Assessment of the Software Defect Prediction Cost Effectiveness in an Industrial Project
Assessment of the Software Defect Prediction Cost Effectiveness in an Industrial Project
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工业项目中软件缺陷预测成本效益的评估
DOI：
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
L. Madeyski
中科院分区：
文献类型：
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作者：
Jarosław Hryszko;L. Madeyski
软件缺陷预测是一种有希望的，新的方法，可以提高软件质量和开发步伐。不幸的是，开创性公司并没有热切地共享软件缺陷预测的成本效益。特别是，使用弗罗茨瓦夫科学技术大学和Capgemini软件开发公司开发的Downses开源软件测量框架的成本有效性，以前尚未研究过商业软件开发项目中的缺陷预测。因此，在本文中，我们探讨了缺陷预测是否可以通过产生利润对工业软件开发项目产生积极影响。为了实现这一目标，我们根据最佳预测结果以及拟议的质量保证（QA）策略进行了缺陷预测和模拟潜在质量保证成本。我们的调查结果非常乐观：我们估计将使用建议的方法时，质量保证成本可以降低近30％，而估计的降压工具使用率（ROI）的使用回报率为73（7300％），收益成本比率为73（7300％） （BCR）是74。这种有希望的结果导致接受了沃尔沃集团经营的实际工业项目的基于压抑的软件缺陷预测的持续使用。
Software defect prediction is a promising, new approach to increase both, software quality and development pace. Unfortunately, the cost effectiveness of software defect prediction in industrial settings is not eagerly shared by the pioneering companies. In particular, the cost effectiveness of using the DePress open source software measurement framework, developed by Wroclaw University of Science and Technology, and Capgemini software development company, for defect prediction in commercial software development projects have not been previously investigated. Thus, in this paper, we explore whether defect prediction can positively impact an industrial software development project by generating profits. To meet this goal, we conducted a defect prediction and simulated potential quality assurance costs based on the best prediction result, as well as the proposed Quality Assurance (QA) strategy. Results of our investigation were optimistic: we estimated that quality assurance costs can be reduced by almost 30 % when proposed approach will be used, while estimated DePress tool usage Return on Investment (ROI) is fully 73 (7300 %), and Benefits Cost Ratio (BCR) is 74. Such promising results have caused the acceptance of continued usage of the DePress-based software defect prediction for actual industrial projects run by Volvo Group.