This paper proposes an approach to analyzing commonality and variability of features using semantic-based analysis criteria which is able to change feature model of specific domain to featureontology. For the purpose, first feature attributes were made, create a feature model following the Meta model, transform it into feature-ontology, and save it to Meta feature-ontology repository. Henceforth, when we construct a feature model of the same product line, commonality and variability of the features can be extracted, comparing it with Meta feature ontology through a semantic similarity analysis method, which is proposed. Furthermore, a tool for a semantic similarity-comparing algorithm was implemented and an experiment with an electronic approval system domain in order to show the efficiency of the approach Was conducted.

A Meta feature model can definitely be created through this approach, to construct a high-quality feature model based on common understanding of a feature. The main contributions are a formulating a method of extracting commonality and variability from features using ontology based on semantic similarity mapping and a enhancement of reusability of feature model.