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Communication Dans Un Congrès Année : 2014

Neo4EMF, a Scalable Persistence Layer for EMF Models

Résumé

Several industrial contexts require software engineering methods and tools able to handle large -size artifacts. The central idea of abstraction makes model-driven engineering (MDE) a promising approach in such contexts, but current tools do not scale to very large models (VLMs): already the task of storing and accessing VLMs from a persisting support is currently ine cient. In this paper we propose a scalable persistence layer for the de-facto standard MDE framework EMF. The layer exploits the e ciency of graph databases in storing and accessing graph structures, as EMF models are. A preliminary experimentation shows that typical queries in reverse-engineering EMF models have good performance on such persistence layer, compared to le-based backends.
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Dates et versions

hal-00968516 , version 1 (15-04-2014)

Identifiants

Citer

Amine Benelallam, Abel Gómez, Gerson Sunyé, Massimo Tisi, David Launay. Neo4EMF, a Scalable Persistence Layer for EMF Models. ECMFA- European conference on Modeling Foundations and applications, University of York, Apr 2014, York, UK, United Kingdom. pp.230-241, ⟨10.1007/978-3-319-09195-2_15⟩. ⟨hal-00968516⟩
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