| Issue |
EPJ Web Conf.
Volume 337, 2025
27th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2024)
|
|
|---|---|---|
| Article Number | 01066 | |
| Number of page(s) | 6 | |
| DOI | https://doi.org/10.1051/epjconf/202533701066 | |
| Published online | 07 October 2025 | |
https://doi.org/10.1051/epjconf/202533701066
Leveraging Large Language Models for Enhanced Code Review
GSI Helmholtzzentrum für Schwerionenforschung GmbH, Planckstraße 1, 64291 Darmstadt
* e-mail: a.rybalchenko@gsi.de
** e-mail: m.al-turany@gsi.de
Published online: 7 October 2025
This paper presents an innovative approach to software code review using Large Language Models (LLMs), incorporating open-source models. We introduce Pearbot, an open-source tool that implements a comprehensive code review workflow using open-weights LLMs, featuring multi-agent capabilities and reflection mechanisms. Our approach demonstrates the potential for LLMs to identify code issues and suggest improvements that may be overlooked by traditional automated analysis tools, while addressing common limitations of LLM-based code review through a multi-agent architecture.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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