mlsanityData to 14 Oct 2026

Prompt Engineering for Requirements Engineering: A Literature Review and Roadmap

arXiv 2507.07682 ↗First posted 10 Jul 2025cs.SEcited by 2

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Abstract (arXiv)

Advancements in large language models (LLMs) have led to a surge of prompt engineering (PE) techniques that can enhance various requirements engineering (RE) tasks. However, current LLMs are often characterized by significant uncertainty and a lack of controllability. This absence of clear guidance on how to effectively prompt LLMs acts as a barrier to their trustworthy implementation in the RE field. We present the first roadmap-oriented systematic literature review of Prompt Engineering for RE (PE4RE). Following Kitchenham's and Petersen's secondary-study protocol, we searched six digital libraries, screened 867 records, and analyzed 35 primary studies. To bring order to a fragmented landscape, we propose a hybrid taxonomy that links technique-oriented patterns (e.g., few-shot, Chain-of-Thought) to task-oriented RE roles (elicitation, validation, traceability). Two research questions, with five sub-questions, map the tasks addressed, LLM families used, and prompt types adopted, and expose current limitations and research gaps. Finally, we outline a step-by-step roadmap showing how today's ad-hoc PE prototypes can evolve into reproducible, practitioner-friendly workflows.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). First posted on arXiv 10 Jul 2025.

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Citing papers per year: 2026: 2.

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  1. 2026BT-APE: A Computationally Light Backtracking Approach to Automatic Prompt Engineering for Requirements Classification ↗
  2. 2025Are Prompts All You Need? Evaluating Prompt-Based Large Language Models (LLM)s for Software Requirements Classification
  3. 2026Evaluating LLM-Based Goal Extraction in Requirements Engineering: Prompting Strategies and Their Limitations
  4. 2024Leveraging Graph-RAG and Prompt Engineering to Enhance LLM-Based Automated Requirement Traceability and Compliance Checks
  5. 2025A Taxonomy of Prompt Defects in LLM Systems
  6. 2024Do Advanced Language Models Eliminate the Need for Prompt Engineering in Software Engineering?
  7. 2026REprompt: Prompt Generation for Intelligent Software Development Guided by Requirements Engineering ↗
  8. 2026Prompt-Driven Code Summarization: A Systematic Literature Review