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Modeling and Multi-Objective Optimization of Quality Attributes in Variability-Rich Software
|Title||Modeling and Multi-Objective Optimization of Quality Attributes in Variability-Rich Software|
|Publication Type||Conference Paper|
|Year of Publication||2012|
|Authors||Olaechea, R., S. Stewart, K. Czarnecki, and D. Rayside|
|Conference Name||International Workshop on Non- functional System Properties in Domain Specific Modeling Languages (NFPinDSML’12)|
|Conference Location||Innsbruck, Austria|
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.