"Confirms that new changes haven’t broken existing functionality. Maintains stability across releases. Often automated for efficiency."

"Measures responsiveness and stability under load. Identifies bottlenecks and scalability issues. Includes throughput, latency, and resource usage. Simulates peak user loads and extreme conditions. Evaluates system resilience and recovery. Helps plan infrastructure capacity."

"Ensure data is accurately stored, retrieved, updated, and deleted. Validate referential integrity (foreign key relationships). Test for valid data formats (e.g., dates, currency). Ensure business rules are enforced at the DB level"

"Speeds up repetitive testing tasks. Enhances test coverage and consistency. Uses tools like Selenium, Cypress, or Playwright."

"Validates model accuracy, bias, and fairness. Tests data drift, prediction reliability, and explainability. Ensures ethical and robust AI behavior."

"Provides insights into test coverage, defect density, and release readiness. Enables data-driven decision-making. Supports continuous improvement."