Prompt Engineering for Requirements Engineering: A Literature Review and Roadmap

TL;DR

This paper systematically reviews prompt engineering techniques for requirements engineering, proposing a taxonomy and roadmap to guide the development of reproducible, practitioner-friendly LLM-based RE workflows.

Contribution

It provides the first structured literature review and taxonomy linking prompt techniques to RE tasks, along with a practical roadmap for future development.

Findings

Identified key prompt techniques used in RE tasks

Mapped LLM families and prompt types to RE roles

Outlined research gaps and future directions

Abstract

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.