Conflict Detection for Edits on Extended Feature Models using Symbolic Graph Transformation

Frederik Deckwerth
(TU Darmstadt)
Géza Kulcsár
(TU Darmstadt)
Malte Lochau
(TU Darmstadt)
Gergely Varró
(TU Darmstadt)
Andy Schürr
(TU Darmstadt)

Feature models are used to specify variability of user-configurable systems as appearing, e.g., in software product lines. Software product lines are supposed to be long-living and, therefore, have to continuously evolve over time to meet ever-changing requirements. Evolution imposes changes to feature models in terms of edit operations. Ensuring consistency of concurrent edits requires appropriate conflict detection techniques. However, recent approaches fail to handle crucial subtleties of extended feature models, namely constraints mixing feature-tree patterns with first-order logic formulas over non-Boolean feature attributes with potentially infinite value domains. In this paper, we propose a novel conflict detection approach based on symbolic graph transformation to facilitate concurrent edits on extended feature models. We describe extended feature models formally with symbolic graphs and edit operations with symbolic graph transformation rules combining graph patterns with first-order logic formulas. The approach is implemented by combining eMoflon with an SMT solver, and evaluated with respect to applicability.

In Julia Rubin and Thomas Thüm: Proceedings 7th International Workshop on Formal Methods and Analysis in Software Product Line Engineering (FMSPLE 2016), Eindhoven, The Netherlands, April 3, 2016, Electronic Proceedings in Theoretical Computer Science 206, pp. 17–31.
Published: 28th March 2016.

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