Logo des Repositoriums
 
Konferenzbeitrag

RuleMerger: Automatic Construction of Variability-Based Model Transformation Rules

Lade...
Vorschaubild

Volltext URI

Dokumententyp

Text/Conference Paper

Zusatzinformation

Datum

2017

Zeitschriftentitel

ISSN der Zeitschrift

Bandtitel

Verlag

Gesellschaft für Informatik e.V.

Zusammenfassung

We 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.

Beschreibung

Strüber, Daniel; Rubin, Julia; Arendt, Thorsten; Chechik, Marsha; Taentzer, Gabriele; Plöger, Jennifer (2017): RuleMerger: Automatic Construction of Variability-Based Model Transformation Rules. Software Engineering 2017. Bonn: Gesellschaft für Informatik e.V.. PISSN: 1617-5468. ISBN: 978-3-88579-661-9. pp. 135. Domain Specific Languages. Hannover. 21.-24. Februar 2017

Schlagwörter

Zitierform

DOI

Tags