Preconditions

1. The user has access to the API specifications that need to be tested.
2. The user has access to a testing tool capable of interpreting Gherkin syntax and executing tests (e.g., ratl.ai configured with Gherkin and test execution capabilities).

Main Success Scenario

1. Input API Specifications

• The user uploads or provides a link to the API specifications within the testing tool.

2. Generate Gherkin Scenarios

• Based on the API specifications, the testing tool automatically generates Gherkin scenarios.
• These scenarios describe the expected behaviors of the API in a structured format, understandable by both technical and non-technical stakeholders.

3. Review Gherkin Scenarios

• The user reviews the generated Gherkin scenarios to ensure they accurately reflect the intended use cases.
• The review ensures that all necessary functionality of the API is covered.

4. Generate Test Code

• The testing tool translates the Gherkin scenarios into executable test code compatible with the test environment.
• This step may involve setting up test harnesses, mocks, and other dependencies required for test execution.

5. Execute End-to-End (E2E) Tests

• The user initiates the execution of the test code.
• The testing tool runs the E2E tests, simulating real-world usage of the API to verify its behavior against the defined scenarios.

6. Analyze Test Results

• Upon completion of the tests, the tool presents the results, highlighting successes and failures.
• Detailed logs and error messages are provided to help identify any issues.

7. Iterate Based on Feedback

• Based on the test results, the user refines the Gherkin scenarios and test code if necessary, addressing any failures or gaps in testing coverage.
• The refined tests are re-run to verify the changes and ensure the API meets the quality standards.

Postconditions

1. The API has been thoroughly tested against its specifications using Gherkin scenarios.
2. All identified issues have been documented and addressed.

Extensions

Scenario Optimization

• After initial test runs, the testing tool may suggest optimizations in the Gherkin scenarios to improve coverage or efficiency.
• These suggestions may leverage AI analysis or historical data.

Continuous Integration (CI) Integration

• The testing process is integrated into a CI pipeline, allowing for automated testing every time changes are made to the API or its specifications.

Frequency of Use

This use case is typically executed:

• At every major API release.
• During regular sprints.
• Whenever significant changes are made to the API specifications.

Special Requirements

1. High Availability and Scalability:
   The testing infrastructure must handle potentially large numbers of API calls.

2. Security Measures:
   Adequate protections are required to safeguard sensitive data used in test scenarios.

By leveraging automated tools like ratl.ai, the entire API testing process becomes faster, more reliable, and scalable. This ensures that APIs meet quality standards and remain robust in dynamic environments.