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Enhancing Software Testing Through Artificial Intelligence: A Comprehensive Review
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Author(s): Ekrem Erol (Istanbul University-Cerrahpasa, Turkey)and Sibel Senan (Istanbul University-Cerrahpasa, Turkey)
Copyright: 2024
Pages: 18
Source title:
Advancing Software Engineering Through AI, Federated Learning, and Large Language Models
Source Author(s)/Editor(s): Avinash Kumar Sharma (Sharda University, India), Nitin Chanderwal (University of Cincinnati, USA), Amarjeet Prajapati (Jaypee Institute of Information Technology, India), Pancham Singh (Ajay Kumar Garg Engineering College, Ghaziabad, India)and Mrignainy Kansal (Netaji Subhas University of Technology (NSUT), Delhi, India)
DOI: 10.4018/979-8-3693-3502-4.ch012
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Abstract
Software testing, a pivotal phase in the software development lifecycle, is becoming increasingly challenging with the escalating complexity of modern software. Traditional testing methods are often inadequate in this evolving landscape. As AI continues to advance, its application in software testing is anticipated to lead to more efficient and effective processes, potentially transforming the entire software development lifecycle. This study focuses on conducting an in-depth analysis of the integration of artificial intelligence (AI) in software testing. By thoroughly analyzing and comparing a wide range of AI methodologies, this chapter aims to provide a comprehensive understanding of AI's current and future role in software testing, serving as a valuable resource for both practitioners and researchers in the field.
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