What is testdata in manual testing?

In manual testing, test data refers to the input or set of inputs that are provided to a software application during the execution of test cases. Test data is essential for testing the functionality, behavior, and performance of the application under various scenarios. The purpose of using different test data sets is to ensure that the application behaves correctly and produces the expected results in a variety of situations.

Key points related to test data in manual testing:

1. Types of Test Data:

   • Positive Test Data: Data that is expected to produce valid and expected results.
   • Negative Test Data: Data that is intentionally designed to produce errors or uncover vulnerabilities in the application.
   • Boundary Test Data: Data that falls on the edge or boundary conditions of the input domain.
   • Random Test Data: Test data generated randomly to test the application's response to unexpected inputs.

2. Test Data Considerations:

   • Data Completeness: Ensure that the test data covers all possible scenarios and input variations.
   • Data Quality: Use accurate, relevant, and realistic data to simulate real-world scenarios.
   • Data Security: Be mindful of sensitive or personal information in the test data, especially when testing in a non-production environment.

3. Test Data Management:

   • Organizing Test Data: Manage and organize test data to make it easy to use and maintain. This includes creating datasets for different test scenarios.
   • Version Control: Implement version control for test data to track changes and maintain consistency across testing cycles.
   • Data Masking: Mask or anonymize sensitive information to comply with privacy and security regulations.

4. Data-Driven Testing:

   • Data-Driven Testing (DDT): In data-driven testing, the same test script is executed with different sets of input data. This helps achieve better test coverage and reduces the need for redundant test scripts.

5. Test Data Preparation:

   • Data Generation: Generate test data systematically or use tools to create large datasets for testing purposes.
   • Data Extraction: Extract data from various sources, such as databases or external files, for testing.

6. Test Scenarios and Test Cases:

   • Mapping to Test Scenarios: Associate test data with specific test scenarios and test cases to ensure comprehensive coverage.
   • Positive and Negative Scenarios: Test data should cover both positive and negative scenarios to validate the application's behavior in various conditions.

7. Data Dependencies:

   • Identify Dependencies: Recognize and account for any dependencies between test cases or scenarios that may influence the test data required.

8. Documentation:

   • Documenting Test Data: Document the test data used in each test case, including its purpose and expected outcomes. This documentation aids in test execution and troubleshooting.

In summary, test data in manual testing is a critical component that helps verify the functionality, reliability, and robustness of an application under different conditions. Proper management, preparation, and documentation of test data contribute to effective manual testing practices.