基于用户反馈的APP软件缺陷识别

doi:10.11896/jsjkx.191100133

计算机科学 ›› 2020, Vol. 47 ›› Issue (6): 44-50.doi: 10.11896/jsjkx.191100133

基于用户反馈的APP软件缺陷识别

段文静, 姜瑛

云南省计算机技术应用重点实验室昆明650500
昆明理工大学信息工程与自动化学院昆明650500

收稿日期:2019-11-18 出版日期:2020-06-15 发布日期:2020-06-10
通讯作者: 姜瑛(jy_910@163.com)
作者简介:526626071@qq.com
基金资助:
国家重点研发计划项目(2018YFB1003904);国家自然科学基金(61462049,61063006,60703116);云南省应用基础研究计划重点项目(2017FA033)

Defect Recognition of APP Software Based on User Feedback

DUAN Wen-jing, JIANG Ying

Computer Technology Application Key Lab of Yunnan Province,Kunming 650500,China
Faculty of Information Engineering and Automation,Kunming University of Science and Technology,Kunming 650500,China

Received:2019-11-18 Online:2020-06-15 Published:2020-06-10
About author:DUAN Wen-jing,born in 1992,postgraduate,is a member of China Compu-ter Federation.Her main research inte-rests include software engineering and so on.
JIANG Ying,born in 1974,Ph.D,professor,Ph.D supervisor,is a senior member of China Computer Federation.Her main research interests include software quality assurance and testing,cloud computing,big data analysis and intelligent software engineering.
Supported by:
This work was supported by the National Key Research and Development Program of China (2018YFB1003904),National Natural Science Foundation of China (61462049,61063006,60703116) and Key Project of Yunnan Applied Basic Research (2017FA033)

摘要/Abstract

摘要： 当前,APP软件已被广泛应用,其质量越来越受到关注。高质量的软件的缺陷应尽可能少,然而软件测试并不能发现所有的缺陷,部分缺陷到用户使用阶段才被发现,因此通过分析用户反馈的信息有助于发现软件缺陷。文中提出了基于用户反馈的APP软件缺陷识别方法,通过定义APP软件缺陷抽取规则挖掘用户反馈中的软件缺陷,并在挖掘软件缺陷的过程中动态更新抽取规则,最后对抽取出的APP软件缺陷进行分类及严重程度分析。实验表明,所提方法是有效的,提取含有软件缺陷的APP软件用户评论的准确率达85.19%,缺陷分类准确率达83.23%。

关键词: APP软件, 缺陷抽取规则, 缺陷分类, 缺陷严重程度, 用户反馈

Abstract: At present,APP software has been widely used,and its quality has been widely concerned.The high quality software defects should be fewer.However,software testing cannot find all defects.Some software defects can not be found until the user uses the software.This paper puts forward a method of software defect recognition based on user feedback.By defining the APP software defect extraction rule,software defects in user feedback are mined.During the mining of APP software’s defect,the extraction rule is dynamically updated.Then the classification and severity for the extracted defects are analyzed.The experimental results show that the proposed method is effective,the accuracy of extracting user comments including APP software’s defects is 85.19%,and the accuracy of defect classification is 83.23%.

Key words: APP software, Defect classification, Defect extraction rules, Defect severity, User feedback

中图分类号:

TP311.5

段文静, 姜瑛. 基于用户反馈的APP软件缺陷识别[J]. 计算机科学, 2020, 47(6): 44-50. https://doi.org/10.11896/jsjkx.191100133

DUAN Wen-jing, JIANG Ying. Defect Recognition of APP Software Based on User Feedback[J]. Computer Science, 2020, 47(6): 44-50. https://doi.org/10.11896/jsjkx.191100133

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基于用户反馈的APP软件缺陷识别

Defect Recognition of APP Software Based on User Feedback

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