530))

Abstract

In the field of Domain Languages Engineering, Semantic Variation Points are an important issue. This crucial information is often related to the dynamic semantics of systems. Identifying and understanding it is a requisite for all model-based activities (design, simulation, test, formal verification, etc.). Most of the time, semantic variation points are only informally identified in a documentation associated with a metamodel: they are not part of the metamodel itself, and there is currently no mechanism to capture them explicitly. We propose a template-based notation enabling semantic variation points to be clearly and explicitly identified within the metamodel, using template parameter definitions. Semantic variation points can then be intuitively fixed by parameter binding at both model and metamodel levels. We illustrate our proposal with a templated version of the UML 2 state machine metamodel. Finally, we describe a prototype implementation of our mechanisms in the context of the Eclipse Modeling Framework.

This work has been performed in the context of the Usine Logicielle project (www.usine-logicielle.org) of the System@tic Paris Region Cluster. This project is partially funded by the ”Direction Générale des Entreprises of the French administration”, the ”Conseil Régional d’Île de France”, the ”Conseil Général des Yvelines”, the ”Conseil Général de l’Essonne” and the ”Conseil Général des Hauts de Seine”.

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David H. Akehurst Régis Vogel Richard F. Paige

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© 2007 Springer Berlin Heidelberg

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Cuccuru, A., Mraidha, C., Terrier, F., Gérard, S. (2007). Templatable Metamodels for Semantic Variation Points. In: Akehurst, D.H., Vogel, R., Paige, R.F. (eds) Model Driven Architecture- Foundations and Applications. ECMDA-FA 2007. Lecture Notes in Computer Science, vol 4530. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72901-3_6

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  • DOI: https://doi.org/10.1007/978-3-540-72901-3_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-72900-6

  • Online ISBN: 978-3-540-72901-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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