Towards Evaluation Guidelines for Empirical Studies Involving LLMs

In the short period since the release of ChatGPT, large language models (LLMs) have changed the software engineering research landscape. While there are numerous opportunities to use LLMs for supporting research or software engineering tasks, solid science needs rigorous empirical evaluations. However, so far, there are no specific guidelines for conducting and assessing studies involving LLMs in software engineering research. Our focus is on empirical studies that either use LLMs as part of the research process or studies that evaluate existing or new tools that are based on LLMs. This paper contributes the first set of holistic guidelines for such studies. Our goal is to start a discussion in the software engineering research community to reach a common understanding of our standards for high-quality empirical studies involving LLMs.

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Publication Details

Published
2025-05-03
DOI
https://doi.org/10.1109/wsese66602.2025.00011
Citations
3
Primary Topic
Semantic Web and Ontologies
Type
article
Field-Weighted Citation Impact
7.44
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article

Towards Evaluation Guidelines for Empirical Studies Involving LLMs

Sebastian Baltes, Stefan Wagner, Davide Falessi, Marvin Muñoz Barón
3 citations
Semantic Web and Ontologies
7.44
article

Towards Evaluation Guidelines for Empirical Studies Involving LLMs

Sebastian Baltes, Stefan Wagner, Davide Falessi, Marvin Muñoz Barón
article en
3 citations

Abstract

In the short period since the release of ChatGPT, large language models (LLMs) have changed the software engineering research landscape. While there are numerous opportunities to use LLMs for supporting research or software engineering tasks, solid science needs rigorous empirical evaluations. However, so far, there are no specific guidelines for conducting and assessing studies involving LLMs in software engineering research. Our focus is on empirical studies that either use LLMs as part of the research process or studies that evaluate existing or new tools that are based on LLMs. This paper contributes the first set of holistic guidelines for such studies. Our goal is to start a discussion in the software engineering research community to reach a common understanding of our standards for high-quality empirical studies involving LLMs.

University of Rome Tor Vergata (IT), Heilbronn University (DE), University of Bayreuth (DE), Technical University of Munich (DE)
Openalex Percentile: Top 3%
Semantic Web and Ontologies
7.44
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