面向持续集成的回归测试优化方法

针对持续集成环境下回归测试需要进行持续优化的问题,提出一种依据回归测试目标自适应调整策略的优化方法.首先将失败标志、缺陷检测数、重要性因子、新旧功能标志作为用例属性进行标记,根据历史数据和关联关系对用例属性进行初始化;而后根据阶段测试目标,区分新功能测试、修改性测试,将需求映射为具体的用例属性指标,据此对用例进行选择;计算重要性因子,更新用例属性标签,根据用例属性进行优先级自动排序;用例执行中,按照时间、资源要求,根据用例属性选择相应规模的测试用例进行执行.最后选择开源数据集进行实验,结果表明该方法针对不同的测试目标均能够降低执行用例的规模,提高缺陷检测效率.

Regression testing optimization method for continuous integration

The regression testing required continuous optimization in continuous integration environment. This paper proposed an optimization method which could adjust strategies adaptively based on regression testing objectives. Firstly, the method defined the test case attribute with failure identification, defect detection number, importance factor and function identification, and initialized them according to historical data and association relationships. Then, it distinguished between the new function and modified tests according to the test objectives, and mapped requirements to specific case attribute indicators to select the test cases. It calculated the importance factor, updated the case attribute label, and automatically sorted the priority according to the test case attributes. During the execution of the test cases, this paper selected the test cases based on the attributes according to time or resource requirements. Finally, the results on an open-dataset for experimentation show that the method can reduce the scale of execution test cases and improve the efficiency of defect detection for different test targets.