Leveraging Large Language Models for Enhanced Code Review

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.

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Publication Details

Journal
EPJ Web of Conferences
Published
2025-01-01
DOI
https://doi.org/10.1051/epjconf/202533701066
Citations
1
Primary Topic
Software Engineering Research
Type
article
Field-Weighted Citation Impact
3.25
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article

Leveraging Large Language Models for Enhanced Code Review

M. Al-Turany, Alexey Rybalchenko
1 citations
EPJ Web of Conferences
Software Engineering Research
3.25
article

Leveraging Large Language Models for Enhanced Code Review

M. Al-Turany, Alexey Rybalchenko
article en
1 citations

Abstract

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.

EPJ Web of ConferencesVol. 337
GSI Helmholtz Centre for Heavy Ion Research (DE)
Openalex Percentile: Top 6%
Software Engineering Research
3.25
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