Flexible and scalable consistency checking on product line variability models
Author(s) -
Michael Vierhauser,
Paul Grünbacher,
Alexander Egyed,
Rick Rabiser,
Wolfgang Heider
Publication year - 2010
Publication title -
citeseer x (the pennsylvania state university)
Language(s) - English
Resource type - Conference proceedings
DOI - 10.1145/1858996.1859009
Subject(s) - consistency (knowledge bases) , scalability , computer science , product (mathematics) , software product line , source lines of code , consistency model , code (set theory) , product line , distributed computing , data mining , data consistency , programming language , software , database , artificial intelligence , software development , mathematics , engineering , set (abstract data type) , manufacturing engineering , geometry
The complexity of product line variability models makes it hard to maintain their consistency over time regardless of the modeling approach used. Engineers thus need support for detecting and resolving inconsistencies. We describe experiences of applying a tool-supported approach for incremental consistency checking on variability models. Our approach significantly improves the overall performance and scalability compared to batch-oriented techniques and allows providing immediate feedback to modelers. It is extensible as new consistency constraints can easily be added. Furthermore, the approach is flexible as it is not limited to variability models and it also checks the consistency of the models with the underlying code base of the product line. We report the results of a thorough evaluation based on real-world product line models and discuss lessons learned.
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