A Network Interference Approach to Analyzing Change Propagation in Requirements

Abstract

Requirements are frequently revised due to iterative nature of the design process. If not properly managed, these changes may result in financial and time losses due to undesired propagating effect. Currently, predictive models to assist designers in making well informed decisions prior to change implementation do not exist. Current modeling methods for managing requirements do not offer formal reasoning necessary to manage requirement change and its propagation. The ability to predict change during the design process may lead to valuable insights in designing artifacts more efficiently by minimizing unanticipated changes due to mismanaged requirement changes. Two research questions (RQs) are addressed in this paper: (1) How do complex network metrics of requirements, considering both node and edge interference, influence the predictability of requirement change propagation across different case studies? (2) How does the performance of the complex network metrics approach compare to the Refined Automated Requirement Change Propagation Prediction (R-ARCPP) tool, developed from our prior study, in accurately predicting requirement change propagation? Requirement changes are simulated by applying the node interference and the edge interference methods. It is found that complex network metrics can be used to predict requirement change propagation. Based on the studied data, the performance ranking of metrics is characterized by edge interference across the changes. The results reveal that the R-ARCPP tool ranks higher than comparatively performing complex network metrics.