Research Article
Empirical Analysis of Widely Used Website Automated Testing Tools
@ARTICLE{10.4108/airo.7285, author={Balqees Sani and Sadaqat Jan}, title={Empirical Analysis of Widely Used Website Automated Testing Tools}, journal={EAI Endorsed Transactions on AI and Robotics}, volume={3}, number={1}, publisher={EAI}, journal_a={AIRO}, year={2024}, month={10}, keywords={Automated testing tools, Selenium, Performance testing, Cloud-based testing}, doi={10.4108/airo.7285} }
- Balqees Sani
Sadaqat Jan
Year: 2024
Empirical Analysis of Widely Used Website Automated Testing Tools
AIRO
EAI
DOI: 10.4108/airo.7285
Abstract
In today's software development, achieving product quality while minimising cost and time is critical. Automated testing is crucial to attaining these goals by lowering inspection efforts and discovering faults more effectively. This paper compares widely used automated testing tools, such as Selenium, Appium, Java Unit (JUnit), Test Next Generation (TestNG), Jenkins, Cucumber, LoadRunner, Katalon Studio, Simple Object Access Protocol User Interface (SoapUI), and TestComplete, based on functionality, ease of use, platform compatibility, and integration capabilities. Our findings show that no single tool is inherently superior, with each excelling in certain areas such as online, mobile, Application Programming Interface (API), or performance testing. While Selenium and Appium are the dominant online and mobile testing frameworks, TestComplete and Katalon Studio offer complete, user-friendly cross-platform testing solutions. Despite the benefits of automation, obstacles such as tool maintenance, scalability, and cost issues remain. The report finishes with advice for picking the best tool for the project and offers potential approaches for enhancing testing frameworks, such as AI-driven optimisation, cloud-based testing, and greater Continuous Integration/ Continuous Deployment (CI/CD) integration. This study offers useful information for developers and testers looking to optimise their testing methods and increase software quality.
Copyright © 2024 Sani et al., licensed to EAI. This is an open access article distributed under the terms of the CC BY-NCSA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.