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RuleMerger: Automatic Construction of Variability-Based Model Transformation Rules

dc.contributor.authorStrüber, Daniel
dc.contributor.authorRubin, Julia
dc.contributor.authorArendt, Thorsten
dc.contributor.authorChechik, Marsha
dc.contributor.authorTaentzer, Gabriele
dc.contributor.authorPlöger, Jennifer
dc.contributor.editorJürjens, Jan
dc.contributor.editorSchneider, Kurt
dc.date.accessioned2017-06-21T19:18:11Z
dc.date.available2017-06-21T19:18:11Z
dc.date.issued2017
dc.description.abstractWe present a summary of our paper of the same title, published in the proceedings of the International Conference on Fundamental Approaches to Software Engineering (FASE) 2016. Unifying similar model transformation rules into variability-based ones can improve both the main- tainability 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 work, we propose a novel merging 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.en
dc.identifier.isbn978-3-88579-661-9
dc.identifier.pissn1617-5468
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofSoftware Engineering 2017
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-267
dc.titleRuleMerger: Automatic Construction of Variability-Based Model Transformation Rulesen
dc.typeText/Conference Paper
gi.citation.publisherPlaceBonn
gi.citation.startPage135
gi.conference.date21.-24. Februar 2017
gi.conference.locationHannover
gi.conference.sessiontitleDomain Specific Languages

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