Aritificial Intelligence in Test Automation Platform – A Comparative Review

Abstract

Software testing is considered as the critical aspect in terms of developing the software. As software systems become more intricate, old-style testing procedures are increasingly impractical. Recently, Artificial Intelligence (AI) has appeared as a promising alternative testing the software. This review study investigates the latest trends and current practices in Artificial Intelligence -driven software testing, evaluating various approaches, techniques, and tools to assess their effectiveness. Testing the software is considered as the fundamental section of the Software Development Life Cycle, and with the tech sectors focus on delivering superior quality applications, many testers are transitioning from manual to test automation to save time and expenses. There is a vast selection of software testing tools available, both open-source and commercial, making it challenging to choose the best tool due to the growing number of options. As the variety of tools increases, so does the range of features and cost differences. Web application testing tools, which are widely used today, provide developers with more convenient testing options, and their integration with web browsers has made testing more modular. Selecting the right testing tool involves assessing various factors to ensure it meets the specific needs of the software being tested. This work aims to recognize and contrast popular testing tools, offering a contrast review of open-source and commercial tools in a tabular format based on diverse parameters. It also designates the topographies of several testing tools to aid end users and programmers in selecting the most suitable ones for their needs.