However, while API testing is essential, it’s also surprisingly difficult to get right. From lack of documentation to complex dependencies, testing APIs introduces a unique set of challenges that many teams underestimate.
In this blog, we’ll explore the key difficulties of API testing, why they matter, and how to start overcoming them.
- Incomplete or Poor API Documentation
One of the most common (and frustrating) problems in API testing is missing or outdated documentation.
Testers rely heavily on documentation to understand:
- Available endpoints
- Input/output formats
- Authentication methods
- Expected status codes
- Business logic
When this information is vague or inconsistent, it becomes nearly impossible to design reliable test cases.
Example:
A developer creates a /payment/submit API that returns a 200 OK, but doesn’t document how it behaves when the credit card is invalid. The tester now has to guess or reverse-engineer the logic.
Tip: Encourage developers to use tools like Swagger/OpenAPI and keep them updated alongside code changes.
- Rapidly Changing APIs in Agile Teams
In Agile environments, APIs often change frequently and without notice — new parameters, deprecated endpoints, changed payloads. This makes test scripts brittle and requires constant maintenance.
Example:
A GET /user endpoint starts requiring a role query param after a sprint update. All previously written tests fail until updated.
Tip: Use contract testing tools or automation frameworks that detect API changes early, such as Postman tests or Keploy that generate test cases automatically from traffic.
- Complex Data Dependencies
Many APIs depend on a specific state or sequence of actions to work properly. You can’t test DELETE /user/123 unless user/123 exists — and was created using a valid POST /user request.
This leads to complications in test setup, teardown, and managing test data across different environments.
Example:
Testing a flight booking API requires chained calls — search → select seat → payment → confirmation — and a failure in any step blocks the rest.
Tip: Create modular tests that include setup and cleanup. Use mocking tools to isolate external dependencies.
- Authentication and Authorization Complexities
APIs today rely on various security protocols — OAuth 2.0, JWTs, API keys, and HMAC signatures. Simulating valid tokens and roles for different test cases can be extremely tricky and time-consuming.
Example:
To test GET /admin/settings, you need a valid admin JWT, which expires in 15 minutes and can only be generated through a multi-step login flow.
Tip: Automate token generation or use environment variables in tools like Postman. For automation, include reusable auth handlers.
- Asynchronous and Event-Driven APIs
Webhooks, message queues, and event-driven APIs are increasingly popular. But testing asynchronous APIs is challenging because you need to wait for and capture external responses that may not be immediate or guaranteed.
Example:
An API triggers a webhook after order delivery. Your test needs to poll or listen for that webhook and assert its payload.
Tip: Use polling or event simulation frameworks. Set appropriate timeouts and error handling logic in automated tests.
- Lack of a Testing Environment or Mock Servers
Many APIs require a backend or third-party service to be live and stable during testing. If the backend is still under development or third-party APIs are rate-limited or paid, this becomes a major blocker.
Example:
Testing weather data from an external API may fail if the service rate-limits you or is unavailable during testing.
Tip: Use mocking tools like WireMock, Mockoon, or Keploy to simulate real responses without hitting the actual APIs.
- Difficulty in Validating Dynamic Responses
Validating responses that contain dynamic or time-sensitive data — such as timestamps, IDs, or tokens — can lead to false negatives in tests.
Example:
A response returns a unique transactionId and createdAt timestamp. Rigid test scripts that expect fixed values will fail every time.
Tip: Use flexible assertions (e.g., regex or partial matches) and focus on data structure, not static values.
8. Lack of Proper Tooling and Automation
Many teams still rely on manual API testing, which is inefficient and prone to human error. Without automation and integration into CI/CD pipelines, it’s hard to ensure consistent and frequent API validation.
Tip: Integrate API testing into your development workflow using tools like:
- Postman (with Newman)
- Rest Assured / SuperTest
- Keploy (for automated test generation)
- Cypress for full-stack tests including APIs
Conclusion
API testing is not as simple as sending a few requests and checking status codes. It involves deep technical understanding, constant updates, smart data management, and the right tooling.
From managing test data and simulating authorization to dealing with asynchrony and documentation issues, each challenge adds complexity — but also highlights the need for robust, automated, and well-maintained API tests.
By addressing these difficulties of api testing head-on and leveraging modern tools and practices, your team can build reliable APIs that stand strong under pressure.
.Read more on https://keploy.io/blog/community/difficulties-of-api-testing