Predictive Analytics in Test Automation uses data analysis and machine learning to forecast potential test failures and application risks before they occur. It analyzes historical test results, defect patterns, and code changes to identify areas likely to cause issues. This helps teams prioritize test cases and focus on high-risk components. It also improves test coverage by suggesting where additional testing is needed. Predictive analytics reduces testing time and improves software quality by enabling proactive decision-making. It is widely used in continuous testing and DevOps environments. This approach enhances efficiency, accuracy, and reliability in modern test automation processes.
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