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Schema Validation in API Testing | Why & How to Perform?

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Schema Validation in API Testing Why & How to Perform
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Schema validation in API testing emerges as a pivotal process for maintaining the integrity and functionality of APIs. This article delves into the what, why, and how of schema validation, providing insights for everyone from manual testers to C-level executives involved in software development. By implementing schema validation, developers and testers can detect and rectify discrepancies in API responses early in the development process, leading to more reliable and robust applications.

What is Schema in API?

A schema in API context refers to the structured layout or blueprint of data expected in API requests and responses. It’s akin to a contract between the API and its consumers detailing the data format, type, and constraints. This structure is essential for APIs to function correctly and consistently.

What is JSON Schema Validation in API Testing?

Schema validation in API testing is a crucial process where the structure of the JSON response from an API is checked against a predefined schema. This schema, often defined using JSON Schema, outlines the expected format, data types, and other constraints for the data returned by the API. By validating the API response against this schema, testers can ensure that the data conforms to the expected structure, essential for the seamless integration of different systems. This process helps identify any deviations or errors in the API response, ensuring the reliability and consistency of the API’s functionality.

Why Schema Validation in API Testing?

Schema validation in API testing is vital for ensuring data consistency and reliability. It acts as a first line of defense against data corruption and unexpected changes in the API’s output, safeguarding the integration of various systems that depend on this data. By confirming that the API responses adhere to a predefined structure and set of rules, schema validation helps catch errors early in the development cycle, reducing the risk of bugs and inconsistencies in production. This practice ultimately leads to more robust and stable software systems, enhancing the overall quality of the application.

JSON Schema Implementation with Testsigma

Implementing JSON Schema with Testsigma involves several steps. Including:

  1. Understand JSON Schema: Familiarize yourself with JSON Schema, a powerful tool for validating JSON data structure.
  2. Define JSON Schema: Create a JSON Schema definition for your API response. This will be a blueprint of the expected data format.
  3. Set Up Testsigma Environment: Ensure your Testsigma environment is ready for API testing.
  4. Create API Test: In Testsigma, create a new API test where you’ll validate the JSON response.
  5. Fetch API Response: Write a test case to send a request to your API and receive the response.
  6. Validate Response Against Schema: Use Testsigma’s capabilities to validate the received JSON response against your defined JSON Schema.
  7. Add Assertions: Add assertions in Testsigma to check if the response adheres to the JSON Schema.
  8. Run Tests: Execute your tests in Testsigma to see if the API responses are as expected.
  9. Analyze Results: Check the test results in Testsigma for any discrepancies or failures in schema validation.
  10. Refine and Iterate: Based on the results, refine your JSON Schema and test cases for better coverage and accuracy. 

For instance, if you’re testing an API that returns user data, your JSON Schema might define expected fields like name, email, and id. Your test in Testsigma would validate if every API response correctly follows this structure.



How to Validate Schema with an Automated Test?

Validating a schema with an automated test in Testsigma can be broken down into a series of straightforward steps. Here’s a concise guide:

  1. Define Your Schema: Define the schema your API response should adhere to. This schema is a structured template outlining the expected format of your JSON response.
JSON
Schema
  1. Create a New Test Case in Testsigma: In Testsigma, create a new test case for the specific API endpoint you want to validate 
  2. Configure the API Request: Set up the API request within Testsigma, specifying the endpoint, request method, and any necessary headers or parameters.

For example, I have a GET request: https://dummyjson.com/products/1 with the following response:

API Request
  1. Verify your JSON schema: Verify your JSON schema by clicking the verify response body button and setting the verification type to SCHEMA, as in the image below


Click on CREATE to save in the verification tab

  1. Apply Schema Validation: Utilize Testsigma’s capabilities to validate the received response against your predefined schema. This step ensures the response adheres to the expected format and data types.
Json Path
  1. Analyze Results: Examine the test results in Testsigma to identify any deviations from the schema.
verify product ID

How JSON Schema Helps Improve Your API Design and Documentation

JSON Schema significantly enhances API design and documentation by providing a clear and concise structure for API responses. It acts as a contract that dictates the data format, type, and structure, leading to more consistent and predictable APIs. This standardization facilitates easier integration and interoperability between different systems and streamlines the development process by setting clear expectations for both producers and consumers of the API. Furthermore, JSON Schema serves as a self-documenting mechanism, making it easier for developers to understand the API’s data model, improving collaboration, and speeding up the development lifecycle.

Conclusion

Schema validation is crucial in API testing as it enforces structure, consistency, and accuracy in API responses. This process not only ensures that the APIs meet their intended specifications but also significantly reduces the likelihood of errors in data exchange, thereby enhancing the reliability of the overall application. 

By integrating schema validation into API testing workflows, developers and testers can achieve more robust and dependable APIs, leading to better user experiences and more efficient development cycles.

Frequently Asked Questions

What is schema in API?

A schema in an API context refers to a predefined structure for the data an API should return. It specifies the format, type, and arrangement of data expected in the API response. This schema acts as a blueprint, helping to maintain consistency and clarity in the data exchanged between the API and its consumers, thus ensuring that the API behaves as expected.

How to validate API schema in Postman?

To validate the API schema in Postman, you need to write a test script in JavaScript that compares the API response against a predefined JSON schema. This is done using the pm.test function to create a test case, and then using pm.expect to assert that the API response adheres to the specified schema. Postman’s built-in support for JSON schema validation makes this process straightforward.

An image of a JSON schema validation in Postman

Json schema

How to create a schema for API?

Creating a schema for an API involves defining the structure, types, and constraints of the data expected in the API response. Typically, this is done using JSON or XML Schema languages, where you outline the required fields, data types, and rules like minimum/maximum values or specific formats. Tools like Swagger or OpenAPI can be used to assist in creating and visualizing the API schema in a more user-friendly format.

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