From Scripts to Intelligence: How AI is Reshaping the Future of Software Testing

Shirley Ugwa *

Independent Researcher, Stoke-on-trent, United Kingdom.
 
Research Article
World Journal of Advanced Engineering Technology and Sciences, 2024, 13(01), 1167-1179.
Article DOI: 10.30574/wjaets.2024.13.1.0449
Publication history: 
Received on 14 August 2024; revised on 24 September 2024; accepted on 26 September 2024
 
Abstract: 
With the increased complexity of the software systems and the need for quick, high-quality releases, traditional testing methods cannot catch up. This article focuses on artificial intelligence's (AI) transformational influence on the software testing environment, with detailed progress from the manual and script-based approach to intelligent adaptive frameworks. It illustrates the shortcomings of legacy test methods. It demonstrates how AI, using machine learning, natural language processing, and neural networks, allows test automation to become more accurate, scalable, and predictive.
Major applications, including AI-based test case generation, defect prediction, and self-healing scripts, are discussed in detail, as well as generative AI models such as ChatGPT for scenario creation and documentation. The article also examines future trends, such as hybrid human-AI testing models and advances in the generative AI that will completely change the quality assurance game. By incorporating AI in the testing workflows, organizations can optimally increase efficiency, decrease time to market, and improve software reliability.
The research detects that AI does not replace human testers but enhances them by helping develop strategic, creative, and user-centric quality assurance activities. As companies try to be agile and competitive, a decision to implement AI-powered testing is not optional but necessary. This change indicates more than a technological evolution; it changes how software quality is maintained in the digital age.
 
Keywords: 
Artificial intelligence in Testing; AI-Powered Software Testing; Generative AI for QA; Test Automation with Machine Learning; Self-Healing Test Scripts; Large Language Models in Software Testing
 
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Copyright information: 
Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0