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February 5, 2026

Leveraging Large Language Models for Enhanced Code Review

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Authors

ARAlexey RybalchenkoMAMohammad Al-Turany

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Overview

Innovative approach enhances code review using large language models in software development, suggesting improvements.

Key Points

  • The aim is to improve software code review processes by using large language models to identify issues and suggest enhancements.
  • Developed Pearbot, an open-source tool for code reviews
  • Integrated open-weights large language models
  • Implemented multi-agent capabilities
  • Incorporated reflection mechanisms for improvement suggestions
  • Demonstrated LLMs' ability to identify code issues
  • Showed improvements that traditional automated tools might overlook
  • Addressed common limitations of LLM-based review using a multi-agent architecture

Cite This Study

Rybalchenko et al. (2025) studied this question.

synapsesocial.com/papers/6984349af1d9ada3c1fb2ed6https://doi.org/10.1051/epjconf/202533701066/pdf
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Leveraging Large Language Models for Enhanced Code Review2025
  2. 2AI-powered Code Review with LLMs: Early Results2024 · 6 citations
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  4. 4Fine-tuning Large Language Models to Improve Accuracy and Comprehensibility of Automated Code Review2024 · 28 citations
  5. 5A Survey on Large Language Models for Code Generation2024 · 61 citations