Software mining and fault prediction

被引:3
|
作者
Catal, Cagatay [1 ]
机构
[1] Istanbul Kultur Univ, Dept Comp Engn, Istanbul, Turkey
关键词
NOISE; CLASSIFICATION; METRICS;
D O I
10.1002/widm.1067
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Mining software repositories (MSRs) such as source control repositories, bug repositories, deployment logs, and code repositories provide useful patterns for practitioners. Instead of using these repositories as record-keeping ones, we need to transform them into active repositories that can guide the decision processes inside the company. By MSRs with several data mining algorithms, effective software fault prediction models can be built and error-prone modules can be detected prior to the testing phase. We discuss numerous real-world challenges in building accurate fault prediction models and present some solutions to these challenges. (c) 2012 Wiley Periodicals, Inc.
引用
收藏
页码:420 / 426
页数:7
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