Statistical data analysis for software metrics validation

被引:0
作者
Lee, MC
机构
来源
KNOWLEDGE-BASED INTELLIGENT INFORMATION AND ENGINEERING SYSTEMS, PT 4, PROCEEDINGS | 2005年 / 3684卷
关键词
metrics validation methodology; quality functions; validity criteria; nonparametric statistical methods;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
A metrics validation process is defined that integrates quality factors and quality functions. It proposes a comprehensive metric validation methodology that has validity criteria, which support the quality function and activities conducted by software organization for the purpose of achieving project quality goals. In this paper, valid metrics are assessing differences in quality, assessing relative quality, control quality (discrimination between high quality and low quality), control quality (tracking changes), and prediction quality. The criteria are defined and illustrated by association, consistency, discriminative power, tracking. Statistical methods such as Mann-Whitency, Wilcoxon Rank Sum test, Wald-Wolfowitz, and Discriminate Analysis play an important role in evaluating metrics against the validity criterion.
引用
收藏
页码:389 / 395
页数:7
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