CodeAgent is a multi-agent-based system engineered to revolutionize the process of code review within software development environments. At its core, CodeAgent leverages a suite of Large Language Models (LLMs) that simulate a dynamic, collaborative review process akin to a team of human reviewers. This system is designed to address the complex nature of code reviews that involve multiple dimensions such as code consistency, style adherence, and security vulnerability identification. By employing a diverse group of agents, each with specialized roles and perspectives, CodeAgent mimics the interactive and iterative nature of human-led code reviews. This approach ensures comprehensive coverage and deeper insights into code quality, enhancing the overall software reliability.

A key innovation in CodeAgent is the incorporation of the QA-Checker, a supervision agent tasked with maintaining the relevance and focus of discussions among the other agents. This component is crucial for aligning the agents’ contributions with the central objectives of the code review, effectively managing the flow of interactions to prevent topic drift and ensure coherence. By applying advanced techniques such as the Newton-Raphson method for optimization, the QA-Checker continuously refines the interactions, thereby enhancing the quality of the review outcomes. The effectiveness of CodeAgent has been demonstrated through rigorous testing, showing marked improvements in identifying inconsistencies, vulnerabilities, and non-compliance with coding standards when compared to existing tools. This not only streamlines the code review process but also significantly reduces the workload on human reviewers.

About the Presenter(s):

Daniel is a third-year PhD student at the University of Luxembourg, where he conducts his research under the supervision of Prof. Dr. Tegawendé F. Bissyandé at the TruX group within the Interdisciplinary Centre for Security, Reliability and Trust (SnT). His research focuses primarily on “Patch Explanation,” “Code Review,” and the “Automatic Coding” series of topics. These areas explore innovative methods for enhancing the automation and understanding of code modifications and reviews, aiming to improve software development practices through sophisticated algorithms and tools.

You will get:

• the newest research speech about code review
• possible use cases
• a demo
• brain-storm ideas based on agents

Tags/Labels/Keywords:

• Code Review
• Agents
• LLM
• Autonomous
• Collaborative

Further Information:

• https://daniel4se.github.io/
• https://code-agent-new.vercel.app/#early-access
• https://enoch-ai.com/