AI-based test requirement analysis and use case generation method and system

By constructing logical flow graphs for both new and old versions and performing graph isomorphic matching, the semantic decay problem of existing test cases under frequent requirement changes in government software was solved, enabling adaptive evolution and logical inheritance of test assets and reducing regression testing maintenance costs.

CN122045069BActive Publication Date: 2026-07-07HUACI GUOSOFT TECH SERVICE NANJING CO LTD
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Patent Information

Application Number
CN202610476968.4
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2026-04-13
Publication Date
2026-07-07
Estimated Expiration
2046-04-13

AI Technical Summary

Technical Problem

Existing AI-based test case generation technologies cannot effectively adapt to the needs of existing test cases and new versions in scenarios with high-frequency iteration of government software requirements, resulting in waste of test assets and incomplete regression test coverage.

Method used

By constructing a logical flow diagram of the requirements for both new and old versions and performing graph isomorphic matching, the overall impact area of ​​requirement changes can be accurately identified, enabling the adaptive evolution of existing test cases, including path mapping, geometric transformation, and expansion optimization, to generate the final set of test cases.

Benefits of technology

It effectively solves the semantic decay problem of existing test cases, preserves testers' experience, reduces regression testing maintenance costs, and ensures the logical inheritance between new and old test cases and the continuous activation of test assets.

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Abstract

The application relates to the technical field of software testing, and discloses a test requirement analysis and use case generation method and system based on AI, which comprises the following steps: acquiring a new and old version requirement document set, constructing a corresponding logic flow graph, generating a logic increment difference graph through graph isomorphism matching and determining an overall influence area; acquiring a stock test case set and mapping the stock test case set into a stock use case path set, identifying an affected path, executing path geometric deformation and expansion, and generating a final evolution path; finally, calculating evolution path comprehensive energy loss, determining a use case evolution state, obtaining a final test case set, and establishing a use case evolution pedigree table; the application realizes activation and evolution of stock test assets, and reduces the maintenance cost of government software regression testing.
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