Abstract
Requirements traceability (RT) links requirements to the corresponding source code entities, which implement them. Information Retrieval (IR) based RT links recovery approaches are often used to automatically recover RT links. However, such approaches exhibit low accuracy, in terms of precision, recall, and ranking. This paper presents an approach (CoChaIR), complementary to existing IR-based RT links recovery approaches. CoChaIR leverages historical co-change information of files to improve the accuracy of IR-based RT links recovery approaches. We evaluated the effectiveness of CoChaIR on three datasets, i.e., iTrust, Pooka, and SIP Communicator. We compared CoChaIR with two different IR-based RT links recovery approaches, i.e., vector space model and Jensen-Shannon divergence model. Our study results show that CoChaIR significantly improves precision and recall by up to 12.38% and 5.67% respectively; while decreasing the rank of true positive links by up to 48% and reducing false positive links by up to 44%.