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dc.contributor.authorMacias Gomez de Villar, Fernando
dc.contributor.authorRutle, Adrian
dc.contributor.authorStolz, Volker
dc.date.accessioned2018-02-01T15:17:55Z
dc.date.available2018-02-01T15:17:55Z
dc.date.issued2016
dc.identifier.citationMacias Gomez de Villar F, Rutle A, Stolz V. MultEcore: Combining the best of fixed-level and multilevel metamodelling. CEUR Workshop Proceedings. 2016;1722:66-75
dc.identifier.issn1613-0073
dc.identifier.urihttp://hdl.handle.net/11250/2482095
dc.description-
dc.description.abstractMainstream metamodelling approaches based on the OMG standards, such as EMF, have a fixed number of modelling levels. Despite their partial acceptance in industry, limitations on the number of levels has led to problems such as lack of flexibility and mixed levels of abstraction. Existing multilevel modelling approaches have already tackled these problems by providing features like deep modelling and linguistic extension. However, these approaches have face challenges like hesitation of adoption by industry due to the lack of an ecosystem which frameworks like EMF already have. In this paper, we (1) propose a conceptual framework for multilevel modelling that tackles such challenges, (2) illustrate the approach with two examples, and (3) present the tool MultEcore, which makes the proposed framework directly compatible with EMF, combining the best of the two worlds of fixed- and multilevel metamodelling approaches.
dc.language.isoeng
dc.relation.ispartofCEUR Workshop Proceedings
dc.relation.urihttp://ceur-ws.org/Vol-1722/p6.pdf
dc.titleMultEcore: Combining the best of fixed-level and multilevel metamodelling
dc.typePeer reviewed
dc.typeJournal article
dc.date.updated2017-10-09T13:16:15Z
dc.identifier.cristin1415697


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