- Accuracy and reliability: Data-driven testing ensures accurate and reliable results by using actual data to drive the test scenarios. It eliminates guesswork and assumptions, reducing the chance of human error.
- Comprehensive test coverage: Data-driven testing allows for testing multiple combinations of values and scenarios, ensuring comprehensive coverage of test cases. It considers various data sets and data variations that may uncover bugs and defects that may arise in real-world situations.
- Reusability: With data-driven testing, test scripts can be easily reused for different data sets and scenarios. This improves efficiency and reduces the time and effort required for testing. It also allows for quick modifications to the test data, enabling testers to quickly adapt to changing testing requirements.
- Scalability: Data-driven testing allows for scalability, as it can handle a large amount of test data without increasing the complexity of the test scripts. It can easily accommodate additional data sets or scenarios without impacting the overall testing process.
- Flexibility: Data-driven testing provides flexibility to change or update test data without modifying the test scripts. This allows for easy maintenance and adaptation to changing business requirements.
- Higher test coverage: By taking advantage of different combinations of test data, data-driven testing can achieve higher test coverage. It ensures that all possible scenarios are tested, increasing the chances of finding defects and vulnerabilities.