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arXiv 1001.3473cs.SE
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基于熵的软件质量评价

Software Metrics Evaluation Based on Entropy

R. Selvarani, T. R. Gopalakrishnan Nair, Muthu Ramachandran, Kamakshi Prasad

摘要:

行业中的软件工程活动已经走过了漫长的道路,在软件开发生存周期的各个阶段都带来了各种改进。现代软件的复杂性、商业约束和对高质量产品的期望要求在软件开发的早期阶段基于面向对象设计度量在类级别上进行准确的故障预测。面向对象类度量在整个OO软件开发生存周期中被用作质量预测器,即使在采用高度迭代的增量模型或敏捷软件过程时也是如此。最近的研究表明,一些面向对象的设计指标是有用的预测类的故障倾向。在本文中,经验验证的一组度量提出的Chidamber和Kemerer进行评估他们的能力,在预测软件质量的故障倾向和退化。我们还提出了面向对象软件的设计复杂性与加权方法每类度量(WMC-CK度量)表示的香农熵,和错误倾向。

英文摘要:

Software engineering activities in the Industry has come a long way with various improve- ments brought in various stages of the software development life cycle. The complexity of modern software, the commercial constraints and the expectation for high quality products demand the accurate fault prediction based on OO design metrics in the class level in the early stages of software development. The object oriented class metrics are used as quality predictors in the entire OO software development life cycle even when a highly iterative, incremental model or agile software process is employed. Recent research has shown some of the OO design metrics are useful for predicting fault-proneness of classes. In this paper the empirical validation of a set of metrics proposed by Chidamber and Kemerer is performed to assess their ability in predicting the software quality in terms of fault proneness and degradation. We have also proposed the design complexity of object-oriented software with Weighted Methods per Class metric (WMC-CK metric) expressed in terms of Shannon entropy, and error proneness.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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