Learning from evolution history to predict future requirement changes

Abstract

Managing the costs and risks of evolution is a challenging problem in the RE community. The challenge lies in the difficulty of analyzing and assessing the proneness to requirement changes across multiple versions, especially when the scale of requirements is large. In this paper, we define a series of metrics to characterize historic evolution information, and propose a novel method for predicting requirements that are likely to evolve in the future based on the metrics. We apply the prediction method to analyze the product updates history through a case study. The empirical results show that this method can provide a tradeoff solution that narrows down the scope of change analysis to a small set of requirements, but it still can retrieve nearly half of the future changes. The results indicate that the defined metrics are sensitive to the history of requirements evolution, and the prediction method can reach a valuable outcome for requirement engineers to balance their workload and risks.