Applying Semantic Web Technology to Feature Modeling

Feature models are models used to capture differences and com­monalities between software features, enabling the representation of variability within software. There are many variations of fea­ture models and different notations are often used to represent the same information. Currently support for validating or integrating feature models is missing. In this paper, we provide an ontology framework for feature mod­eling which consists of an ontology that formally provides a specification for feature models. In addition, we provide means to integrate segmented feature models and provide a rule based model consistency check and conflict detection. We use SWRL rules to implement the rules and a DL reasoner to evaluate the rules and infer extra interesting informa­tion regarding the variability of the software.
Publication Reference
Abo Zaid, L., Kleinermann, F., De Troyer, O.: Applying Semantic Web Technology to Feature Modeling. In: The 24th Annual ACM Symposium on Applied Computing, The Semantic Web and Applications (SWA) Track, March 2009.