Abstract
Nowadays, it is well recognized that model transformation is at the heart of model driven engineering approaches (MDE) and represents as a consequence one of the most important operation in MDE. However, despite the multitude of model transformation language proposals emerging from university and industry, these transformations are often created manually, which is a fastidious and error-prone task, and therefore an expensive process. In this context, we argue that the semi-automatic generation of transformation rules is an important challenge in future MDE development to make it easier, faster, and cost-reduced process. In this paper we propose to discuss metamodels matching as a key technique for a semi-automatic transformation process. First, we review and discuss the main approaches that have been proposed in the state of the art for metamodels matching. Secondly, we compare three algorithms of metamodel matching namely “Similarity Flooding”, SAMT4MDE+ and ModelCVS using match quality measures proposed for schema matching in databases. A Plug-in under the Eclipse framework has been developed to support our comparison using three couple of metamodels.
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Lafi, L., Hammoudi, S., Feki, J. (2011). Metamodel Matching Techniques in MDA: Challenge, Issues and Comparison. In: Bellatreche, L., Mota Pinto, F. (eds) Model and Data Engineering. MEDI 2011. Lecture Notes in Computer Science, vol 6918. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24443-8_29
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DOI: https://doi.org/10.1007/978-3-642-24443-8_29
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