Improving requirements tracing via information retrieval

TLDR

The study proposes framing requirements tracing as an information‑retrieval problem to improve recall and precision, thereby reducing missed and irrelevant traceability links. We adapted and implemented several IR algorithms and evaluated them against a senior analyst’s manual tracing and an existing tracing tool. Results show the IR approach retrieves a higher percentage of links than analysts, in less time, while maintaining comparable signal‑to‑noise levels.

Abstract

We present an approach for improving requirements tracing based on framing it as an information retrieval (IR) problem. Specifically, we focus on improving recall and precision in order to reduce the number of missed traceability links as well as to reduce the number of irrelevant potential links that an analyst has to examine when performing requirements tracing. Several IR algorithms were adapted and implemented to address this problem. We evaluated our algorithms by comparing their results and performance to those of a senior analyst who traced manually as well as with an existing requirements tracing tool. Initial results suggest that we can retrieve a significantly higher percentage of the links than analysts, even when using existing tools, and do so in much less time while achieving comparable signal-to-noise levels.