Title
Conflict Detection For Edits On Extended Feature Models Using Symbolic Graph Transformation
Abstract
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.
Year
DOI
Venue
2016
10.4204/EPTCS.206.3
ELECTRONIC PROCEEDINGS IN THEORETICAL COMPUTER SCIENCE
DocType
Issue
ISSN
Journal
206
2075-2180
Citations 
PageRank 
References 
2
0.37
20
Authors
5
Name
Order
Citations
PageRank
Frederik Deckwerth1423.70
Géza Kulcsár2184.07
Malte Lochau354835.64
Gergely Varró440336.67
Andy Schürr52195230.25