How does load testing differ from stress testing in API performance testing?
- Evaluates the system's behavior under extreme conditions beyond its normal capacity.
- Focuses on identifying bottlenecks and potential failures under normal conditions.
- Measures the system's capability to handle a specific load without performance degradation.
- Tests the system's stability and robustness during prolonged use.
Load testing simulates expected load, while stress testing pushes the system to its limits to identify breaking points. Stress testing helps uncover vulnerabilities under extreme conditions that load testing may not reveal.
Which factor is most critical when dealing with large-scale data in API testing?
- Compatibility
- Reliability
- Scalability
- Usability
Scalability is crucial in handling large-scale data in API testing. It ensures that the system can handle increased data loads without compromising performance.
How should error handling be approached when integrating a third-party API?
- Handle errors gracefully and provide meaningful feedback
- Ignore errors and log them for future analysis
- Propagate the errors to the end-user
- Retry the API call
Effective error handling is vital in API integrations. Handling errors gracefully and providing meaningful feedback to users helps in troubleshooting and resolving issues efficiently.
_________ plays a crucial role in API versioning, especially when deciding the lifecycle and deprecation policies for API versions.
- Authorization
- Configuration
- Documentation
- Metadata
Documentation is crucial in API versioning as it provides clear information about the API, including its lifecycle and deprecation policies, aiding developers in understanding changes.
In GraphQL, what is the role of a Schema?
- Define the data structure and types
- Execute queries
- Handle HTTP requests
- Store data in the database
A Schema in GraphQL defines the types of data that can be queried and the relationships between them. It serves as a contract between the client and server, specifying the structure of the API.
In API automation scripts, _________ are used to validate the response and ensure it meets certain criteria.
- Assertions
- Functions
- Loops
- Variables
In API automation, assertions are crucial for validating the response received from the API. They allow you to set criteria and ensure that the API response aligns with the expected results. This helps in verifying the correctness of the API behavior.
SOAP APIs enforce a strict _______ which is essential for enterprise-level web services.
- Language
- Protocol
- Schema
- Style
SOAP APIs enforce a strict schema, defining the structure of data exchanged between systems. This strict structure is crucial for enterprise-level web services, ensuring consistency and reliability in data communication.
In the context of API testing, how does parameterization in data-driven testing enhance test coverage?
- Varied input scenarios
- Code optimization
- Database management
- Error handling
Parameterization in data-driven testing allows testers to use varied input scenarios, covering a wide range of possible inputs and conditions. This enhances test coverage by exploring different combinations of inputs and ensuring the API functions correctly across diverse situations. Options 2, 3, and 4 are not directly related to the concept of parameterization and test coverage.
The HTTP status code _______ is commonly returned when the requested resource does not exist.
- 404
- 400
- 403
- 405
The correct option is 404. This status code indicates that the server could not find the requested resource. It is a standard response for situations where the server cannot locate the requested URL on the server.
What advanced feature in Postman allows for dynamic and conditional scripting in tests?
- Collection Runner
- Newman CLI
- Pre-request Scripts
- Test Scripts
The advanced feature in Postman that allows dynamic and conditional scripting in tests is the Test Scripts. With Test Scripts, you can write JavaScript code to perform complex validations, manipulate data, and create conditional logic. This flexibility enhances the testing capabilities of Postman, making it a powerful tool for API testing with dynamic scenarios.