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- W1615444493 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." @default.
- W1615444493 created "2016-06-24" @default.
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- W1615444493 date "2014-01-01" @default.
- W1615444493 modified "2023-10-06" @default.
- W1615444493 title "Neo4EMF, A Scalable Persistence Layer for EMF Models" @default.
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- W1615444493 doi "https://doi.org/10.1007/978-3-319-09195-2_15" @default.
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