Code generation method based on multi-agent self-reflection framework

Through the code generation method based on the multi-agent self-reflection framework, the problem of unstable code generation quality in the existing technology is solved, and more efficient and intelligent code generation and error repair are achieved.

CN119668580APending Publication Date: 2025-03-21CHONGQING UNIV
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Patent Information

Application Number
CN202411756166.6
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-12-03
Publication Date
2025-03-21

AI Technical Summary

Technical Problem

The existing code generation technology has significant shortcomings in the reliability of code generation quality, the stability of prompts, the efficiency of multi-agent collaboration, and the intelligence of error repair, which limits its application potential in complex programming tasks.

Method used

A code generation method based on the multi-agent self-reflection framework is adopted, and a self-reflection mechanism and pruning optimization mechanism are introduced through steps such as prompt generation, test case generation, code generation and result inspection to ensure the generated code quality and efficiency.

Benefits of technology

It effectively solves the problems of syntax errors, logical defects and semantic incompleteness in code generation, improves the reliability and quality of code generation, and improves the efficiency of multi-agent collaboration and the intelligence level of error repair.

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Abstract

The invention relates to a code generation method based on a multi-agent self-reflection framework, which combines a staged optimization process of prompt generation, test case generation, code generation, result check and code repair, and effectively solves the technical problem of unstable code generation quality in the prior art. By introducing a pruning method to perform quality screening on output of each stage and utilizing an intelligent feedback mechanism to realize efficient error repair and iteration, the code generation accuracy, reliability and efficiency are remarkably improved, and an innovative and efficient technical solution is provided for intelligent code generation of complex programming tasks.
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