数据驱动的软件缺陷预测研究综述

doi:10.3969/j.issn.0372-2112.2017.04.030

电子学报 ›› 2017, Vol. 45 ›› Issue (4): 982-988.DOI: 10.3969/j.issn.0372-2112.2017.04.030

数据驱动的软件缺陷预测研究综述

李勇^1,2, 黄志球¹, 王勇¹, 房丙午¹

1. 南京航空航天大学计算机科学与技术学院, 江苏南京 211106;
2. 新疆师范大学网络信息安全与舆情分析重点实验室, 新疆乌鲁木齐 830054

收稿日期:2015-10-19 修回日期:2016-08-01 出版日期:2017-04-25
- 通讯作者:
- 黄志球
- 作者简介:
- 李勇男,1983年12月生于山西晋中,现为南京航空航天大学计算机科学与技术学院博士研究生.主要研究方向为实证软件工程.E-mail:liyong@live.com
- 基金资助:
- 国家自然科学基金 (No.61562087，No.61272083）; 江苏省普通高校研究生科研创新计划 (No.CXLX13_-160）; 中央高校基本科研业务费专项项目

Survey on Data Driven Software Defects Prediction

LI Yong^1,2, HUANG Zhi-qiu¹, WANG Yong¹, FANG Bing-wu¹

1. College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu 211106, China;
2. Key Laboratory of Network Information Security and Public Opinion Analysis, Xinjiang Normal University, Urumqi, Xinjiang 830054, China

Received:2015-10-19 Revised:2016-08-01 Online:2017-04-25 Published:2017-04-25
- Supported by:
- National Natural Science Foundation of China (No.61562087, No.61272083); Graduate Research Innovation Program of univerities in Jiangsu Province (No.CXLX13<sub>-</sub>160); Fundamental Research Funds for the Central Universities

摘要/Abstract

摘要：

数据驱动的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之一，近几年已成为实证软件工程的研究热点.首先介绍了数据驱动软件缺陷预测的研究背景；然后总结了已有软件缺陷数据属性度量方法的特点，并按照软件开发中缺陷预测的使用场景，以数据来源为主线从基于版本内数据、跨版本数据和跨项目数据实现缺陷预测三个方面对近10年（2005~2015）已有的研究工作进行分类归纳和比较；最后对该领域未来的研究趋势进行了展望.

关键词: 软件缺陷预测, 数据驱动, 软件度量, 机器学习

Abstract:

Data driven software defects prediction is considered as an effective means for the optimization of quality assurance activities.This paper tries to survey the studies of data driven software defects prediction from 2005 to 2015.First,it briefly introduces the research background in this field.Then,it summarizes and analyzes the software modules attribute metrics in detail,and thoroughly surveys the state-of-the-art methods of data driven software defects prediction.The discussed topics include within-release,cross-release and cross-project defects prediction.Finally,the potential research directions in the field are discussed.

Key words: software defects prediction, data driven, software metrics, machine learning

中图分类号:

TP311.5

李勇, 黄志球, 王勇, 等. 数据驱动的软件缺陷预测研究综述[J]. 电子学报, 2017, 45(4): 982-988.

LI Yong, HUANG Zhi-qiu, WANG Yong, et al. Survey on Data Driven Software Defects Prediction[J]. Acta Electronica Sinica, 2017, 45(4): 982-988.

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数据驱动的软件缺陷预测研究综述

Survey on Data Driven Software Defects Prediction

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