Automated variability injection for graphical modelling languages
Entidad
UAM. Departamento de Ingeniería InformáticaEditor
Association for Computing MachineryFecha de edición
2020-11-16Cita
10.1145/3425898.3426957
Garmendía, A; Wimmer, M.; Guerra, E.; Gómez-Martínez, M.E. (2000). Automated variability injection for graphical modelling languages. Proceedings of the 19th ACM SIGPLAN International Conference on Generative Programming: Concepts and Experiences (GPCE), pp. 15–21
ISBN
978-1-4503-8174-1DOI
10.1145/3425898.3426957Financiado por
Work funded by the R&D programme of Madrid (S2018/TCS4314), the Spanish Ministry of Science (RTI2018-095255-BI00), and the Austrian Science Fund (P 30525-N31)Proyecto
Comunidad de Madrid. S2018/TCS4314; Gobierno de España. RTI2018-095255-BI00Versión del editor
https://doi.org/10.1145/3425898.3426957Materias
EMF; Graphical Modelling Language; Meta-Modelling; Model-Driven Engineering; Product Lines; InformáticaNota
© ACM 2020. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in International Conference on Generative Programming: Concepts and Experiences, https://doi.org/10.1145/3425898.3426957Derechos
© Association for Computering MachineryResumen
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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Google Scholar:Garmendia Jorge, Antonio
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Wimmer, Manuel
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Guerra Sánchez, Esther
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Gómez Martínez, María Elena
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De Lara, Juan
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