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FASE
2016
Springer

RuleMerger: Automatic Construction of Variability-Based Model Transformation Rules

3 years 17 days ago
RuleMerger: Automatic Construction of Variability-Based Model Transformation Rules
Abstract. Unifying similar model transformation rules into variabilitybased ones can improve both the maintainability and the performance of a model transformation system. Yet, manual identification and unification of such similar rules is a tedious and error-prone task. In this paper, we propose a novel merge-refactoring approach for automating this task. The approach employs clone detection for identifying overlapping rule portions and clustering for selecting groups of rules to be unified. Our instantiation of the approach harnesses state-of-the-art clone detection and clustering techniques and includes a specialized merge construction algorithm. We formally prove correctness of the approach and demonstrate its ability to produce high-quality outcomes in two real-life case-studies.
Daniel Strüber 0001, Julia Rubin, Thorsten Ar
Added 03 Apr 2016
Updated 03 Apr 2016
Type Journal
Year 2016
Where FASE
Authors Daniel Strüber 0001, Julia Rubin, Thorsten Arendt, Marsha Chechik, Gabriele Taentzer, Jennifer Plöger
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