摘要
为了解决基于单纯马尔可夫使用模型测试用例生成不稳定、测试充分性判定不精确的问题,在分析现有测试用例自动生成方法的基础上,提出一种改进的高阶马尔可夫测试模型,并依据此模型,提出改进的基于快速轮盘赌的二分查找测试用例生成方法和基于相对熵的测试充分性判定方法。实践表明,改进后的方法有效地提高了测试用例生成的稳定性和测试充分性判定的精确性,与原有方法比较更适合大规模软件的测试,提高了大规模软件自动化测试的效率。
In order to solve the problem that the test case generation based on the pure Markov usage model is unstable and the test adequacy judgment is inaccurate,an improved high-order Markov test model is proposed on the basis of analyzing the existing test case automatic generation methods. According to this model,an improved test case generation method based on the binary search of the fast roulette,and a test adequacy judgment method based on the relative entropy are put forward. The practical results show that in comparison with the original methods,the improved method can effectively improve the generation stability of test cases and the judgment accuracy of test adequacy,which is suitable for large-scale software testing,and im-proves the efficiency of large-scale software automatic testing.
作者
赵卫东
李有俊
张丽
ZHAO Weidong;LI Youjun;ZHANG Li(Shandong University of Science and Technology,Qingdao 266590,China)
出处
《现代电子技术》
北大核心
2019年第6期26-29,共4页
Modern Electronics Technique
基金
山东省研究生教育创新计划一般项目(SDYC16022)
国家重点研发计划课题(2016YFC0801406)~~
