An approach to constructing feature models based on requirements clustering

Feature models have been widely adopted in software reuse to organize the requirements of a set of similar applications in a software domain/product line. However, in most feature-oriented methods, the construction of feature models heavily depends on the domain analysts´ personal understanding, and the work of constructing feature models from the original requirements of sample applications is often tedious and ineffective. This paper proposes a semiautomatic approach to constructing feature models based on requirements clustering, which automates the activities of feature identification, organization and variability modeling to a great extent. The underlying idea of this approach is to analyze the relationships between individual requirements and cluster tight-related requirements into features. With the automatic support of this approach, good quality feature models can be constructed in a more effective way. A case study is also provided to show the feasibility of this approach.