Software product lines: practices and patterns
Software product lines: practices and patterns
Software Product Line Engineering: Foundations, Principles and Techniques
Software Product Line Engineering: Foundations, Principles and Techniques
Selecting highly optimal architectural feature sets with Filtered Cartesian Flattening
Journal of Systems and Software
Approaching Non-functional Properties of Software Product Lines: Learning from Products
APSEC '10 Proceedings of the 2010 Asia Pacific Software Engineering Conference
Scalable Prediction of Non-functional Properties in Software Product Lines
SPLC '11 Proceedings of the 2011 15th International Software Product Line Conference
Automated reasoning on feature models
CAiSE'05 Proceedings of the 17th international conference on Advanced Information Systems Engineering
Software Abstractions: Logic, Language, and Analysis
Software Abstractions: Logic, Language, and Analysis
Predicting performance via automated feature-interaction detection
Proceedings of the 34th International Conference on Software Engineering
Extending alloy with partial instances
ABZ'12 Proceedings of the Third international conference on Abstract State Machines, Alloy, B, VDM, and Z
SPL Conqueror: Toward optimization of non-functional properties in software product lines
Software Quality Control
Variability in software: state of the art and future directions
FASE'13 Proceedings of the 16th international conference on Fundamental Approaches to Software Engineering
Multi-objective test generation for software product lines
Proceedings of the 17th International Software Product Line Conference
Visualization and exploration of optimal variants in product line engineering
Proceedings of the 17th International Software Product Line Conference
Clafer tools for product line engineering
Proceedings of the 17th International Software Product Line Conference co-located workshops
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Variability-rich software, such as software product lines, offers optional and alternative features to accommodate varying needs of users. Designers of variability-rich software face the challenge of reasoning about the impact of selecting such features on the quality attributes of the resulting software variant. Attributed feature models have been proposed to model such features and their impact on quality attributes, but existing variability modelling languages and tools have limited or no support for such models and the complex multi-objective optimization problem that arises. This paper presents ClaferMoo, a language and tool that addresses these shortcomings. ClaferMoo uses type inheritance to modularize the attribution of features in feature models and allows specifying multiple optimization goals. We evaluate an implementation of the language on a set of attributed feature models from the literature, showing that the optimization infrastructure can handle small-scale feature models with about a dozen features within seconds.