一种测试实例生成方法及自动化测试系统
By automatically generating test cases through an NLP engine and optimizing the generation and discrimination networks, the problem of incomplete test coverage of the instrument's core modules was solved, achieving efficient and comprehensive automated testing, reducing costs and improving test quality.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- CHONGQING UNIV OF POSTS & TELECOMM
- Filing Date
- 2023-12-01
- Publication Date
- 2026-07-17
AI Technical Summary
Existing instrument core module testing solutions cannot effectively cover peripheral interface functions, bus communication functions, and internal algorithm blocks. Manually generating test cases is time-consuming, labor-intensive, and susceptible to subjective bias, while automatically generating test cases is prone to omissions, making it difficult to meet the requirements for high-efficiency and comprehensive testing.
Test cases are automatically generated using an NLP engine. By constructing a generator network and a discriminator network, the generator network is optimized to meet testing requirements. GANs are used to optimize the NLP-generated test cases. Combined with an automated testing system, the peripheral interface functions, bus communication functions, and internal algorithm blocks of the instrument's core module are tested.
It achieves low maintenance costs and high ease of use, simplifies testing operations, reduces testing costs, improves automation, and generates test cases that are comprehensive, highly effective, and repeatable, thereby improving testing quality and effectiveness.
Smart Images
Figure CN117743152B_ABST