SoK: Systematizing Software Artifacts Traceability via Associations, Techniques, and Applications

TL;DR

This paper systematically reviews software artifacts traceability, creating a comprehensive graph of associations, evaluating recovery techniques, and highlighting gaps between research and industrial practice to guide future developments.

Contribution

It constructs the first global traceability graph, evaluates current recovery techniques, and proposes a role-centric framework to bridge research and industrial adoption.

Findings

Severe imbalance favoring code-related links in traceability

Only 37% of studies release code for reproducibility

95% of tools are confined to academic research

Abstract

Software development relies heavily on traceability links between various software artifacts to ensure quality and facilitate maintenance. While automated traceability recovery techniques have advanced for different artifact pairs, the field remains fragmented with an incomplete overview of artifact associations, ambiguous linking techniques, and fragmented knowledge of application scenarios. To bridge these gaps, we conducted a systematic literature review on software traceability recovery to synthesize the linked artifacts, recovery tools, and usage scenarios across the traceability ecosystem. First, we constructed the first global artifacts traceability graph of 23 associations among 22 artifact types, exposing a severe research imbalance that heavily favors code-related links. Second, while recovery techniques are shifting toward deep semantic models, a reproducibility crisis persists (e.g., only 37% of studies released code); to address this, we provided a comprehensive evaluation framework including a technical decision map and standardized benchmarks. Finally, we quantified an industrial adoption gap (i.e., 95% of tools remain confined to academia) and proposed a role-centric framework to dynamically align artifact paths with concrete engineering activities. This review contributes a coherent knowledge framework for artifacts traceability research, identifies current trends, and provides directions for future work.