Towards LLM-augmented multiagent systems for agile software engineering

A cognitive multi-agent ecosystem designed for efficient software engineering using Agile methodologies can significantly improve software development processes. Key components include the integration of Multi-Agent Systems (MAS) and Large Language Models (LLMs), utilizing Dynamic Context techniques...

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Bibliographic Details
Published in:IEEE/ACM International Conference on Automated Software Engineering : [proceedings] pp. 2476 - 2477
Main Authors: Chudziak, Jaroslaw A., Cinkusz, Konrad
Format: Conference Proceeding
Language:English
Published: ACM 27.10.2024
Subjects:
Agile software development
CogniSim
Collaboration Automation
Computational modeling
Ecosystems
Large language models
methodologies
Multi-agent systems
Organizations
Problem-solving
SAFe
Software
Software engineering
Unified modeling language
ISSN:2643-1572
Online Access:Get full text
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Summary:A cognitive multi-agent ecosystem designed for efficient software engineering using Agile methodologies can significantly improve software development processes. Key components include the integration of Multi-Agent Systems (MAS) and Large Language Models (LLMs), utilizing Dynamic Context techniques for agent profiling, and Theory of Mind to enhance collaboration. The CogniSim Ecosystem analyzes problems, proposes solutions, constructs and validates plans, and coordinates specialized agents playing roles such as developers, executors, quality checkers, and methodology reviewers. These agents produce documentation, models, and diagrams (e.g., UML) while adhering to predefined quality and performance measures. The ecosystem also simulates the impact of various team configurations on problem-solving effectiveness, helping organizations identify optimal team structures. Case studies and simulations demonstrate its practical applications.CCS CONCEPTS* Computing methodologies → Multi-agent systems; * Software and its engineering → Agile software development.
ISSN:2643-1572
DOI:10.1145/3691620.3695336