Natural Language Processing for Requirements Traceability
Not on the map. Why?
Abstract (arXiv)
Traceability, the ability to trace relevant software artifacts to support reasoning about the quality of the software and its development process, plays a crucial role in requirements and software engineering, particularly for safety-critical systems. In this chapter, we provide a comprehensive overview of the representative tasks in requirement traceability for which natural language processing (NLP) and related techniques have made considerable progress in the past decade. We first present the definition of traceability in the context of requirements and the overall engineering process, as well as other important concepts related to traceability tasks. Then, we discuss two tasks in detail, including trace link recovery and trace link maintenance. We also introduce two other related tasks concerning when trace links are used in practical contexts. For each task, we explain the characteristics of the task, how it can be approached through NLP techniques, and how to design and conduct the experiment to demonstrate the performance of the NLP techniques. We further discuss practical considerations on how to effectively apply NLP techniques and assess their effectiveness regarding the data set collection, the metrics selection, and the role of humans when evaluating the NLP approaches. Overall, this chapter prepares the readers with the fundamental knowledge of designing automated traceability solutions enabled by NLP in practice.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 17 May 2024.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2025: 3; 2026: 2.
5 papers.
- 2025Past, Present, and Future of Bug Tracking in the Generative AI Eracited by 4
- 2025A Blueprint for AI-Driven Software Quality: Integrating LLMs with Established Standardscited by 1
- 2025Reconsidering Requirements Engineering: Human-AI Collaboration in AI-Native Software Developmentcited by 0
- 2026Choose Your Own Adventure: Non-Linear AI-Assisted Programming with EvoGraphcited by 0
- 2026TraceDev: A Traceability-Driven Multi-agent Framework for Requirement-to-Code Developmentcited by 0
- 2026TraceDev: A Traceability-Driven Multi-agent Framework for Requirement-to-Code Development21 Jul 2026
- 2026Choose Your Own Adventure: Non-Linear AI-Assisted Programming with EvoGraph20 Apr 2026
- 2025Past, Present, and Future of Bug Tracking in the Generative AI Era9 Oct 2025
- 2025Reconsidering Requirements Engineering: Human-AI Collaboration in AI-Native Software Development5 Oct 2025
- 2025A Blueprint for AI-Driven Software Quality: Integrating LLMs with Established Standards19 May 2025