使用“ODC和谐矩阵”监测和改进ODC数据的质量:一个案例研究

Nirav Saraiya, Jason E. Lohner, Jongmoon Baik
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引用次数: 1

摘要

正交缺陷分类(ODC)是一种先进的软件工程技术,它使用缺陷数据向开发人员和测试人员提供过程中反馈。大型组织中的ODC制度化涉及一些具有挑战性的障碍,例如收集的数据质量差,导致错误的分析。在本文中,我们提出了一种技术(“和谐矩阵”)来改进数据收集过程。ODC和谐矩阵有很多有用的应用。在单个缺陷级别,如果选择了低概率的组合,结果可以用于在数据收集点向从业者发出警报。在更高的级别上,ODC和谐矩阵有助于监视所收集的ODC数据的质量。ODC和谐矩阵补充了监视和增强ODC数据收集过程的其他方法,并有助于ODC成功制度化,最终改进产品和过程。本文还描述了使用这种方法时应采取的预防措施
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Monitoring and Improving the Quality of ODC Data using the "ODC Harmony Matrices": A Case Study
Orthogonal defect classification (ODC) is an advanced software engineering technique to provide in-process feedback to developers and testers using defect data. ODC institutionalization in a large organization involves some challenging roadblocks such as the poor quality of the collected data leading to wrong analysis. In this paper, we have proposed a technique ('Harmony Matrix') to improve the data collection process. The ODC Harmony Matrix has useful applications. At the individual defect level, results can be used to raise alerts to practitioners at the point of data collection if a low probability combination is chosen. At the higher level, the ODC Harmony Matrix helps in monitoring the quality of the collected ODC data. The ODC Harmony Matrix complements other approaches to monitor and enhances the ODC data collection process and helps in successful ODC institutionalization, ultimately improving both the product and the process. The paper also describes precautions to take while using this approach
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