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Abstract-With increased adoption of Model-Driven Engineering, the number of related artefacts in use, such as models, greatly increase. To be able to tackle this dimension of scalability in MDE, we propose to treat the artefacts as data, and apply various techniques ranging from information retrieval to machine learning to analyse and manage them in a scalable and efficient way.

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