Code conversion system and method based on multiple agents

By using a multi-agent code conversion system, the problems of complexity and reliability in cross-language development are solved, achieving efficient and flexible code conversion that adapts to different coding styles and long code processing.

CN121832945APending Publication Date: 2026-04-10HEFEI SUXIN MICROELECTRONICS TECHNOLOGY CO LTD
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Patent Information

Application Number
CN202511680027.4
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-11-17
Publication Date
2026-04-10

AI Technical Summary

Technical Problem

Existing code conversion tools suffer from problems such as complexity, time consumption, and error-proneness in cross-language development. They are particularly difficult to adapt to complex structures and different coding styles. Furthermore, AI-based methods lack sufficient data and have limited model intelligence, making it difficult to guarantee the correctness and reliability of the conversion results.

Method used

A multi-agent-based code conversion system is adopted. By inserting block delimiters into the source code for preprocessing, creating code description files, and using multi-agents for module-by-module generation and debugging, the target code is ensured to meet hardware functional requirements and adapt to conversions of various code styles and no mapping relationships.

Benefits of technology

It improves the reliability and quality of code conversion, reduces the pressure of handling long contexts for large models, can handle thousands to tens of thousands of lines of code, adapts to diverse coding styles, and ensures conversion quality through multiple debugging sessions.

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Abstract

The invention provides a multi-agent-based code conversion system and method. The method comprises the following steps: preprocessing an input source code; performing block processing on the source code to obtain source code blocks, obtaining variable information and array size information of the blocks corresponding to the source code, and integrating the variable information and the array size information into complete variable information; fusing the code description file, the code blocks of the source codes and the variable information of the blocks corresponding to the source codes to generate target code blocks; debugging and checking the target code blocks in combination with the source code blocks; the code description file is used for guiding the intelligent agent to establish a jumping type relation in the code conversion process, and it is ensured that the generated target code better meets the actual function requirement of hardware; a block identifier is inserted into a long code to divide the long code into a plurality of blocks, so that the limitation on long code conversion is relieved; codes of different styles can be output by simply adjusting the cue word of the intelligent agent; through multiple times of debugging verification, the conversion quality of the target code is ensured.
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