A method for complex functions in low-code platforms based on large model code interpretation and generation

By constructing semantic consistency anchors and a real-time verification mechanism, the problems of inconsistent variable naming, control flow, and data types when generating complex functions on low-code platforms are solved, achieving high-quality and reliable code generation suitable for enterprise-level development.

CN122363700APending Publication Date: 2026-07-10GUANGZHOU ZHUORUI DIGITAL TECHNOLOGY CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
GUANGZHOU ZHUORUI DIGITAL TECHNOLOGY CO LTD
Filing Date
2026-03-16
Publication Date
2026-07-10

AI Technical Summary

Technical Problem

Existing low-code platforms suffer from issues such as non-standard variable naming, contradictory control flow structures, and mismatched data types when generating complex functions, leading to inconsistent results and logical breaks.

Method used

By constructing semantic consistency anchors (SARs), a structured intent graph is built using explicit business entity nodes, operational verb edges, and parameter constraint triples as a unified semantic benchmark for multi-model generation. A semantic alignment checker is introduced for real-time verification, and the consistency of the generated results is verified by performing simulation using a joint abstract syntax tree and lightweight symbols. Finally, optimization is performed using a conflict locator.

Benefits of technology

It significantly improves the context consistency and executability of generated code, reduces debugging costs, and ensures the logical completeness and maintainability of generated results, making it suitable for enterprise-level development scenarios such as financial transactions and industrial automation scripts.

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Abstract

This invention provides a method for generating complex functions on a low-code platform based on large model code interpretation and generation. By capturing and standardizing user input, a structured intent graph containing business entities, operational relationships, parameter constraints, and control flow topology is constructed as a unified semantic anchor. Combined with a pre-defined domain rule base, a semantic alignment validator is designed to achieve multi-dimensional semantic comparison and conflict detection between code and requirements. Code snippets are generated in parallel by multiple models and verified in real time, and semantic conflicts are resolved through local regeneration. By fusing the results of multiple models to construct a joint abstract syntax tree, lightweight symbolic execution is used to simulate the correctness of cross-model code, locate and correct core logical conflicts. This invention significantly improves the consistency, accuracy, and automatic correction capabilities of low-code platform code generation.
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