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%。
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%.
作者
段文静
姜瑛
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)
出处
《计算机科学》
CSCD
北大核心
2020年第6期44-50,共7页
Computer Science
基金
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)。