Estimation of software defects fix effort using neural networks

被引：0

作者：

Zeng, H ^{[1
]}

Rine, D ^{[1
]}

机构：

[1] George Mason Univ, Sch Informat & Technol, Fairfax, VA 22030 USA

来源：

PROCEEDINGS OF THE 28TH ANNUAL INTERNATIONAL COMPUTER SOFTWARE AND APPLICATION CONFERENCE, WORKSHOP AND FAST ABSTRACTS | 2004年

关键词：

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：

Software defects fix effort is an important software development process metric that plays a critical role in software quality assurance. People usually like to apply parametric effort estimation techniques using historical Lines of Code and Function Points data to estimate effort of defects fixes. However, these techniques are neither efficient nor effective for a new different kind of project's fixing defects when code will be written within the context of a different project or organization. In this paper, we present a solution for estimating software defect fix effort using Self-organizing Neural Networks.

引用

页码：20 / 21

页数：2

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