一种测试用例的目标用例缺陷预测模型的生成方法和装置
By constructing a target use case defect prediction model and training it using logistic regression algorithm and cross-entropy loss function, the problem of low efficiency in test case defect discovery is solved, enabling rapid defect location and improved testing efficiency, thus ensuring stable product launch.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- BEIJING JINGDONG ZHENSHI INFORMATION TECH CO LTD
- Filing Date
- 2022-12-12
- Publication Date
- 2026-07-17
AI Technical Summary
In the existing testing process, the discovery of test case defects relies on manual searching, which leads to excessive time consumption, low efficiency, and an inability to meet the testing needs of rapidly iterating products. In particular, when complex defects are discovered in the later stages of testing, the testing progress is affected, and the normal launch of the product cannot be guaranteed.
A target test case defect prediction model is constructed. By acquiring historical test cases, performing word segmentation and unique encoding, and using logistic regression algorithm and cross-entropy loss function to iteratively train the model, the defect probability of test cases is predicted.
Quickly locate defective test cases, shorten testing time, improve testing efficiency, reduce manpower and time costs, ensure stable product launch, expand testing scenarios to cover more product requirements, and improve user experience.
Smart Images
Figure CN115794647B_ABST