题名 | Collaborative bug finding for android apps |
作者 | |
DOI | |
发表日期 | 2020-06-27
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会议名称 | International Conference on Software Engineering
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ISSN | 0270-5257
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ISBN | 978-1-7281-6519-6
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会议录名称 | |
页码 | 1335-1347
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会议日期 | 6-11 July 2020
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会议地点 | online
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摘要 | Many automated test generation techniques have been proposed for finding crashes in Android apps. Despite recent advancement in these approaches, a study shows that Android app developers prefer reading test cases written in natural language. Meanwhile, there exist redundancies in bug reports (written in natural language) across different apps that have not been previously reused. We propose collaborative bug finding, a novel approach that uses bugs in other similar apps to discover bugs in the app under test. We design three settings with varying degrees of interactions between programmers: (1) bugs from programmers who develop a different app, (2) bugs from manually searching for bug reports in GitHub repositories, (3) bugs from a bug recommendation system, Bugine. Our studies of the first two settings in a software testing course show that collaborative bug finding helps students who are novice Android app testers to discover 17 new bugs. As students admit that searching for relevant bug reports could be time-consuming, we introduce Bugine, an approach that automatically recommends relevant GitHub issues for a given app. Bugine uses (1) natural language processing to find GitHub issues that mention common UI components shared between the app under test and other apps in our database, and (2) a ranking algorithm to select GitHub issues that are of the best quality. Our results show that Bugine is able to find 34 new bugs. In total, collaborative bug finding helps us find 51 new bugs, in which eight have been confirmed and 11 have been fixed by the developers. These results confirm our intuition that our proposed technique is useful in discovering new bugs for Android apps. |
关键词 | |
学校署名 | 第一
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语种 | 英语
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相关链接 | [Scopus记录] |
收录类别 | |
EI入藏号 | 20204409433213
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EI主题词 | Application programs
; Android (operating system)
; Students
; Software testing
; Program debugging
; Testing
; Natural language processing systems
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EI分类号 | Computer Software, Data Handling and Applications:723
; Computer Programming:723.1
; Data Processing and Image Processing:723.2
; Computer Applications:723.5
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Scopus记录号 | 2-s2.0-85094130539
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来源库 | Scopus
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全文链接 | https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9284092 |
引用统计 |
被引频次[WOS]:14
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成果类型 | 会议论文 |
条目标识符 | http://sustech.caswiz.com/handle/2SGJ60CL/209205 |
专题 | 南方科技大学 工学院_计算机科学与工程系 |
作者单位 | Southern University of Science and Technology Shenzhen,Guangdong Province,China |
第一作者单位 | 南方科技大学 |
第一作者的第一单位 | 南方科技大学 |
推荐引用方式 GB/T 7714 |
Tan,Shin Hwei,Li,Ziqiang. Collaborative bug finding for android apps[C],2020:1335-1347.
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条目包含的文件 | ||||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | 操作 | |
collaborative.pdf(836KB) | -- | -- | 限制开放 | -- |
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