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Erschienen in:
2015 | OriginalPaper | Buchkapitel
A Variability-Based Approach to Reusable and Efficient Model Transformations
verfasst von : Daniel Strüber, Julia Rubin, Marsha Chechik, Gabriele Taentzer
Erschienen in: Fundamental Approaches to Software Engineering
Verlag: Springer Berlin Heidelberg
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Large model transformation systems often contain transformation rules that are substantially similar to each other, causing performance bottlenecks for systems in which rules are applied nondeterministically, as long as one of them is applicable. We tackle this problem by introducing
variability-based graph transformations
. We formally define variability-based rules and contribute a novel match-finding algorithm for applying them. We prove correctness of our approach by showing its equivalence to the classic one of applying the rules individually, and demonstrate the achieved performance speed-up on a realistic transformation scenario.