Scalable Mobile Automation Testing Frameworks for Government Digital Service Platforms
Abstract
It must be ensured that automation testing frameworks can be used to test government mobile applications to ensure that the workflows are correct, accessibility standards, and cross platform behavior are met on a large scale. The paper presents a proposed scalable mobile automation testing framework, which can be used to test public-sector applications, consisting of UI automation, API-validation, accessibility testing, and regression coverage on both the iOS and Android platforms. This framework focuses on the maintainability, isolation of tests in the test environment, functionality of CI/CD pipelines, which give government agencies the ability to maintain a high rate of releases without affecting the compliance to reliability and security as well as accessibility. Besides, it also points to an Appium-based architecture that will provide the flexibility and scalability of testing. The strategy will make sure that the mobile application in the public sector can address the special needs of security, compliance and performance and sustain a sound testing ecosystem. This framework will provide the government agencies with an effective tool to test the automation to provide faster and more reliable deployment cycles and enhance the overall quality of mobile digital services
Article Information
Journal |
International Journal of Advanced Engineering Science and Information Technology (IJAESIT) |
|---|---|
Volume (Issue) |
Vol. 7 No. 4 (2024): International Journal of Advanced Engineering Science and Information Technology (IJAESIT) |
DOI |
|
Pages |
14455-14465 |
Published |
July 9, 2024 |
| Copyright | |
Open Access |
This work is licensed under a Creative Commons Attribution 4.0 International License. |
How to Cite |
Mahendar Ramidi (2024). Scalable Mobile Automation Testing Frameworks for Government Digital Service Platforms. International Journal of Advanced Engineering Science and Information Technology (IJAESIT) , Vol. 7 No. 4 (2024): International Journal of Advanced Engineering Science and Information Technology (IJAESIT) , pp. 14455-14465. https://doi.org/10.15662/IJAESIT.2024.0704002 |
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