An approach for prioritizing software features based on node centrality in probability network

Abstract

Due to the increasing complexity of software products as well as the restriction of the development budget and time, requirements prioritization, i.e., selecting more crucial requirements to be designed and developed firstly, has become increasingly important in the software development lifetime. Considering the fact that a feature in a feature model can be viewed as a set of closely related requirements, feature prioritization will contribute to requirements prioritization to a large extent. Therefore, how to measure the priority of features within a feature model becomes an important issue in requirements analysis. In this paper, a software feature prioritization approach is proposed, which utilizes the dependencies between features to build a feature probability network and measures feature prioritization through the nodes centrality in the network. Experiments conducted on real world feature models show that the proposed approach can accurately prioritize features in feature models.