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Test automation in open-source Android apps: a large-scale empirical study

Published: 27 January 2021 Publication History
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  • Abstract

    Automated testing of mobile apps has received significant attention in recent years from researchers and practitioners alike. In this paper, we report on the largest empirical study to date, aimed at understanding the test automation culture prevalent among mobile app developers. We systematically examined more than 3.5 million repositories on GitHub and identified more than 12, 000 non-trivial and real-world Android apps. We then analyzed these non-trivial apps to investigate (1) the prevalence of adoption of test automation; (2) working habits of mobile app developers in regards to automated testing; and (3) the correlation between the adoption of test automation and the popularity of projects. Among others, we found that (1) only 8% of the mobile app development projects leverage automated testing practices; (2) developers tend to follow the same test automation practices across projects; and (3) popular projects, measured in terms of the number of contributors, stars, and forks on GitHub, are more likely to adopt test automation practices. To understand the rationale behind our observations, we further conducted a survey with 148 professional and experienced developers contributing to the subject apps. Our findings shed light on the current practices and future research directions pertaining to test automation for mobile app development.

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    cover image ACM Conferences
    ASE '20: Proceedings of the 35th IEEE/ACM International Conference on Automated Software Engineering
    December 2020
    1449 pages
    ISBN:9781450367684
    DOI:10.1145/3324884
    This work is licensed under a Creative Commons Attribution International 4.0 License.

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    Published: 27 January 2021

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    Author Tags

    1. Android
    2. automated testing
    3. empirical study
    4. mobile apps

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    • (2023)Assistive-Technology Aided Manual Accessibility Testing in Mobile Apps, Powered by Record-and-ReplayProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3580679(1-20)Online publication date: 19-Apr-2023
    • (2023)Mobile Test Script Generation from Natural Language Descriptions2023 IEEE 23rd International Conference on Software Quality, Reliability, and Security (QRS)10.1109/QRS60937.2023.00042(348-359)Online publication date: 22-Oct-2023
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