Which of the following best explains why API testing is crucial for validating backend logic?
Think about what happens behind the scenes when data is sent or received.
API testing focuses on the backend by checking if the server processes requests and returns correct responses, validating the backend logic.
What will be the output of this test code snippet that validates an API response status?
response = {'status_code': 200, 'data': {'id': 1, 'name': 'Test'}}
assert response['status_code'] == 200
print('Test Passed')Check if the status code matches the expected value.
The assertion checks if the status code is 200, which it is, so the print statement runs.
Which assertion correctly verifies that the API response contains a 'user' key with a non-empty 'id' field?
response = {'user': {'id': 123, 'name': 'Alice'}}Focus on checking the 'id' field is present and valid.
Option C asserts the 'id' is greater than zero, ensuring it is a valid non-empty value.
What error will this API test code raise?
response = {'status': 404, 'error': 'Not Found'}
assert response['status_code'] == 200Check the keys used in the response dictionary.
The code tries to access 'status_code' which does not exist, causing a KeyError.
Which design choice best supports maintainability and scalability in an API test automation framework?
Think about how to easily update tests when APIs change.
Centralizing configuration and using reusable functions makes tests easier to maintain and scale.