Automated variability injection for graphical modelling languages

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Abstract

Model-based development approaches, such as Model-Driven Engineering (MDE), heavily rely on the use of modelling languages to achieve and automate software development tasks. To enable the definition of model variants (e.g., supporting the compact description of system families), one solution is to combine MDE with Software Product Lines. However, this is technically costly as it requires adapting many MDE artefacts associated to the modelling language-especially the meta-models and graphical environments. To alleviate this situation, we propose a method for the automated injection of variability into graphical modelling languages. Given the meta-model and graphical environment of a particular language, our approach permits configuring the allowed model variability, and the graphical environment is automatically adapted to enable creating models with variability. Our solution is implemented atop the Eclipse Modeling Framework and Sirius, and synthesizes adapted graphical editors integrated with FeatureIDE.

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APA

Garmendia, A., Wimmer, M., Guerra, E., Gómez-Martínez, E., & De Lara, J. (2020). Automated variability injection for graphical modelling languages. In GPCE 2020 - Proceedings of the 19th ACM SIGPLAN International Conference on Generative Programming: Concepts and Experiences, Co-located with SPLASH 2020 (pp. 15–21). Association for Computing Machinery, Inc. https://doi.org/10.1145/3425898.3426957

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