traditional manual and partially automated testing methods have found it difficult to meet the efficiency requirements of system testing work
especially when dealing with rapidly changing and highly customized industrial software systems
where testing coverage and efficiency are often insufficient. Therefore
in this research
a component-based industrial software system test case generation method is proposed based on a large language model
aiming to improve the flexibility and efficiency of testing work. This method uses a large language model to convert user descriptions into test cases
combined with a step-by-step generation strategy
covering three stages: test case generation
correction
and test code generation. Firstly
the system starts from user input and generates preliminary test case data based on the knowledge base. Subsequently
the Petri net model is used to modify the generated test case paths to ensure the accuracy of the testing process. Finally
by modularizing the generation of core business code
the deployment of test cases can be accelerated. The experimental results show that this method demonstrates good automation capabilities in component-based industrial software system testing
significantly improving testing efficiency and coverage.
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Keywords
references
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