Codeless Web Testing using Selenium and Machine Learning

Duyen Nguyen, Stephane Maag


Complexity of web systems lead to development processes always more tough to test. Testing phases are crucial in software and system engineering and are known to be very costly. While automated testing methods appear to take over the role of the human testers, the issues of reliability and the capability of the testing method still need to be solved. In our paper, we focus on the automation of functional tests of websites. A single web page may contain a huge set of important functionalities leading to the execution of critical web service operations. Besides, testing all of these functionalities implemented in a web page service is highly complex. Two current popular research areas for automation web-based testing are Codeless Functional Test Automation and Machine Learning/Artificial Intelligence (ML/AI) in test automation. We therefore define and implement a framework to figure out how to automate the web service product under test, the machine can detect or predict the change and adapt those changes to suitable generic test cases. In our work, we examine on Selenium and the benefits of using machine learning in automated web application testing.


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