A Generative AI Framework for Enhancing Software Test Automation: Design, Implementation, and Validation
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


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Informative Article | Computer Science and Information Technology | United States of America | Volume 13 Issue 6, June 2024 | Popularity: 5.7 / 10


     

A Generative AI Framework for Enhancing Software Test Automation: Design, Implementation, and Validation

Narendar Kumar Ale


Abstract: The integration of Generative AI in software test automation can revolutionize testing processes by enhancing efficiency, accuracy, and coverage. This paper introduces a novel framework that leverages Generative AI for autonomous test case generation, execution, and validation. By utilizing advanced machine learning algorithms, our framework addresses key challenges in traditional test automation, such as maintaining test coverage and adapting to frequent software changes. Experimental results on a real - world e - commerce platform show a 20% improvement in defect detection and a 30% reduction in test execution time compared to traditional methods, validating the effectiveness of our approach.


Keywords: Generative AI, Test Automation, Machine Learning, Software Testing, AI - driven Testing, Automation Framework


Edition: Volume 13 Issue 6, June 2024


Pages: 571 - 574


DOI: https://www.doi.org/10.21275/SR24604032016


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Narendar Kumar Ale, "A Generative AI Framework for Enhancing Software Test Automation: Design, Implementation, and Validation", International Journal of Science and Research (IJSR), Volume 13 Issue 6, June 2024, pp. 571-574, https://www.ijsr.net/getabstract.php?paperid=SR24604032016, DOI: https://www.doi.org/10.21275/SR24604032016

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