On-Demand Cluster Analysis for Product Line Functional Requirements

We propose an on-demand clustering framework for analyzing the functional requirements in a product line. Our approach is novel in that the objects to be clustered capture the domain's action themes at a primitive level, and the essential attributes are uncovered via semantic analysis. We provide automatic support to complement domain analysis by quickly identifying important entities and functionalities. A second contribution is our recognition of stakeholders' different goals in cluster analysis, e.g., feature identification for users versus system decomposition for designers. We thus advance the literature by examining requirements clusters that overlap and those causing a minimal information loss, and by facilitating the discovery of product line variabilities. A proof-of-concept example is presented to show the applicability and usefulness of our approach.