Meta-model Matching for Automatic Model Transformation Generation

Jean-Rémy Falleri 1 Marianne Huchard 1 Mathieu Lafourcade 2 Clémentine Nebut 1
1 MAREL - Models And Reuse Engineering, Languages
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
2 TEXTE - Exploration et exploitation de données textuelles
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
Abstract : Applying Model-Driven Engineering (MDE) leads to the creation of a large number of metamodels, since MDE recommends an intensive use of models defined by metamodels. Metamodels with similar objectives are then inescapably created. A recurrent issue is thus to turn compatible models conforming to similar metamodels, for example to use them in the same tool. The issue is classically solved developing ad hoc model transformations. In this paper, we propose an approach that automatically detects mappings between two metamodels and uses them to generate an alignment between those metamodels. This alignment needs to be manually checked and can then be used to generate a model transformation. Our approach is built on the Similarity Flooding algorithm used in the fields of schema matching and ontology alignment. Experimental results comparing the effectiveness of the application of various implementations of this approach on real-world metamodels are given.
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Jean-Rémy Falleri, Marianne Huchard, Mathieu Lafourcade, Clémentine Nebut. Meta-model Matching for Automatic Model Transformation Generation. MoDELS: Model Driven Engineering Languages and Systems, Sep 2008, Toulouse, France. pp.326-340, ⟨10.1007/978-3-540-87875-9_24⟩. ⟨lirmm-00322879⟩

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