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Prompt me: intelligent software agent for requirements engineering - a vision paper
Date
2025
Abstract
[Context and Motivation] Software engineers can interact with users through digital channels (e.g., online forums) to exchange information about software products and achieve their requirements engineering (RE) goals. However, conducting RE manually is challenging due to the large number of users and the volume of their online feed-back. [Question/Problem] Previous work has proposed tools to automatically extract useful information from online feedback (e.g., feature requests); however, these tools suffer from three major limitations: (i) an overlooked RE perspective in their design and evaluation; (ii) insuffcient functional and performance capabilities; and (iii) missing evaluations of their ability to address RE needs. [Principal Idea/Results] This paper presents a vision for an intelligent RE software agent designed to overcome these limitations. Specifically, our vision explores how RE can
guide the design and evaluation of software agents powered by large language models (LLMs), proposes empirical assessments of LLMs for RE usage and the agent’s ability to meet RE needs. [Contributions] Our contribution is threefold: (i) a vision for an RE agent, (ii) identification of key challenges, and (iii) a roadmap to address current limitations.
Supervisor
Description
This is a preprint of a paper accepted for presentation at the 31st International Working Conference on Requirement Engineering: Foundation for Software Quality (REFSQ 2025). Please note that this version may differ slightly from the final published version. Published version availablehttps://doi.org/10.1007/978-3-031-88531-0_17
Publisher
Springer
Citation
Hess, A., Susi, A. (eds) Requirements Engineering: Foundation for Software Quality. REFSQ 2025. Lecture Notes in Computer Science, vol 15588.