Quantitative Software Quality/Reliability Prediction Based on Project Management Data for Waterfall and Agile Development Paradigms

被引:0
作者
Shigeru Yamada
Toshiki Aoki
Toshiyuki Toyota
机构
[1] Tottori University,Department of Social Management Engineering, Graduate School of Engineering
[2] Tottori University of Environmental Studies Kita 1-1-1,Department of Information Systems, Faculty of Environmental and Information Studies
关键词
Quality prediction; Software metrics; Multiple regression analysis; Collaborative filtering; Similarity of projects;
D O I
10.1007/BF03398828
中图分类号
学科分类号
摘要
Software development productivity and product quality are related to quality of the software development process. Therefore, if we can improve quality of software development process based on project management technologies, software development productivity and product quality will be increased. In this paper, we conduct a multivariate analysis by using process measurement data, and derive a relational expression based on statistically significant factors, which can quantitatively predict final product quality/reliability. Furthermore, we apply a method of collaborative filtering by using process measurement data to predict final product quality from the similarity of software projects. Finally, we compare the results of two methods, i.e., multiple regression analysis and collaborative filtering, in terms of predictive accuracy of final product quality/reliability.
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页码:391 / 404
页数:13
相关论文
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Tunoda M(2005)Software Development Effort Prediction Based on Collaborative Filtering Trans. IPS Japan 46 1155-1164
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