[1]李 勇,刘战东,张海军.跨项目软件缺陷预测方法研究综述[J].计算机技术与发展,2020,30(03):98-103.[doi:10. 3969 / j. issn. 1673-629X. 2020. 03. 019]
　LI Yong,LIU Zhan-dong,ZHANG Hai-jun.Review on Cross-project Software Defects Prediction Methods[J].Computer Technology and Development,2020,30(03):98-103.[doi:10. 3969 / j. issn. 1673-629X. 2020. 03. 019]
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跨项目软件缺陷预测方法研究综述()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
30
期数:
2020年03期
页码:
98-103
栏目:
智能、算法、系统工程
出版日期:
2020-03-10

文章信息/Info

Title:
Review on Cross-project Software Defects Prediction Methods
文章编号:
1673-629X(2020)03-0098-06
作者:
李 勇1; 2; 刘战东1; 张海军1
1. 新疆师范大学 计算机科学技术学院,新疆 乌鲁木齐 830054; 2. 新疆师范大学 数据安全重点实验室,新疆 乌鲁木齐 830054
Author(s):
LI Yong1; 2; LIU Zhan-dong1; ZHANG Hai-jun1
1.School of Computer Science and Technology,Xinjiang Normal University,Urumqi 830054,China; 2.Key Laboratory of Data Security,Xinjiang Normal University,Urumqi 830054,China
关键词:
跨项目缺陷预测; 迁移学习; 软件属性特征; 软件模块实例; 模型训练
Keywords:
cross-project defects prediction; transfer learning; software attribute characteristics; software module instance; model training
分类号:
TP311.5
DOI:
10. 3969 / j. issn. 1673-629X. 2020. 03. 019
摘要:
软件缺陷预测是提高软件测试效率、保证软件可靠性的重要途径,已经成为目前实证软件工程领域的研究热点。 在软件工程中,软件的开发过程或技术平台可能随时变化,特别是遇到新项目启动或旧项目重新开发时,基于目标项目数 据的传统软件缺陷预测方法无法满足实践需求。 基于迁移学习技术采用其他项目中已经标注的软件数据实现跨项目的 缺陷预测,可以有效解决传统方法的不足,引起了国内外研究者的极大关注,并取得了一系列的研究成果。 首先总结了跨 项目软件缺陷预测中的关键问题。 然后根据迁移学习的技术特点将现有方法分为基于软件属性特征迁移和软件模块实 例迁移两大类,并分析比较了常见方法的特点和不足。 最后探讨了跨项目软件缺陷预测未来的发展方向。
Abstract:
Software defect prediction is an important way to improve the software testing efficiency and ensure software reliability,which has become a research hotspot in the field of empirical software engineering. In software engineering,the software development processor technology platform may change at any time. Especially when a new project is started or an old project is redeveloped,the traditional within-project software defect prediction method cannot meet the practical needs. Cross-project software defect prediction that using the cross-project labeled data and transfer learning technology can effectively solve the shortcomings of traditional method,which has attracted great attention of scholars at home and abroad,and produced a series of research findings. Firstly,the key problems of crossproject software defect prediction methods are summarized. Then,according to the technical characteristics of transfer learning,the existing methods are divided into two types, i.e.,the methods based on attribute characteristics and the methods based on software module instances,and the characteristics and shortcomings of common methods are analyzed and compared. Finally,the future development direction of cross-project software defect prediction is discussed.

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更新日期/Last Update: 2020-03-10