Automated Data-Driven Testing Demo

Experience how data-driven testing can streamline your test automation by running multiple test cases with different input data sets.

Test Data

Test Case	Username	Password	Expected Result
Valid Credentials	testuser	Test@123	Login Success
Invalid Username	wronguser	Test@123	Login Failed
Invalid Password	testuser	wrongpass	Login Failed
Empty Fields			Login Failed

Add New Test Case

Test Case Name

Username

Password

Expected Result

Test Execution

Key Features of Data-Driven Testing

Reusable Test Logic

Write test scripts once and run them with multiple data sets, reducing code duplication and maintenance effort.

Comprehensive Coverage

Easily test various input combinations, edge cases, and boundary conditions without modifying test code.

Centralized Test Data

Manage all test data in one place, making it easy to update and maintain as requirements change.

Clear Reporting

Get detailed reports showing which data sets passed or failed, helping with quick debugging.

What is Data-Driven Testing?

Data-driven testing is an automated testing methodology where test input and expected results are stored in a separate data source (like spreadsheets, databases, or arrays) and fed into the test script during execution. This approach separates test logic from test data, allowing you to run the same test scenario with multiple data combinations without changing the test code.

Benefits of Data-Driven Testing

Data-driven testing offers several advantages for quality assurance teams:

• Increased Test Coverage: Easily test numerous input combinations that would be time-consuming to test manually
• Reduced Maintenance: Update test data without touching test scripts, making maintenance simpler
• Early Bug Detection: Identify edge cases and boundary conditions that might be missed with manual testing
• Reusability: The same test scripts can be reused with different data sets across projects
• Efficiency: Save time by automating repetitive test scenarios with varying inputs

How Data-Driven Testing Works

The demo above illustrates a typical data-driven testing workflow for a login system:

1. Test data is stored in a structured format (table in this example)
2. The automated test script reads each row of data
3. For each data set, the test script inputs the values and verifies the results
4. Test results are reported, showing which data sets passed or failed

Implementing Data-Driven Testing in Your Projects

To implement data-driven testing effectively:

• Identify test scenarios that can benefit from multiple data inputs
• Design your test scripts to accept external data sources
• Store test data in maintainable formats (CSV, Excel, JSON, databases)
• Implement clear reporting to analyze test results
• Regularly review and update test data as requirements change

Best Practices for Data-Driven Testing

Follow these best practices to get the most from your data-driven testing efforts:

• Keep test data well-organized and documented
• Include both positive and negative test cases
• Use meaningful names for test cases to make reports readable
• Parameterize your tests to handle different data types
• Implement data cleanup between test runs when needed