Software development projects often struggle with maintaining requirements traceability, as manual traceability matrices are error-prone, time-consuming, and difficult to update as work products change. Existing commercial tools such as IBM DOORS or Helix RM are costly, complex, and require steep learning curves, hindering widespread adoption. In this paper, we propose an effective graph-based requirements traceability management method, which automatically extracts identifiers from work products over the software development life cycle (SDLC) and illustrates their relationships in the form of a requirements traceability graph. The proposed approach enables detection of missing or-mis-specified work products, supports efficient updates of work products, and offers visualization that facilitates verification and validation. By using structured identifiers and configurable keyword types, the system generates traceability links across SDLC phases, eliminating the need for manual rework. Case studies empirically demonstrate that the proposed method reduces effort through automation, improves accuracy, and enhances visibility compared to traditional manual traceability matrices. Performance analysis shows that RTG effectively manages traceability across complex projects, offering scalability and adaptability while mitigating inconsistency risks. This facilitates a more reliable assessment of project success and quality in the domains of software engineering and R&D.
Jong-Min Lee (Sat,) studied this question.