Surveying the Corpus of Model Resolution Strategies for Metamodel Evolution

Modeling languages evolve regularly. Companies need to maintain all those models that are used in running projects, which can cause these projects to fall back in their schedules. Since 10 years research addresses this issue with approaches for automating co-evolution. The dominant core of these approaches are model resolution strategies. They define 1) how models have to be changed in reaction to specific metamodel changes, 2) what degree of automation can be reached, and 3) to what extent the user can control the resolution outcome. In this paper, we survey existing co-evolution approaches and analyze model resolution strategies. We present a corpus of more than 200 resolution strategies for 116 types of metamodel changes and discuss degree of automation and choices that users have today.

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