Using a class abstraction technique to predict faults in OO classes: a case study through six releases of the Eclipse JDT
Using a class abstraction technique to predict faults in OO classes: a case study through six releases of the Eclipse JDT
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使用类抽象技术来预测 OO 类中的错误：通过 Eclipse JDT 的六个版本进行的案例研究
DOI：
10.1145/1982185.1982492
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发表时间：
2011
期刊：
影响因子：
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通讯作者：
B. M. Kibria
中科院分区：
文献类型：
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作者：
Djuradj Babich;Peter J. Clarke;James F. Power;B. M. Kibria
在本文中，我们提出了基于类抽象的创新指标套件，该集体抽象使用OO类（CAT）的分类法（CAT）来通过类特征的组合来捕获软件复杂性的各个方面。我们从经验上验证了他们使用故障数据为基于Java的开源Eclipse集成开发环境预测故障数据预测故障类别的能力。我们得出的结论是，这个提出的猫公制套件即使它分组而不是单独对待类，也与传统的Chidamber和Kemerer指标同样有效。
In this paper, we propose an innovative suite of metrics based on a class abstraction that uses a taxonomy for OO classes (CAT) to capture aspects of software complexity through combinations of class characteristics. We empirically validate their ability to predict fault prone classes using fault data for six versions of the Java-based open-source Eclipse Integrated Development Environment. We conclude that this proposed CAT metric suite, even though it treats classes in groups rather than individually, is as effective as the traditional Chidamber and Kemerer metrics in identifying fault-prone classes.