Android的记录和重放:我们在工业案例中已经实现了吗?

Wing Lam, Zhengkai Wu, Dengfeng Li, Wenyu Wang, Haibing Zheng, Hui Luo, Peng Yan, Yuetang Deng, Tao Xie
{"title":"Android的记录和重放:我们在工业案例中已经实现了吗?","authors":"Wing Lam, Zhengkai Wu, Dengfeng Li, Wenyu Wang, Haibing Zheng, Hui Luo, Peng Yan, Yuetang Deng, Tao Xie","doi":"10.1145/3106237.3117769","DOIUrl":null,"url":null,"abstract":"Mobile applications, or apps for short, are gaining popularity. The input sources (e.g., touchscreen, sensors, transmitters) of the smart devices that host these apps enable the apps to offer a rich experience to the users, but these input sources pose testing complications to the developers (e.g., writing tests to accurately utilize multiple input sources together and be able to replay such tests at a later time). To alleviate these complications, researchers and practitioners in recent years have developed a variety of record-and-replay tools to support the testing expressiveness of smart devices. These tools allow developers to easily record and automate the replay of complicated usage scenarios of their app. Due to Android's large share of the smart-device market, numerous record-and-replay tools have been developed using a variety of techniques to test Android apps. To better understand the strengths and weaknesses of these tools, we present a comparison of popular record-and-replay tools from researchers and practitioners, by applying these tools to test three popular industrial apps downloaded from the Google Play store. Our comparison is based on three main metrics: (1) ability to reproduce common usage scenarios, (2) space overhead of traces created by the tools, and (3) robustness of traces created by the tools (when being replayed on devices with different resolutions). The results from our comparison show which record-and-replay tools may be the best for developers and identify future directions for improving these tools to better address testing complications of smart devices.","PeriodicalId":313494,"journal":{"name":"Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"31","resultStr":"{\"title\":\"Record and replay for Android: are we there yet in industrial cases?\",\"authors\":\"Wing Lam, Zhengkai Wu, Dengfeng Li, Wenyu Wang, Haibing Zheng, Hui Luo, Peng Yan, Yuetang Deng, Tao Xie\",\"doi\":\"10.1145/3106237.3117769\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Mobile applications, or apps for short, are gaining popularity. The input sources (e.g., touchscreen, sensors, transmitters) of the smart devices that host these apps enable the apps to offer a rich experience to the users, but these input sources pose testing complications to the developers (e.g., writing tests to accurately utilize multiple input sources together and be able to replay such tests at a later time). To alleviate these complications, researchers and practitioners in recent years have developed a variety of record-and-replay tools to support the testing expressiveness of smart devices. These tools allow developers to easily record and automate the replay of complicated usage scenarios of their app. Due to Android's large share of the smart-device market, numerous record-and-replay tools have been developed using a variety of techniques to test Android apps. To better understand the strengths and weaknesses of these tools, we present a comparison of popular record-and-replay tools from researchers and practitioners, by applying these tools to test three popular industrial apps downloaded from the Google Play store. Our comparison is based on three main metrics: (1) ability to reproduce common usage scenarios, (2) space overhead of traces created by the tools, and (3) robustness of traces created by the tools (when being replayed on devices with different resolutions). The results from our comparison show which record-and-replay tools may be the best for developers and identify future directions for improving these tools to better address testing complications of smart devices.\",\"PeriodicalId\":313494,\"journal\":{\"name\":\"Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-08-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"31\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3106237.3117769\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3106237.3117769","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 31

摘要

移动应用程序(简称app)越来越受欢迎。承载这些应用程序的智能设备的输入源(例如,触摸屏、传感器、发射器)使应用程序能够为用户提供丰富的体验,但这些输入源给开发人员带来了测试复杂性(例如,编写测试以准确地利用多个输入源,并能够在以后的时间重放这些测试)。为了减轻这些并发症,研究人员和从业人员近年来开发了各种记录和回放工具来支持智能设备的测试表现力。这些工具允许开发者轻松记录和自动回放他们的应用程序的复杂使用场景。由于Android在智能设备市场的巨大份额,许多记录和回放工具已经开发使用各种技术来测试Android应用程序。为了更好地理解这些工具的优点和缺点,我们对研究人员和从业者的流行记录和回放工具进行了比较,并应用这些工具测试了从Google Play商店下载的三个流行的工业应用程序。我们的比较基于三个主要指标:(1)重现常见使用场景的能力,(2)工具创建的痕迹的空间开销,以及(3)工具创建的痕迹的鲁棒性(当在不同分辨率的设备上重放时)。我们的比较结果显示了哪些记录和回放工具可能是最适合开发人员的,并确定了改进这些工具以更好地解决智能设备测试复杂性的未来方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Record and replay for Android: are we there yet in industrial cases?
Mobile applications, or apps for short, are gaining popularity. The input sources (e.g., touchscreen, sensors, transmitters) of the smart devices that host these apps enable the apps to offer a rich experience to the users, but these input sources pose testing complications to the developers (e.g., writing tests to accurately utilize multiple input sources together and be able to replay such tests at a later time). To alleviate these complications, researchers and practitioners in recent years have developed a variety of record-and-replay tools to support the testing expressiveness of smart devices. These tools allow developers to easily record and automate the replay of complicated usage scenarios of their app. Due to Android's large share of the smart-device market, numerous record-and-replay tools have been developed using a variety of techniques to test Android apps. To better understand the strengths and weaknesses of these tools, we present a comparison of popular record-and-replay tools from researchers and practitioners, by applying these tools to test three popular industrial apps downloaded from the Google Play store. Our comparison is based on three main metrics: (1) ability to reproduce common usage scenarios, (2) space overhead of traces created by the tools, and (3) robustness of traces created by the tools (when being replayed on devices with different resolutions). The results from our comparison show which record-and-replay tools may be the best for developers and identify future directions for improving these tools to better address testing complications of smart devices.
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
期刊最新文献
Serverless computing: economic and architectural impact The rising tide lifts all boats: the advancement of science in cyber security (invited talk) User- and analysis-driven context aware software development in mobile computing Continuous variable-specific resolutions of feature interactions Attributed variability models: outside the comfort zone
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1