What Is API Automation Testing?
By Hamid Akhtar, Community Contributor - July 25, 2023
Automating API testing brings significant benefits, including the early detection of bugs, increased test case reusability, and elimination of human error. It also facilitates the development of API products faster and more efficiently, thereby saving time and resources in the long run.
What role does API test automation play?
API automation testing plays a crucial role in ensuring the robustness and reliability of software applications.
- APIs serve as the building blocks of software in this approach, and their quality directly impacts the application’s overall performance.
- API automation testing allows for efficient validation of these APIs, ensuring they function as expected and adhere to the required standards.
- Moreover, API automation testing becomes even more critical in an API-first development approach, where applications are built by linking several different APIs.
- It improves the quality assurance process and ensures the timely release of high-quality software.
Therefore, in an API-first world, API automation testing is not just a good-to-have but a necessity for maintaining software applications’ high quality and reliability.
APIs, or Application Programming Interfaces, are like the unsung heroes of our connected world. They’re the behind-the-scenes players that allow software applications to communicate with each other. When you use an app on your phone, APIs work hard in the background, fetching the data you see on your screen.
There are two main types of APIs that you should know about:
- RESTful APIs: These are the cool kids on the block. They’re easy to work with and use HTTP methods to perform tasks. When you’re using a RESTful API, you’re having a conversation with a server. You ask for data, and the server responds with your requested data. It’s like asking a librarian for a book, and the librarian brings you the book you requested.
- SOAP APIs: These are the old-school types. They’re protocol-based and use XML for sending and receiving messages. They’re highly secure and provide robust error checking. If RESTful APIs are like librarians, SOAP APIs are like bank vaults. They’re secure, reliable, and more complex to work with.
What is API Automation Testing?
API test automation, or “api automation testing”, is like a health check for your software. It’s all about ensuring the APIs, your software’s building blocks, are working as they should.
- The main objectives are to ensure the APIs function correctly, validate their features, and improve the efficiency of the testing process. It’s like having a mechanic who checks all car parts to ensure they’re working properly.
- The benefits of API test automation are numerous. It provides faster feedback, reduces manual effort, increases test coverage, and can be integrated into your CI/CD pipeline. Plus, it can lead to significant cost savings in the long run. So, it’s about finding problems and making the development process more efficient and cost-effective.
Here’s a simple Python script using the requests library to send a GET request to an API:
response = requests.get(‘https://api.example.com/users’)
This script sends a GET request to the /users endpoint of the API and prints the response data.
API Testing Types
This is the most basic type of API testing, which involves checking whether the API functions as expected.
For example, if you have an API endpoint that retrieves user information based on a user ID, a functional test would involve sending a request with a valid user ID and checking if the response correctly includes the expected user information.
response = api.get(‘/users/1’)
assert response.status_code == 200
assert response.json()[‘id’] == 1
2. Load Testing
This type of testing checks how the API handles many requests. For instance, you might send hundreds or thousands of requests to the API quickly and monitor its performance and response times.
from locust import HttpUser, task, between
wait_time = between(1, 2.5)
3. Security Testing
Security testing involves checking the API’s security mechanisms, such as authentication and authorization. For example, you can access protected endpoints without providing valid authentication credentials and verify that the API correctly denies access.
response = api.get(‘/protected’)
assert response.status_code == 401 # Unauthorized
This testing verifies that the API works correctly when integrated with other services. For instance, if our API relies on a database, you might check that it can retrieve and store data correctly.
5. Reliability Testing
This testing ensures that the API consistently performs under the proposed conditions. For example, you might run a series of functional tests in a loop for an extended period to check the API’s reliability.
This testing checks the API’s response time and speed. It is similar to load testing but focuses on how quickly the API can process requests and return responses.
7. Negative Testing
This testing involves providing invalid or unexpected input to the API to see how it handles such situations. For example, you might send a request with an invalid user ID and check that the API correctly returns an error.
response = api.get(‘/users/999999’)
assert response.status_code == 404 # Not Found
This testing checks whether the API works as expected across different platforms, devices, and environments. For example, you might run our tests on different operating systems or using different versions of the programming language to ensure compatibility.
