Prompt Engineering Guidelines for Using Large Language Models in Requirements Engineering
Paper i proceeding, 2026

The rapid emergence of generative AI models like Large Language Models (LLMs) has demonstrated its utility across various activities, including within Requirements Engineering (RE). Ensuring the quality and accuracy of LLM-generated output is critical, with prompt engineering serving as a key technique to guide model responses. However, existing literature provides limited guidance on how prompt engineering can be leveraged, specifically for RE activities. The objective of this study is to explore the applicability of existing prompt engineering guidelines for the effective usage of LLMs within RE. To achieve this goal, we began by conducting a systematic review of primary literature to compile a non-exhaustive list of prompt engineering guidelines. Then, we conducted interviews with RE experts to present the extracted guidelines and gain insights on the advantages and limitations of their application within RE. Our literature review indicates a shortage of prompt engineering guidelines for domain-specific activities, specifically for RE. Our proposed mapping contributes to addressing this shortage. We conclude our study by identifying an important future line of research within this field.

Generative AI

Large Language Models

Guidelines

Prompt Engineering

Requirements Engineering

Författare

Krishna Ronanki

Göteborgs universitet

Chalmers, Data- och informationsteknik, Interaktionsdesign och Software Engineering

Simon Arvidsson

Student vid Chalmers

Johan Axell

Student vid Chalmers

Lecture Notes in Computer Science

0302-9743 (ISSN) 1611-3349 (eISSN)

Vol. 16083 LNCS 245-262
9783032042064 (ISBN)

51st Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2025
Salerno, Italy,

Ämneskategorier (SSIF 2025)

Programvaruteknik

DOI

10.1007/978-3-032-04207-1_17

Mer information

Senast uppdaterat

2025-11-18