Abstract
Automated test case generation is one of the key points of automated unit testing. In path-oriented automated unit testing, the abstract memory model is used to accurately extract the semantics and constraints of variables on the path, which is a prerequisite for automatically generating test cases. However, the existing abstract memory model still has shortcomings, such as incomplete type support, difficulty in handling complex operations accurately. This paper focuses on improving the accuracy of the abstract memory model and the completeness of support. Based on the existing abstract memory model ˈ the paper proposes an optimized abstract memory model supporting the expression of numeric, pointer, structure, array, union. And the constraint extraction algorithm and the non-numeric test case shape construction algorithm are improved, which can more accurately simulate the semantics of complex operations and extract constraints. Based on the optimized abstract memory, it can provide more accurate and comprehensive information for automatic test case generation.
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