ABSTRACT
Mobile applications are an essential part of our daily life. In fact, they can be used for tasks that range from reading the news to performing bank transactions. Considering the impact that mobile applications have in our lives, it is important for developers to test them and gain confidence that they behave as expected. However, testing mobile applications proves to be challenging. In fact, mobile companies report that they do not have enough time and the right methods to test. In addition, in the case of Android applications, the situation is further complicated by the "fragmentation" of the ecosystem. Developers not only need to ensure that an application behaves as expected but also need to make sure that the application does so on a multitude of different devices. Finally, because it is virtually impossible to release a bug free application, developers also need to quickly react to bug reports and release a fixed version of the application before customer loss. The research plan proposed in this paper, aims to provide novel techniques to automate the support for mobile application testing and maintenance. Specifically, it proposes techniques to: test apps more effectively and efficiently, tackle the problems caused by the "fragmentation" of the Android ecosystem, and help developers in quickly handling bug reports.
- Nicolas Bettenburg, Sascha Just, Adrian Schröter, Cathrin Weiss, Rahul Premraj, and Thomas Zimmermann. 2008. What Makes a Good Bug Report?. In Proceedings of the 16th ACM SIGSOFT International Symposium on Foundations of Software Engineering. ACM, New York, NY, USA, 308–318. Google ScholarDigital Library
- Pamela Bhattacharya, Liudmila Ulanova, Iulian Neamtiu, and Sai Charan Koduru. 2013.Google Scholar
- David Bolton. 2017.Google Scholar
- 88% Of People Will Abandon An App Because Of Bugs. Retrieved June 29, 2018 from https://www.applause.com/blog/ appabandonmentbugtestingGoogle Scholar
- Capgemini 2018. World Quality Report 2017-18. Retrieved June 29, 2018 from https://www.capgemini.com/service/worldqualityreport- 2017- 18Google Scholar
- Marie-Catherine de Marneffe, Bill MacCartney, and Christopher D. Manning. 2006. Generating Typed Dependency Parses from Phrase Structure Parses. In Proceedings of the Fifth International Conference on Language Resources and Evaluation. European Language Resources Association (ELRA), Genoa, Italy, 449–454.Google Scholar
- Darrell Etherington. 2016. Mobile internet use passes desktop for the first time, study finds. Retrieved June 29, 2018 from https://techcrunch.com/2016/11/01/ mobileinternetusepassesdesktopforthefirsttimestudyfindsGoogle Scholar
- Mattia Fazzini, Eduardo Noronha de A. Freitas, Shauvik Roy Choudhary, and Alessandro Orso. 2017. Barista: A Technique for Recording, Encoding, and Running Platform Independent Android Tests. In 2017 IEEE International Conference on Software Testing, Verification and Validation. IEEE Computer Society, Washington, DC, USA, 149–160.Google ScholarCross Ref
- Mattia Fazzini and Alessandro Orso. 2017. Automated Cross-Platform Inconsistency Detection for Mobile Apps. In Proceedings of the 32nd IEEE/ACM International Conference on Automated Software Engineering. IEEE Computer Society, Washington, DC, USA, 308–318. Google ScholarDigital Library
- Mattia Fazzini, Martin Prammer, and Marcelo d’Amorim Alessandro Orso. 2018.Google Scholar
- Google 2016. Create UI tests with Espresso Test Recorder. Retrieved June 29, 2018 from https://developer.android.com/studio/test/espressotestrecorderGoogle Scholar
- Dongjie He, Lian Li, Lei Wang, Hengjie Zheng, Guangwei Li, and Jingling Xue. 2018. Understanding and Detecting Evolution-induced Compatibility Issues in Android Apps. In Proceedings of the 33rd ACM/IEEE International Conference on Automated Software Engineering. ACM, New York, NY, USA, 167–177. Google ScholarDigital Library
- Yongjian Hu, Tanzirul Azim, and Iulian Neamtiu. 2015. Versatile yet Lightweight Record-and-Replay for Android. In Proceedings of the 2015 ACM SIGPLAN International Conference on Object-Oriented Programming, Systems, Languages, and Applications. ACM, New York, NY, USA, 349–366. Google ScholarDigital Library
- Dan Jurafsky and James H Martin. 2014.Google Scholar
- Speech and language processing. Pearson Education, London, UK.Google Scholar
- Jouko Kaasila, Denzil Ferreira, Vassilis Kostakos, and Timo Ojala. 2012. Testdroid: automated remote UI testing on Android. In 11th International Conference on Mobile and Ubiquitous Multimedia. ACM, New York, NY, USA, 28–31. Google ScholarDigital Library
- Adam Lella and Andrew Lipsman. 2017.Google Scholar
- The 2017 U.S. Mobile App Report. Retrieved June 29, 2018 from https://www.comscore.com/Insights/ Presentations- and-Whitepapers/2017/The- 2017-USMobile-App-ReportGoogle Scholar
- Li Li, Tegawendé F. Bissyandé, Haoyu Wang, and Jacques Klein. 2018.Google Scholar
- Walid Maalej and Hadeer Nabil. 2015. Bug Report, Feature Request, or Simply Praise? On Automatically Classifying App Reviews. In International Requirements Engineering Conference. IEEE Computer Society, Washington, DC, USA, 116–125.Google Scholar
- Kevin Moran, Mario Linares Vásquez, Carlos Bernal-Cárdenas, and Denys Poshyvanyk. 2015. Auto-Completing Bug Reports for Android Applications. In Proceedings of the 2015 10th Joint Meeting on Foundations of Software Engineering. ACM, New York, NY, USA, 673–686. Google ScholarDigital Library
- OpenSignal 2015. Android Fragmentation. Retrieved June 29, 2018 from https: //opensignal.com/reports/2015/08/androidfragmentationGoogle Scholar
- Dennis Pagano and Walid Maalej. 2013.Google Scholar
- User Feedback in the AppStore: An Empirical Study. In 21st IEEE International Requirements Engineering Conference. IEEE Computer Society, Washington, DC, USA, 125–134.Google Scholar
- Avinash Sharma. 2018.Google Scholar
- 8 Quick Tips to Speed Up Android App Development. Retrieved June 29, 2018 from https://appinventiv.com/blog/ 8quicktipsspeed- androidappdevelopmentGoogle Scholar
- Gregory Tassey. 2002. The Economic Impacts of Inadequate Infrastructure for Software Testing. National Institute of Standards and Technology 7007.011 (2002).Google Scholar
Index Terms
- Automated support for mobile application testing and maintenance
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