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A Feature-Based Approach for Variability Exploration and Resolution in Model Transformation Migration

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Modelling Foundations and Applications (ECMFA 2017)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 10376))

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Abstract

The key to success with Model-Driven Engineering is the ability to maintain metamodels and their related artifacts consistent over time. Metamodels can evolve under evolutionary pressure that arises when clients and users express the need for enhancements. However, metamodel changes come at the price of compromising metamodel-related artifacts, including model transformations, necessitating their migration to again conform to the evolved metamodel. Restoring conformance of transformations is intrinsically difficult since a multitude of possible migration alternatives exist, which are unfeasible to be inspected manually. In this paper, we present an approach to explore variability in model transformation migration. Employing a feature-based representation of several possible transformation migrations, the approach permits modelers to explore and explicitly discover differences and conflicts among them. Once the desired migration alternatives are selected, the actual migration program is generated and executed by exploiting the EMFMigrate platform.

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Notes

  1. 1.

    In order to give more evidence of the difficulties related to the extensional treatment of transformation migrations, which might be required because of metamodel evolutions, our online appendix discusses a list of metamodel changes borrowed from existing catalogues, e.g., [5, 12]: http://www.emfmigrate.org/wp-content/uploads/2017/04/appendix.pdf. Such changes are organized with respect to the impact they might have on existing transformations.

  2. 2.

    Currently, the weaving model \(m_{WMM}\) is manually specified even though an automatic creation is feasible as discussed later in the paper. Such a relevant automation step is an important work that we plan to do in the future.

  3. 3.

    In this work we employed the Eclipse FeatureIDE plugin [22] for specifying feature models.

  4. 4.

    The auxiliary functions HasDoubleMatch, IsRuleDeleted, IsBindingDeleted, and AddConflict used in Algorithm 1 are reported online: http://www.emfmigrate.org/wp-content/uploads/2017/04/appendix.pdf.

  5. 5.

    A detailed discussion of EMFMigrate is outside the scope of this paper. Interested reader can refer to [6, 23] for a detailed presentation of the approach.

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Acknowledgment

This work has been partly funded by the Austrian Science Fund (FWF) under grant P 28519-N31 and the OeAD under grant WTZ AR18/2013 and WTZ AR10/2015.

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Authors and Affiliations

  1. University of L’Aquila, L’Aquila, Italy

    Davide Di Ruscio & Alfonso Pierantonio

  2. Johannes Kepler University Linz, Linz, Austria

    Juergen Etzlstorfer & Wieland Schwinger

  3. Gran Sasso Science Institute, L’Aquila, Italy

    Ludovico Iovino

Authors
  1. Davide Di Ruscio
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  2. Juergen Etzlstorfer
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  3. Ludovico Iovino
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  4. Alfonso Pierantonio
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  5. Wieland Schwinger
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Corresponding author

Correspondence to Ludovico Iovino .

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Editors and Affiliations

  1. University of Paderborn, Paderborn, Germany

    Anthony Anjorin

  2. Tecnalia Research and Innovation, Derio, Spain

    Huáscar Espinoza

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Di Ruscio, D., Etzlstorfer, J., Iovino, L., Pierantonio, A., Schwinger, W. (2017). A Feature-Based Approach for Variability Exploration and Resolution in Model Transformation Migration. In: Anjorin, A., Espinoza, H. (eds) Modelling Foundations and Applications. ECMFA 2017. Lecture Notes in Computer Science(), vol 10376. Springer, Cham. https://doi.org/10.1007/978-3-319-61482-3_5

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  • DOI: https://doi.org/10.1007/978-3-319-61482-3_5

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