Computer Engineering and Applications ›› 2013, Vol. 49 ›› Issue (2): 67-71.

Previous Articles     Next Articles

Research on software defect list:prediction method based on grey relational analysis

DONG Shaoyang, XIA Qingguo, LI Ning   

  1. School of Computer Science, Northwestern Polytechnical University, Xi’an 710072, China
  • Online:2013-01-15 Published:2013-01-16

基于灰色关联分析法的软件缺陷类型预测

董少阳,夏清国,李  宁   

  1. 西北工业大学 计算机学院,西安 710072

Abstract: Grey relational analysis is a method which is always used to describe the degree of influence among the factors and suitable for small project data sets. But the small project data sets often restrain the predicting methods of the traditional software detect types, which causes the inaccuracy and unreliability of the predicting results. This paper particularly proposes feature subset selection method, outlier project detection method, and software defect list prediction method of a project. Moreover it evaluates the approach on publicly available industrial data sets using a series of experiments, and the prediction result demonstrates the method is more accurate and reliable.

Key words: grey relational analysis, feature subset selection, outlier project detection, software defect list prediction

摘要: 灰色关联分析法是一种描述元素之间影响程度的分析法,适合于小项目数据集。小项目数据集制约着传统的软件缺陷类型的预测方法,使得预测的结果往往不够准确和可靠。因此在灰色关联分析法的基础上提出了特征子集选择、异常工程检测以及软件缺陷类型预测3种方法。通过实验的分析对比,验证了在灰色关联分析法的基础上,提出的软件缺陷类型预测方法的准确性和可靠性。

关键词: 灰色关联分析法, 特征子集选择, 异常工程检测, 软件缺陷类型预测