ISSN No:2250-3676 ----- Crossref DOI Prefix: 10.64771 ----- Impact Factor: 9.625
(Peer Reviewed, Referred & Indexed Journal)
A Retrieval-Augmented Multi-Agent Large Language Model Framework For Autonomous Software Engineering And Intelligent Code GenerationID: 3626 Abstract :The Rapid Advancement Of Large Language Models (LLMs) Has Transformed Modern Software Engineering By Enabling Intelligent Code Generation, Automated Debugging, Software Documentation, Test Case Generation, And Program Optimization. Despite These Remarkable Capabilities, Conventional LLM-based Coding Assistants Frequently Suffer From Hallucinated Code, Outdated Programming Knowledge, Limited Project-level Understanding, Inconsistent Software Architecture, And Inadequate Collaboration Among Multiple Development Activities. These Limitations Reduce The Reliability Of Autonomous Software Engineering Systems When Developing Complex, Large-scale Software Projects That Require Accurate Contextual Reasoning, Repository Awareness, And Continuous Software Maintenance. |
Published:24-2-2025 Issue:Vol. 25 No. 2 (2025) Page Nos:94 - 109 Section:Articles License:This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. How to Cite |