随机测试
计算机科学
软件测试
测试套件
边距(机器学习)
一套
代码覆盖率
编码(集合论)
度量(数据仓库)
可靠性工程
算法
数据挖掘
测试用例
机器学习
软件
程序设计语言
工程类
回归分析
考古
集合(抽象数据类型)
历史
作者
Laleh Sh. Ghandehari,Jacek Czerwonka,Yu Lei,Soheil Shafiee,Raghu N. Kacker,Richard Kühn
摘要
Some conflicting results have been reported on the comparison between t-way combinatorial testing and random testing. In this paper, we report a new study that applies t-way and random testing to the Siemens suite. In particular, we investigate the stability of the two techniques. We measure both code coverage and fault detection effectiveness. Each program in the Siemens suite has a number of faulty versions. In addition, mutation faults are used to better evaluate fault detection effectiveness in terms of both number and diversity of faults. The experimental results show that in most cases, t-way testing performed as good as or better than random testing. There are few cases where random testing performed better, but with a very small margin. Overall, the differences between the two techniques are not as significant as one would have probably expected. We discuss the practical implications of the results. We believe that more studies are needed to better understand the comparison of the two techniques.
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