Multi-level model product lines: Open and closed variability for modelling language families
Entidad
UAM. Departamento de Ingeniería InformáticaEditor
Springer OpenFecha de edición
2020-03-13Cita
10.1007/978-3-030-45234-6_8
H. Wehrheim and J. Cabot (Eds.): FASE 2020, Dublin, Ireland, LNCS 12076, pp. 161–181
ISSN
0302-9743 (print); 1611-3349 (online)ISBN
978-3-030-45233-9; 978-3-030-45234-6 (eBook)DOI
10.1007/978-3-030-45234-6_8Financiado por
Work funded by the Spanish Ministry of Science (project MASSIVE, RTI2018-095255-B-I00) and the R&D programme of Madrid (project FORTE, P2018/TCS-4314).Proyecto
Gobierno de España. RTI2018-095255-B-I00; Comunidad de Madrid. P2018/TCS-4314/FORTE-CMVersión del editor
https://doi.org/10.1007/978-3-030-45234-6_8Materias
Domain-specific languages; Meta-modelling; MetaDepth; Multi-level modelling; Product lines; InformáticaDerechos
© 2020 The AuthorsResumen
Modelling is an essential activity in software engineering processes. It typically involves two meta-levels: one includes meta-models that describe modelling languages, and the other contains models built by instantiating those meta-models. Multi-level modelling generalizes this approach by allowing models to span an arbitrary number of meta-levels. A scenario that profits from multi-level modelling is the definition of language families that become specialized by successive refinements at subsequent meta-levels, hence promoting language reuse. This enables an open set of variability options for the possible specializations of a given language. However, multi-level modelling lacks the ability to express closed variability regarding the supported language primitives and their realizations. This limits the reuse opportunities of a language family. To improve this situation, we propose a novel combination of product lines with multi-level modelling to cover both open and closed variability. Our proposal is backed by a formal theory that guarantees correctness, and is implemented atop the MetaDepth multi-level modelling tool.
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Google Scholar:Lara Jaramillo, Juan de
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Guerra Sánchez, Esther
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