The first new HTTP method since PATCH has officially arrived. While most discussions focus on how to implement QUERY, there's another question every API engineer should be asking: How do you test it?
For over two decades, API developers have relied on a familiar set of HTTP methods—GET, POST, PUT, PATCH, DELETE, and a few others. Most API testing tools have been built around these semantics, assuming that a request is either safe without a body (GET) or has a body but may change server state (POST).
That assumption has now changed.
In June 2026, the QUERY HTTP method was standardized in RFC 10008, becoming the first new standard HTTP method since PATCH in 2010. QUERY combines characteristics that previously required trade-offs: it accepts a request body like POST while remaining safe and idempotent like GET.
For API consumers, this means cleaner designs for complex read operations.
For API testers, it introduces an entirely new category of behaviors that need validation.
If you're new to HTTP semantics or want a refresher on how GET, POST, PUT, PATCH, DELETE, and the new QUERY method differ, our HTTP methods learning hub provides a practical overview before diving into automation.
The good news? As soon as the specification became available, we added support for testing QUERY requests in Shift-Left API, allowing teams to generate, execute, and validate QUERY endpoints just like any other HTTP method.
So, what actually changes from an API automation perspective?
Understanding QUERY from a Testing Perspective
Unlike GET requests, QUERY allows clients to send complex filters and search criteria inside the request body.
For example:
QUERY /orders
Content-Type: application/json
{
"status": "completed",
"customerType": "premium",
"dateRange": {
"from": "2026-01-01",
"to": "2026-06-30"
},
"sort": {
"field": "createdAt",
"direction": "desc"
}
}
Functionally, this behaves much like a GET request.
It retrieves information.
It doesn't modify server state.
It can be cached.
It can safely be replayed.
Those characteristics immediately influence how automated tests should be designed.
1. Idempotency Becomes a First-Class Test
One of the defining characteristics of QUERY is idempotency.
Sending exactly the same request multiple times should always produce the same outcome, assuming the underlying data hasn't changed.
Your automated tests shouldn't stop after verifying a successful response.
Instead, they should intentionally replay the same request multiple times.
A good test verifies:
- Response status remains identical.
- Response schema remains unchanged.
- Returned data is consistent.
- No new resources are created.
- Audit logs don't record duplicate business events.
Many teams already perform similar validations for GET requests.
QUERY deserves the same treatment.
2. Request Body Validation Gets Much Richer
Traditional GET requests are constrained by URL length and query parameter syntax.
QUERY removes those limitations.
That means APIs can now receive:
- Nested objects
- Arrays
- Complex filters
- JSONPath expressions
- Large search payloads
With that flexibility comes additional testing responsibility.
Automation should validate scenarios such as:
- Missing required fields
- Invalid filter operators
- Unexpected data types
- Oversized payloads
- Empty request bodies
- Unknown properties
The richer the request body becomes, the more valuable automated validation becomes.
3. Contract Testing Becomes Even More Important
Many QUERY endpoints will be defined through OpenAPI specifications.
That creates an excellent opportunity for contract-driven testing.
Instead of manually writing assertions for every combination, test generators can use the specification to validate:
- Required properties
- Optional fields
- Enumerations
- Data types
- Response schemas
- Status codes
This dramatically reduces manual effort while ensuring that implementations remain aligned with documented contracts.
As QUERY adoption grows, contract testing is likely to become the preferred way to validate these endpoints.
4. Cache Behaviour Should Be Tested Explicitly
One of QUERY's biggest advantages is cacheability.
Unlike POST, intermediaries can safely cache responses.
Testing should verify more than functional correctness.
It should also confirm that caching behaves as expected.
Typical assertions include:
- Cache-Control headers
- ETags
- Last-Modified values
- Conditional requests
- Cache hit consistency
- Response freshness
Without these checks, applications may lose one of QUERY's primary performance benefits.
5. Replay and Retry Testing
Network failures happen.
One reason QUERY was introduced is that clients can safely replay requests without worrying about unintended side effects.
Your automation should simulate scenarios such as:
- Timeout before response
- Connection interruption
- Client retry
- Gateway retry
Every replay should return equivalent results without modifying server state.
Unlike POST, retrying QUERY requests should never introduce duplicates.
Testing this behavior is straightforward and provides significant confidence in production resilience.
How We're Testing QUERY in Shift-Left API
Supporting a new HTTP method isn't simply about allowing another verb in the request editor.
The real value comes from understanding its semantics.
Within Shift-Left API, QUERY endpoints can be tested using the same AI-assisted workflow as existing REST APIs.
Depending on your OpenAPI specification or captured API traffic, the platform can automatically generate scenarios covering:
- Valid QUERY requests
- Invalid payload validation
- Required versus optional fields
- Schema assertions
- Authentication
- Authorization
- Boundary values
- Negative testing
- Response consistency across repeated executions
Because QUERY combines characteristics of both GET and POST, having these scenarios generated automatically helps teams avoid subtle testing gaps that often appear when writing tests manually.
If you'd like to see the QUERY method available to test in Shift-Left API, along with examples of other HTTP methods and their testing strategies, we've documented everything in our HTTP methods guide.
Challenges to Expect During Adoption
Although RFC 10008 has standardized QUERY, ecosystem support is still in its early stages.
Developers should expect varying levels of support across:
- API gateways
- Reverse proxies
- HTTP client libraries
- Browsers
- Load balancers
- Testing frameworks
Some tools may initially reject QUERY requests.
Others may simply treat them as POST requests without understanding their safe and idempotent semantics.
Testing during this transition period becomes especially valuable because implementations are likely to evolve rapidly.
Building Future-Proof Test Suites
Rather than hardcoding assumptions about HTTP methods, modern API test suites should become semantic-aware.
Instead of asking:
"Is this a POST request?"
Automation should ask:
- Is this request safe?
- Is it idempotent?
- Should retries be allowed?
- Should caching be validated?
- Should server state remain unchanged?
Those questions remain valid regardless of future HTTP methods.
Designing test suites around behavior instead of individual verbs makes them much easier to maintain as standards evolve.
Looking Ahead
QUERY represents an interesting evolution of HTTP rather than a replacement for GET or POST.
GET remains ideal for simple retrieval.
POST continues to handle operations that modify server state.
QUERY fills the long-standing gap where clients need rich request bodies while preserving safe, repeatable semantics.
Adoption will take time.
Servers, frameworks, proxies, SDKs, and testing tools all need to implement support before QUERY becomes commonplace.
However, understanding its testing implications today will make future migrations significantly smoother.
Since support for QUERY is still emerging across frameworks and tooling, it's a good opportunity to validate how your APIs behave before adopting it in production. You can try Shift-Left API for free and generate automated tests for modern REST APIs—including support for evolving HTTP standards.
Final Thoughts
The introduction of QUERY isn't simply another HTTP verb for developers to memorize.
It changes how API consumers express complex read operations and how automation frameworks validate them.
Testing QUERY requires more than checking response codes.
It requires validating idempotency, replay behavior, request-body handling, contract compliance, caching semantics, and security.
As support for QUERY expands across the ecosystem, these validations will become part of everyday API automation.
The earlier teams begin incorporating them into their testing strategy, the easier adoption will be when QUERY becomes widely supported across production environments.
Top comments (1)
Wow, excellent post! Good to learn about QUERY !