LLM-Based Multi-Agent Systems for Software Engineering: Literature Review, Vision, and the Road Ahead

Singapore Management University

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Abstract

Integrating Large Language Models (LLMs) into autonomous agents marks a significant shift in the research landscape by offering cognitive abilities that are competitive with human planning and reasoning. This article explores the transformative potential of integrating Large Language Models into Multi-Agent (LMA) systems for addressing complex challenges in software engineering (SE). By leveraging the collaborative and specialized abilities of multiple agents, LMA systems enable autonomous problem-solving, improve robustness, and provide scalable solutions for managing the complexity of real-world software projects. In this article, we conduct a systematic review of recent primary studies to map the current…

Citation impact

105
total citations
FWCI
268.26
Percentile
100%
References
84
Citations per year

Authors

3

Topics & keywords

Keywords
  • Computer science
  • Scalability
  • Software engineering
  • Systems development life cycle
  • Transformative learning
  • Software
  • Software development
  • Systems engineering
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