Automatically Tracing Dependability Requirements via Term-Based Relevance Feedback

In many critical industrial information systems, tracking a dependability requirement is instrumental to the verification and validation (V&V) of security, privacy, and other dependability concerns. Automated traceability tools employ information retrieval methods to recover candidate links, which saves much manual effort. Integrating relevance feedback (RF) could potentially improve the retrieval effectiveness by soliciting the relevance judgments on a subset of the retrieval results and then incorporating the feedback into subsequent retrieval. However, little is known about how to use RF to trace dependability requirements. In this paper, we propose a novel term-based RF algorithm that leverages the term usage context to recommend positive and negative feedback. Experiments on two software datasets show that our algorithm significantly outperforms the contemporary link-based RF tracing method. Our work not only contributes a new solution to dependability requirements' V&V, but also enables further automation to reduce the manual effort in the development life cycle of dependable industrial systems.