Autonomous Test Oracles: Integrating AI for Intelligent Decision-Making in Automated Software Testing
Keywords:
Autonomous Test Oracles, Artificial Intelligence, Automated Software Testing, Intelligent Decision-Making, Machine Learning, Software Defects, AI-driven ModelsAbstract
Artificial Intelligence (AI) integration in test oracles provides an unprecedented means to apply intelligent decision-making to automated software testing. This research describes the autonomous development of test oracles based on AI techniques that can provide higher accuracy and efficiency at defect identification. We show that existing methodologies are significantly improved over traditional oracles or current state-of-the-art AI techniques in various testing scenarios by analyzing the existing AI methodologies and implementing the AI-driven models. The proposed framework demonstrates the benefit of using AI techniques in software testing and looks toward future developments and industry applications of such innovations.
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