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Enabling the Reuse of Stored Model Transformations Through Annotations

Part of the Lecture Notes in Computer Science book series (LNPSE,volume 9152)

Abstract

With the increasing adoption of MDE, model transformations, one of its core concepts together with metamodeling, stand out as a valuable asset. Therefore, a mechanism to annotate and store existing model transformations appears as a critical need for their efficient exploitation and reuse. Unfortunately, although several reuse mechanisms have been proposed for software artifacts in general and models in particular, none of them is specially tailored to the domain of model transformations. In order to fill this gap, we present here such a mechanism. Our approach is composed by two elements (1) a new DSL specially conceived for describing model transformations in terms of their functional and non-functional properties (2) a semi-automatic process for annotating and querying (repositories of) model transformations using as criteria the properties of our DSL. We validate the feasibility of our approach through a prototype implementation that integrates our approach in a GitHub repository.

Keywords

  • Model Transformation
  • Metamodel
  • Transformation Language
  • Megamodel
  • Default Catalog

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Notes

  1. 1.

    https://eclipse.org/Xtext/.

  2. 2.

    http://eclipse.org/sirius/.

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Acknowledgments

This work was funded by the EU ERDF and the Spanish MINECO under Project TIN2013-41576-R, the Spanish MECD under a FPU grant (AP2010-3259), and the Andalusian Regional Government (Spain) under Project P10-TIC-6114.

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Correspondence to Javier Criado .

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Criado, J., Martínez, S., Iribarne, L., Cabot, J. (2015). Enabling the Reuse of Stored Model Transformations Through Annotations. In: Kolovos, D., Wimmer, M. (eds) Theory and Practice of Model Transformations. ICMT 2015. Lecture Notes in Computer Science(), vol 9152. Springer, Cham. https://doi.org/10.1007/978-3-319-21155-8_4

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  • DOI: https://doi.org/10.1007/978-3-319-21155-8_4

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