Investigating the Use of LLMs for Evidence Briefings Generation in Software Engineering
Abstract
[Context] An evidence briefing is a concise and objective transfer medium that can present the main findings of a study to software engineers in the industry. Although practitioners and researchers have deemed Evidence Briefings useful, their production requires manual labor, which may be a significant challenge to their broad adoption. [Goal] The goal of this registered report is to describe an experimental protocol for evaluating LLM-generated evidence briefings for secondary studies in terms of content fidelity, ease of understanding, and usefulness, as perceived by researchers and practitioners, compared to human-made briefings. [Method] We developed an RAG-based LLM tool to generate evidence briefings. We used the tool to automatically generate two evidence briefings that had been manually generated in previous research efforts. We designed a controlled experiment to evaluate how the LLM-generated briefings compare to the human-made ones regarding perceived content fidelity, ease of understanding, and usefulness. [Results] To be reported after the experimental trials. [Conclusion] Depending on the experiment results.
Cite
@article{arxiv.2507.15828,
title = {Investigating the Use of LLMs for Evidence Briefings Generation in Software Engineering},
author = {Mauro Marcelino and Marcos Alves and Bianca Trinkenreich and Bruno Cartaxo and Sérgio Soares and Simone D. J. Barbosa and Marcos Kalinowski},
journal= {arXiv preprint arXiv:2507.15828},
year = {2025}
}
Comments
ESEM 2025 Registered Report with an IPA (In Principle Acceptance) for the Empirical Software Engineering journal