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Neo4EMF, A Scalable Persistence Layer for EMF Models

  • Amine Benelallam
  • Abel Gómez
  • Gerson Sunyé
  • Massimo Tisi
  • David Launay
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8569)

Abstract

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 inefficient. In this paper we propose a scalable persistence layer for the de-facto standard MDE framework EMF. The layer exploits the efficiency 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 file-based backends.

Keywords

Relational Database Large Model Enterprise Architecture Graph Database Eclipse Modeling Framework 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Amine Benelallam
    • 1
  • Abel Gómez
    • 1
  • Gerson Sunyé
    • 1
  • Massimo Tisi
    • 1
  • David Launay
    • 2
  1. 1.AtlanMod, Inria, Mines-Nantes, & LinaFrance
  2. 2.Mia-Software NantesFrance

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