Establishing Correspondences between Models with the Epsilon Comparison Language

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Abstract

Model comparison is an essential prerequisite for a number of model management tasks in Model Driven Engineering, such as model differencing and versioning, model and aspect merging and model transformation testing. In this paper we present the Epsilon Comparison Language (ECL), a hybrid rule-based language, built atop the Epsilon platform, which enables developers to implement comparison algorithms at a high level of abstraction and execute them in order to identify matches between elements belonging to models of diverse metamodels and modelling technologies.