Artificial Intelligence in Automated Testing Environments
DOI:
https://doi.org/10.55544/sjmars.2.4.5Keywords:
Artificial Intelligence, Component Behaviour, Software Applications, Test Automation, Smart Manufacturing, Machine Learning, Software Testing, AI IndustryAbstract
Artificial intelligence is developing at a breakneck pace, and its combination with automation has begun to transform the corporate environment. Businesses are concentrating on employing current AI in conjunction with automated procedures to achieve unprecedented levels of productivity and quality. The revolutionary impact of AI-driven reporting for test automation is explored in this research study. By using artificial intelligence, we enable test automation to provide useful insights in addition to problem detection. Every day, enormous volumes of data are produced from several sources, which must be properly tracked, analysed, reported on, and used to guide action. With the development of more sophisticated software programs, time is becoming a crucial consideration in the deployment of applications that need to be thoroughly tested and adhere to business requirements. AI is essential to software testing because it can provide faster and more reliable findings. These malfunctions may be hazardous and often happen during testing. Understanding component behaviour is essential for putting into practice effective defences against failure. While it is currently difficult to predict random component failures, artificial intelligence (AI) enables predictive failure simulation by intelligently simulating real-world conditions. Failure prediction is then possible by comparing simulated component behaviour with actual data, which is useful for maintenance and spare provisioning plans. As AI technology in automotive systems continues to advance, it is becoming increasingly important to address current issues and prevent future failures. Virtual reality and preventive maintenance are essential for understanding system behaviour and preventing failures.
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