How can Machine Learning techniques contribute to test data generation in functional testing?
- Analyzing Code Complexity
- Generating Random Test Data
- Predicting Test Input Values
- Verifying Test Execution Results
Machine Learning techniques contribute to test data generation in functional testing by predicting suitable test input values. By analyzing patterns and historical data, ML algorithms can generate meaningful and relevant test data, improving the effectiveness of functional tests and ensuring a more thorough validation of software functionality.
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