Published Paper Details:

The intricate nature of healthcare applications, handling sensitive patient data and influencing critical medical decisions, demands rigorous testing strategies. While manual testing remains vital, its limitations in efficiency and error susceptibility hinder comprehensive software evaluation. Test Automation Frameworks (TAFs) emerge as a powerful solution, streamlining the testing process for healthcare applications. We explore how TAFs enhance testing efficiency by automating repetitive tasks, allowing testers to focus on high-level and exploratory scenarios. This not only reduces testing costs but also leads to improved test accuracy and repeatability. TAFs enable running a broader spectrum of test cases, encompassing regression testing, edge cases, and integration testing, resulting in more comprehensive test coverage and reduced risks of undetected defects. This paper delves into the multifaceted advantages and practical uses of TAFs within the healthcare software domain. This paper further explores potential future directions for TAFs in the healthcare domain. Advancements in machine learning and artificial intelligence hold promise for enhanced test automation capabilities, enabling automated test generation and self-healing test scripts. Integrating TAFs with continuous integration/continuous delivery (CI/CD) pipelines streamlines the development process for healthcare applications. Embracing TAFs and staying at the forefront of technological advancements will allow developers and healthcare institutions to guarantee the quality and reliability of healthcare applications, ultimately contributing to improved patient care outcomes