BECLoMA:用用户评论信息增加堆栈跟踪

L. Pelloni, Giovanni Grano, Adelina Ciurumelea, Sebastiano Panichella, Fabio Palomba, H. Gall
{"title":"BECLoMA:用用户评论信息增加堆栈跟踪","authors":"L. Pelloni, Giovanni Grano, Adelina Ciurumelea, Sebastiano Panichella, Fabio Palomba, H. Gall","doi":"10.1109/SANER.2018.8330252","DOIUrl":null,"url":null,"abstract":"Mobile devices such as smartphones, tablets and wearables are changing the way we do things, radically modifying our approach to technology. To sustain the high competition characterizing the mobile market, developers need to deliver high quality applications in a short release cycle. To reveal and fix bugs as soon as possible, researchers and practitioners proposed tools to automate the testing process. However, such tools generate a high number of redundant inputs, lacking of contextual information and generating reports difficult to analyze. In this context, the content of user reviews represents an unmatched source for developers seeking for defects in their applications. However, no prior work explored the adoption of information available in user reviews for testing purposes. In this demo we present BECLOMA, a tool to enable the integration of user feedback in the testing process of mobile apps. BECLOMA links information from testing tools and user reviews, presenting to developers an augmented testing report combining stack traces with user reviews information referring to the same crash. We show that BECLOMA facilitates not only the diagnosis and fix of app bugs, but also presents additional benefits: it eases the usage of testing tools and automates the analysis of user reviews from the Google Play Store.","PeriodicalId":6602,"journal":{"name":"2018 IEEE 25th International Conference on Software Analysis, Evolution and Reengineering (SANER)","volume":"115 12 1","pages":"522-526"},"PeriodicalIF":0.0000,"publicationDate":"2018-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"25","resultStr":"{\"title\":\"BECLoMA: Augmenting stack traces with user review information\",\"authors\":\"L. Pelloni, Giovanni Grano, Adelina Ciurumelea, Sebastiano Panichella, Fabio Palomba, H. Gall\",\"doi\":\"10.1109/SANER.2018.8330252\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Mobile devices such as smartphones, tablets and wearables are changing the way we do things, radically modifying our approach to technology. To sustain the high competition characterizing the mobile market, developers need to deliver high quality applications in a short release cycle. To reveal and fix bugs as soon as possible, researchers and practitioners proposed tools to automate the testing process. However, such tools generate a high number of redundant inputs, lacking of contextual information and generating reports difficult to analyze. In this context, the content of user reviews represents an unmatched source for developers seeking for defects in their applications. However, no prior work explored the adoption of information available in user reviews for testing purposes. In this demo we present BECLOMA, a tool to enable the integration of user feedback in the testing process of mobile apps. BECLOMA links information from testing tools and user reviews, presenting to developers an augmented testing report combining stack traces with user reviews information referring to the same crash. We show that BECLOMA facilitates not only the diagnosis and fix of app bugs, but also presents additional benefits: it eases the usage of testing tools and automates the analysis of user reviews from the Google Play Store.\",\"PeriodicalId\":6602,\"journal\":{\"name\":\"2018 IEEE 25th International Conference on Software Analysis, Evolution and Reengineering (SANER)\",\"volume\":\"115 12 1\",\"pages\":\"522-526\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-03-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"25\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE 25th International Conference on Software Analysis, Evolution and Reengineering (SANER)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SANER.2018.8330252\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE 25th International Conference on Software Analysis, Evolution and Reengineering (SANER)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SANER.2018.8330252","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 25

摘要

智能手机、平板电脑和可穿戴设备等移动设备正在改变我们做事的方式,从根本上改变我们对技术的态度。为了维持手机市场的高竞争,开发者需要在较短的发布周期内交付高质量的应用。为了尽快发现和修复错误,研究人员和从业者提出了自动化测试过程的工具。然而,这些工具产生了大量的冗余输入,缺乏上下文信息,生成的报告难以分析。在这种情况下,用户评论的内容代表了开发人员在其应用程序中寻找缺陷的无与伦比的来源。然而,之前的工作没有探索用户评论中可用信息用于测试目的的采用。在这个演示中,我们展示了BECLOMA,一个能够在移动应用程序的测试过程中集成用户反馈的工具。BECLOMA将来自测试工具和用户评论的信息链接起来,向开发人员展示一个增强的测试报告,该报告结合了堆栈跟踪和用户评论信息,涉及相同的崩溃。我们发现BECLOMA不仅有助于诊断和修复应用漏洞,而且还提供了额外的好处:它简化了测试工具的使用,并自动分析来自Google Play Store的用户评论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
BECLoMA: Augmenting stack traces with user review information
Mobile devices such as smartphones, tablets and wearables are changing the way we do things, radically modifying our approach to technology. To sustain the high competition characterizing the mobile market, developers need to deliver high quality applications in a short release cycle. To reveal and fix bugs as soon as possible, researchers and practitioners proposed tools to automate the testing process. However, such tools generate a high number of redundant inputs, lacking of contextual information and generating reports difficult to analyze. In this context, the content of user reviews represents an unmatched source for developers seeking for defects in their applications. However, no prior work explored the adoption of information available in user reviews for testing purposes. In this demo we present BECLOMA, a tool to enable the integration of user feedback in the testing process of mobile apps. BECLOMA links information from testing tools and user reviews, presenting to developers an augmented testing report combining stack traces with user reviews information referring to the same crash. We show that BECLOMA facilitates not only the diagnosis and fix of app bugs, but also presents additional benefits: it eases the usage of testing tools and automates the analysis of user reviews from the Google Play Store.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信