AI and ML: The New Frontier in Testing

Test data Generation: The importance of comprehensive and diverse test data cannot be overstated. However, manually creating such data sets can be time-consuming, error-prone, and often fails to cover all possible scenarios. AI/ML algorithms analyse existing data models, understand the underlying structures, and use this knowledge to synthesize new test data. This automated approach ensures that generated data is representative of real-world scenarios, enabling more effective testing. AI-powered test data generation tools can dynamically mutate existing datasets to create variations, mimicking different user behaviours, system states, and environmental conditions. This dynamic approach enhances test coverage by exploring a broader range of scenarios.

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