Defect Prediction in Software Using Predictive Models Based on Historical Data

被引：1

作者：

Czyczyn-Egird, Daniel ^{[1
]}

Slowik, Adam ^{[1
]}

机构：

[1] Koszalin Univ Technol, Dept Elect & Comp Sci, Sniadeckich 2 St, PL-75453 Koszalin, Poland

来源：

DISTRIBUTED COMPUTING AND ARTIFICIAL INTELLIGENCE | 2019年 / 801卷

关键词：

Data mining in software; Defect prediction models; Software metrics;

D O I：

10.1007/978-3-319-99608-0_11

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Nowadays, there are many methods and good practices in software engineering that aim to provide high quality software. However, despite the efforts of software developers, there are often defects in projects, the removal of which is often associated with a large financial effort and time. The article presents an example approach to defect prediction in IT projects based on prediction models built on historical information and product metrics collected from various data repositories.

引用

页码：94 / 101

页数：8

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