Design and Analysis of a Mobile Automation Testing Framework: Evidence and AI Enhancement from Chinese Internet Technological Companies

A Case Study

Authors

  • Jun Cui
  • Wangmei Chen
  • Qiang Wan
  • Zhongxin Gan
  • Zihao Ning

DOI:

https://doi.org/10.54097/xevpea32

Keywords:

The qualitative and quantitative mixed analysis, Appium framework, IOS and Android framework, mobile automation framework and AI enhancement technologies.

Abstract

This present study mainly describes the implementation and ideas of the mobile automation framework, which supports iOS and Android mobile automation testing technology. This study mainly uses a combination of qualitative and documentary analysis methods, designs some technical architecture diagrams, and writes some open-source code to implement respectively. Meanwhile, The automation code is not made public due to mobile automation security and privacy concerns. The paper is mainly driven by the so file inside Android and the ADB command, while iOS uses some class libraries based on the iOS system. The research framework also uses the Appium framework for encapsulation and research and carries out secondary encapsulation and call based on the internal Appium framework. It is convenient for the internal quality team's automated testing staff to use and execute and improve the efficiency and speed of automated software testing, which is the contribution of this research. Beside, The limitation of this research is that the framework is based on the secondary development and encapsulation of Appium framework, so this study are inevitably some imperfections and bugs that need to be continuously improved and used. Moreover, these contribution results demonstrate that it can combine the businesses of different china internet enterprises to complete. Next, the paper discusses specific cases of mobile automation testing framework and artificial intelligence in mobile framework design and evaluates their effects and impacts. Finally, the paper summarizes the roles and challenges of mobile automation testing framework design and AI enhancement elements and looks ahead to the future.

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References

Septian, I., & Alianto, R. S. (2018). Comparison analysis of android gui testing frameworks by using an experimental study. Procedia Computer Science, 135, 736-748.

Singh, S., Gadgil, R., & Chudgor, A. (2014). Automated testing of mobile applications using scripting technique: A study on appium. International Journal of Current Engineering and Technology (IJCET), 4(5), 3627-3630.

Hussain, A., Razak, H. A., & Mkpojiogu, E. O. (2017). The perceived usability of automated testing tools for mobile applications. Journal of Engineering, Science and Technology (JESTEC), 12(4), 89-97.

Lovreto, G., Endo, A. T., Nardi, P., & Durelli, V. H. (2018, October). Automated tests for mobile games: An experience report. In 2018 17th Brazilian Symposium on Computer Games and Digital Entertainment (SBGames) (pp. 48-488). IEEE.

Coppola, R., Ardito, L., & Torchiano, M. (2019, August). Fragility of layout-based and visual GUI test scripts: an assessment study on a hybrid mobile application. In Proceedings of the 10th acm sigsoft international workshop on automating test case design, selection, and evaluation (pp. 28-34).

Pyshkin, E., & Mozgovoy, M. (2018). So You Want to Build a Farm: An Approach to Resource and Time Consuming Testing of Mobile Applications. ICSEA 2018, 101.

Anjum, H., Babar, M. I., Jehanzeb, M., Khan, M., Chaudhry, S., Sultana, S., ... & Bhatti, S. N. (2017). A comparative analysis of quality assurance of mobile applications using automated testing tools. International Journal of Advanced Computer Science and Applications, 8(7).

E. E. Reber, R. L. Michell, and C. J. Carter, “Oxygen absorption in the Earth’s atmosphere,” Aerospace Corp., Los Angeles, CA, Tech. Rep. TR-0200 (420-46)-3, Nov. 1988.

Cruz, L., & Abreu, R. (2018, May). Measuring the energy footprint of mobile testing frameworks. In Proceedings of the 40th International Conference on Software Engineering: Companion Proceeedings (pp. 400-401).

Vadan, A. M., & Miclea, L. C. (2023). Software testing techniques for improving the quality of smart-home iot systems. Electronics, 12(6), 1337.

Thant, K., Khaung, T., & Ind, H. H. I. (2023). The impact of manual and automatic testing on software testing efficiency and effectiveness. Indian journal of science and research, 3(3), 88-93.

Berihun, N. G., Dongmo, C., & Van der Poll, J. A. (2023). The Applicability of Automated Testing Frameworks for Mobile Application Testing: A Systematic Literature Review. Computers, 12(5), 97.

Godboley, S., Dalei, D., Sadam, R., & Mohapatra, D. P. (2023, March). Agile GUI Testing by computing novel Mobile App Coverage Using Appium Tool. In Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing (pp. 1026-1029).

Heid, K., Tefke, T., Heider, J., & Staudemeyer, R. C. (2022). Android Data Storage Locations and What App Developers Do with It from a Security and Privacy Perspective. In ICISSP (pp. 378-387).

Gu, R., & Rojas, J. M. (2023, September). An Empirical Study on the Adoption of Scripted GUI Testing for Android Apps. In 2023 38th IEEE/ACM International Conference on Automated Software Engineering Workshops (ASEW) (pp. 179-182). IEEE

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Published

06-04-2024

Issue

Section

Articles

How to Cite

Cui, J., Chen, W., Wan, Q., Gan, Z., & Ning, Z. (2024). Design and Analysis of a Mobile Automation Testing Framework: Evidence and AI Enhancement from Chinese Internet Technological Companies: A Case Study. Frontiers in Business, Economics and Management, 14(2), 163-170. https://doi.org/10.54097/xevpea32