[go: up one dir, main page]
More Web Proxy on the site http://driver.im/ skip to main content
10.1145/3387905.3388603acmconferencesArticle/Chapter ViewAbstractPublication PagesicseConference Proceedingsconference-collections
abstract

Improving app quality despite flawed mobile analytics

Published: 07 October 2020 Publication History

Abstract

Analytics can help improve the quality of software; the improvements are affected by the fidelity of the analytics. The impact of poor fidelity may vary depending on the type of data being collected, for example, for crashes low fidelity may be sufficient.
The mobile ecosystem includes a platform where apps run and an app store that intermediates between developers and users. Google's Android ecosystem provides all the developers with analytics about various qualities of their app through a service called Android Vitals that automatically collects data on how their app is performing.
My research found ways to improve app quality through using mobile analytics, including Android Vitals. It also found fidelity flaws in several analytics tools provided by Google. They confirmed and validated some flaws and chose not to discuss others.

References

[1]
Afnan AlSubaihin, Federica Sarro, Sue Black, Licia Capra, and Mark Harman. 2019. App store effects on software engineering practices. IEEE Transactions on Software Engineering 50, 8 (2019), 1--19.
[2]
Android Developers. 2020. Android vitals. https://developer.android.com/topic/performance/vitals
[3]
Android Developers. 2020. Crashes - Android Developers. Google. https://developer.android.com/topic/performance/vitals/crash
[4]
AppBrain. 2020. Android analytics libraries. https://www.appbrain.com/stats/libraries/tag/analytics/android-analytics-libraries
[5]
Raymond PL Buse and Thomas Zimmermann. 2010. Analytics for software development. In Proceedings of the FSE/SDP workshop on Future of software engineering research. ACM, ACM, Santa Fe, New Mexico, USA, 77--80.
[6]
Raymond PL Buse and Thomas Zimmermann. 2012. Information needs for software development analytics. In Proceedings of the 34th international conference on software engineering. IEEE Press, IEEE, Zurich, Switzerland, 987--996.
[7]
Catrobat Project Team. 2019. Developer's website for the Catrobat project. Catrobat Project. https://developer.catrobat.org/
[8]
Bin Fu, Jialiu Lin, Lei Li, Christos Faloutsos, Jason Hong, and Norman Sadeh. 2013. Why people hate your app: Making sense of user feedback in a mobile app store. In Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining. ACM, ACM, Chicago, Illinois, USA, 1276--1284.
[9]
Julian Harty. 2019. Google Play Console: Insightful Development using Android Vitals and Pre-Launch Reports. In MOBILESoft 2019. IEEE, IEEE, Montreal, QC, Canada, 62 -- 65.
[10]
Julian Harty. 2020. How Can Software Testing be Improved by Analytics to Deliver Better Apps?. In 2020 13th IEEE Conference on Software Testing, Validation and Verification (ICST). IEEE, Porto, Portugal.
[11]
J. Harty and A. Aymer. 2015. The Mobile Analytics Playbook: A Practical Guide to Better Testing. Hewlett Packard Enterprise. 161 pages.
[12]
Julian Harty and Matthias Müller. 2019. Better Android Apps Using Android Vitals. In WAMA 2019. ACM, ACM, Tallinn, Estonia, 26 -- 32.
[13]
Thomas Hirsch, Christian Schindler, Matthias Müller, Thomas Schranz, and Wolfgang Slany. 2019. An Approach to Test Classification in Big Android Applications. In 2019 IEEE 19th International Conference on Software Quality, Reliability and Security Companion (QRS-C). IEEE, 300--308.
[14]
Daniel J Hughes. 1995. Moltke on the art of war: Selected writings. Random House Digital, Inc., USA.
[15]
Dan Lew. 2018. How to Release a Buggy App (And Live to Tell the Tale). https://tech.trello.com/how-to-release-a-buggy-app-and-live-to-tell-the-story/
[16]
Kirshan Kumar Luhana, Christian Schindler, and Wolfgang Slany. 2018. Streamlining mobile app deployment with Jenkins and Fastlane in the case of Catrobat's pocket code. In 2018 IEEE International Conference on Innovative Research and Development (ICIRD). IEEE, 1--6.
[17]
Robert Musson, Jacqueline Richards, Danyel Fisher, Christian Bird, Brian Bussone, and Sandipan Ganguly. 2013. Leveraging the crowd: How 48,000 users helped improve lync performance. IEEE software 30, 4 (2013), 38--45.
[18]
Sebastiano Panichella, Andrea Di Sorbo, Emitza Guzman, Corrado A Visaggio, Gerardo Canfora, and Harald C Gall. 2015. How can I improve my app? classifying user reviews for software maintenance and evolution. In 2015 IEEE international conference on software maintenance and evolution (ICSME). IEEE, 281--290.
[19]
Lorenzo Villarroel, Gabriele Bavota, Barbara Russo, Rocco Oliveto, and Massimiliano Di Penta. 2016. Release planning of mobile apps based on user reviews. In 2016 IEEE/ACM 38th International Conference on Software Engineering (ICSE). IEEE, 14--24.

Cited By

View all
  • (2024)Taming App Reliability: Mobile Analytics “in the wild”Proceedings of the 28th International Conference on Evaluation and Assessment in Software Engineering10.1145/3661167.3661169(450-453)Online publication date: 18-Jun-2024
  • (2021)Logging Practices with Mobile Analytics: An Empirical Study on Firebase2021 IEEE/ACM 8th International Conference on Mobile Software Engineering and Systems (MobileSoft)10.1109/MobileSoft52590.2021.00013(56-60)Online publication date: May-2021

Recommendations

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Conferences
MOBILESoft '20: Proceedings of the IEEE/ACM 7th International Conference on Mobile Software Engineering and Systems
July 2020
158 pages
ISBN:9781450379595
DOI:10.1145/3387905
  • General Chair:
  • David Lo,
  • Program Chairs:
  • Leonardo Mariani,
  • Ali Mesbah
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

Sponsors

In-Cooperation

  • IEEE CS

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 07 October 2020

Check for updates

Author Tags

  1. Android-vitals
  2. crashlytics
  3. firebase
  4. mobile-analytics

Qualifiers

  • Abstract

Conference

MOBILESoft '20
Sponsor:

Upcoming Conference

ICSE 2025

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)22
  • Downloads (Last 6 weeks)0
Reflects downloads up to 25 Dec 2024

Other Metrics

Citations

Cited By

View all
  • (2024)Taming App Reliability: Mobile Analytics “in the wild”Proceedings of the 28th International Conference on Evaluation and Assessment in Software Engineering10.1145/3661167.3661169(450-453)Online publication date: 18-Jun-2024
  • (2021)Logging Practices with Mobile Analytics: An Empirical Study on Firebase2021 IEEE/ACM 8th International Conference on Mobile Software Engineering and Systems (MobileSoft)10.1109/MobileSoft52590.2021.00013(56-60)Online publication date: May-2021

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media