API testing guides — test REST and GraphQL APIs, write contract tests, and automate API validation.
API Testing
API documentation that lies is worse than no documentation. When a spec says an endpoint returns { "id": "string" } but the server actually returns { "id": 42 }, every consumer who read the docs gets a runtime surprise. Dredd is a tool specifically built to prevent this.
API Testing
The hardest bugs to find with manual testing are the ones you don't think to test. You write tests for the happy path, a few expected error cases, and maybe some edge cases you've burned by before. But the input space of a real API is
API Testing
Property-based testing for APIs works like this: instead of writing POST /users with {"name": "Alice"} and checking the response, you define what properties the API should always satisfy, and let the test tool generate hundreds of inputs automatically. Schemathesis does exactly this for REST APIs
API Testing
Manual API tests cover the happy path and a handful of error cases you thought to write down. Property-based testing covers the space you didn't think about — and that's exactly where real bugs live. Schemathesis is a Python-based tool that reads your OpenAPI (or
Testing Strategy
Schema-driven testing uses API specifications — OpenAPI, JSON Schema, AsyncAPI — as executable contracts. Instead of writing tests manually, you derive them from the spec. This catches structural bugs, breaking changes, and edge cases before they reach production, often without writing a single test by hand. Key Takeaways A schema is
Python
Behave and the Python requests library are a natural pairing for API testing. You write scenarios in plain Gherkin that non-developers can read, while step definitions handle the HTTP calls. This post walks through project setup, reusable context objects, authentication flows, and error-case testing — all with working code.
Security Testing
Web application security testing with Burp is intuitive when there's a browser to proxy.
Testing
Integration tests are slow, brittle, and expensive to maintain. You spin up multiple services, wire them together in a test environment, and hope that everything behaves the way it did last Tuesday. When a test fails, you spend twenty minutes figuring out whether the problem is in the consumer, the
Test Automation
A growing share of traffic hitting business websites isn't a person clicking around — it's an AI agent filling out a form, submitting a product to a directory, or calling an API on a user's behalf. These agents follow the same UI and API contracts
Robot Framework
Robot Framework isn't just for UI testing. With RequestsLibrary, it becomes a capable API testing tool — one that produces the same structured reports and follows the same keyword model as your UI tests. This matters for teams that want unified test output and want non-developers to be
API Testing
Spring Boot's testing support is excellent on its own, but pairing it with REST Assured gives you expressive, readable integration tests that cover the full HTTP layer — controllers, serialization, validation, error handling, and everything in between. This guide shows you how to wire the two together and build
API Testing
Field-by-field assertions work fine when an API has three fields. When your API returns a complex nested object with 30 fields, writing individual body("field", equalTo(...)) calls for each one is tedious, fragile, and easy to get wrong. JSON Schema validation solves this: define the expected