Testing, Understanding, and Optimizing Coding Agents: A Survey on Multi-Agent Systems for Code Generation

PhD Qualifying Examination


Title: "Testing, Understanding, and Optimizing Coding Agents: A Survey on
Multi-Agent Systems for Code Generation"

by

Mr. Zongyi LYU


Abstract:

With the rapid advancement of large language models (LLMs), coding agents have 
emerged as a transformative paradigm for automating software development 
tasks. Among the various instantiations of this paradigm, multi-agent code 
generation systems (MACGS) have demonstrated remarkable potential by 
decomposing complex programming tasks into specialized subtasks delegated to 
dedicated agents. Despite remarkable benchmark performance, the engineering 
foundations of these systems-their reliability, internal mechanisms, and 
optimization pathways-remain poorly understood, posing critical barriers to 
real-world deployment. This survey provides a systematic review of coding 
agents, especially MACGS, through the lens of testing, understanding, and 
optimization, a perspective that reflects the maturation of the field toward 
production-readiness: testing establishes a principled, reproducible 
characterization of system behavior; understanding then transforms empirical 
observations into actionable mechanistic insight; and optimization, grounded 
in that insight, applies targeted interventions that yield principled and 
transferable improvements. Specifically, we first categorize the architectural 
landscape of coding agents, spanning role-based pipelines and adaptive 
frameworks. We then survey different testing methodologies, analysis 
frameworks, and optimization strategies. We conclude by identifying open 
challenges in these perspectives, positioning this survey as both a map of 
current progress and a guide for the research directions that will define the 
next generation of reliable coding agents.


Date:                   Wednesday, 15 July 2026

Time:                   10:30am - 11:30am

Venue:                  Room 3494
                        Lift 25/26

Committee Members:      Prof. Shing-Chi Cheung (Supervisor)
                        Dr. Shuai Wang (Co-supervisor)
                        Prof. Raymond Wong (Chairperson)
                        Dr. Binhang Yuan