Multi-Agent Debate (MAD) systems enable structured collaboration between specialized LLM-based agents to tackle complex software engineering tasks through iterative refinement.

• MAD leverages diverse expertise through role-specific agents working together
• The system promotes dynamic interactions and structured decision-making processes
• Research focuses on practical applications in code summarization and translation
• Demonstrates how collaborative AI approaches can solve problems requiring multi-step reasoning

This research matters for Engineering teams by providing a framework to automate and improve complex software engineering tasks that traditionally required human expertise across multiple domains.

Is Multi-Agent Debate (MAD) the Silver Bullet? An Empirical Analysis of MAD in Code Summarization and Translation