An Exploratory Study of the Relationship Between Software Test Smells and Fault-Proneness
An Exploratory Study of the Relationship Between Software Test Smells and Fault-Proneness
复制标题
软件测试气味与故障倾向之间关系的探索性研究
作者：
A. Qusef;Mahmoud O. Elish;D. Binkley
测试气味被定义为设计不良测试的指标。它们的存在会对测试套件和产品代码的可维护性产生负面影响。尽管有许多研究解决了各种测试气味的负面影响，但到目前为止，还没有经验证据表明测试气味的演变与生产代码中的错误之间的关系。本文提供了这样的证据。它提供了一个案例研究，研究了从28个版本的Apache Ant中收集的数据，其中包括总共4，447个单元测试。从这些数据中得出三个关键结果。首先，测试气味的绝对数量随着Apache Ant的发展而增加。第二，一些测试气味与产品代码中存在的错误正相关。最后，我们的研究结果表明，它是可以预测的基础上存在的测试气味在代码的单元测试的生产代码中的故障。此外，所得到的预测模型在预测高严重性故障时比低严重性故障更准确。这是一个重要的结果，因为它使工程师能够集中预防性维护工作，应用于生产代码，使用在单元测试中发现的测试气味。
Test smells have been defined as indicators of poorly designed tests. Their presence negatively affects the maintainability of a test suite as well as the production code. Despite the many studies that address the negative impacts of various test smells, until now there has been no empirical evidence considering the relation between the evolution of test smells and that of faults in the production code. This paper presents such evidence. It presents a case study of data collected from 28 versions of Apache Ant that include a total of 4,447 unit tests. Three key results arise from the data. First, the absolute number of test smells increases as Apache Ant evolves. Second, some test smells are positively correlated with the existence of faults in the production code. Finally, our results show that it is possible to predict faults in the production code based on the existence of test smells in the code’s unit tests. In addition, the resulting prediction model is more accurate at predicting high-severity faults than low-severity faults. This is an important result as it enables an engineer to focus preventative maintenance efforts, applied to the production code, using test smells found in the unit tests.
DOI：
--
发表时间：
2016
期刊：
--
影响因子：
--
作者：
A. Tahir
通讯作者：
A. Tahir
影响因子：
4.4
作者：
Hall, Tracy;Zhang, Min;Sun, Yi
通讯作者：
Sun, Yi