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Automated variability injection for graphical modelling languages

Automated variability injection for graphical modelling languages

Authors :
Manuel Wimmer
Antonio Garmendia
Esther Guerra
Elena Gómez-Martínez
Juan de Lara
UAM. Departamento de Ingeniería Informática
Source :
GPCE
Publication Year :
2020
Publisher :
Association for Computing Machinery, 2020.

Abstract

© 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/10.1145/3425898.3426957<br />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<br />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)

Details

Language :
English
Database :
OpenAIRE
Journal :
GPCE
Accession number :
edsair.doi.dedup.....612f66e917d9bb91565719dd9175b015
Full Text :
https://doi.org/10.1145/3425898.3426957