Artificial Intelligence Applied to Software Testing

Abstract

The study investigates the background, advantages, and difficulties of AI-based testing. The use of artificial intelligence (AI) has shown great promise as a means of enhancing software testing procedures. To improve test case generation, bug prediction, and test result analysis, AI-based testing approaches use machine learning, NLP (natural language Processing), GUIs(graphical user interfaces), genetic algorithms, and robotic process automation. We also provide a brief literature review of recent studies in the field, focusing on the various approaches and tools proposed for AI-based software testing. We conclude with a strategy for introducing AI-based testing and a list of possible approaches and resources. Overall, this paper provides a comprehensive survey of AI-based software testing and highlights the potential benefits and challenges of this emerging field.

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