Common Challenges in API Automation Testing
API automation testing, while beneficial, does come with its own set of common challenges listed below:
- Use Case Propagation: Traditional UI testing is limited to testing the functionality of the overall application. However, API testing follows a different approach. Being the central hub of logic and the gateway to data for interfacing applications, use cases are near-infinite in API testing. This can lead to the number of required tests rapidly exceeding the competencies of the technical staff responsible for test case design.
- Access to Connected Systems: APIs pull data from multiple APIs and back-end systems, resulting in a complex architecture. It’s often impossible to have access to every environment on this tree. The emulation of inaccessible resources is key to avoiding testing bottlenecks.
- Synchronous and Asynchronous Methods: Modern applications are intricate, and one API can link several microservices and other APIs. Accordingly, a single call on an API can prompt numerous serial and parallel activities. The intricacies of an API can thus grow exponentially as it is combined with other API calls.
- Tracking API Inventory: The numerous APIs involved in an application act independently of each other. While performing API testing, it gets challenging for testers to keep up with rapid updates and how those updates impact the overall application.
- Knowledge of the Business Application Logic: APIs usually have several rules and guidelines dictating their usage. The lack of knowledge and understanding of these business logic and rules among API testers lead to ambiguity regarding the test objective.
- Complex Protocols: APIs interact through defined rules known as contracts or protocols. Often these protocols are complicated and might hinder the proper integration and testing of the communication between components.
- Impact of Change: Whenever there is a new version of an API, it will likely cause the entire application to go haywire. As there are multiple dependent components, implementing a change is often highly risky and unpredictable regarding its effects.
- Test Data Management: The numerous APIs with various parameters require enormous amounts of data to test them effectively. Maintaining such a large amount of data and ensuring that the data is reusable is a big challenge for API testers.
API Functionalities to be tested
- Endpoint Responses: Each API endpoint should return the expected response for a given request. This includes checking the status code, the data returned, and the response format. Bugs in this area could include incorrect input parameters, output format, response code, and data type.
- Error Handling: APIs should properly handle errors and return appropriate error messages. This includes testing with invalid inputs or when a resource is not available. Bugs in this area could include incorrect error messages or missing error codes.
- Security: APIs should be secure and protect against unauthorized access. This includes testing authentication mechanisms and checking for weak encryption, SQL injection, or insufficient authentication mechanisms. Bugs in this area could include unauthorized access to sensitive data or functions.
- Performance: APIs should respond quickly and handle a high volume of requests. This includes load testing to ensure the API can handle many concurrent users and requests. Bugs in this area could include slow response times or system crashes under high load.
- Functionality: APIs should fulfill all the requirements and functions they are designed for. This includes testing all the API endpoints and methods. Bugs in this area could include missing functionality or duplicate functionality.
- Compatibility: APIs should work well with the platforms, frameworks, or languages they are designed to interact with. This includes testing the API in different environments and configurations. Bugs in this area could include integration issues or incompatibility with certain platforms or languages.
- Reliability: APIs should be available at all times and provide consistent results. This includes testing for downtime and latency issues. Bugs in this area could include frequent downtime or inconsistent results.
- Documentation: The documentation for APIs should be clear, concise, and easy to understand. Bugs in this area could include incomplete or confusing documentation.
Read More: Top Python REST API Frameworks in 2023
How to perform API Test Automation?
- Select a Tool: Many tools are available for API testing like Postman, Rest Assured, and TestProject. These API testing tools help you to send requests to your API and validate the responses.
- Understand the API: Go through the API documentation to understand its functionalities. This includes knowing the endpoints, request methods (GET, POST, PUT, DELETE, etc.), request parameters, and expected responses.
- Create Test Cases: Based on the API documentation, create test cases that cover all possible scenarios. This includes positive testing (valid inputs), negative testing (invalid inputs), and edge case testing.
- Execute Test Cases: Use the selected tool to execute the test cases. This involves sending requests to the API endpoints and validating the responses against the expected results.
- Integrate with CI/CD Pipeline: Integrate your API tests with your CI/CD pipeline. This ensures that your tests are executed automatically whenever changes are made to the API.
- Analyze Test Results: After executing the tests, analyze the results to identify any failures or issues. If any issues are found, report them to the development team for resolution.
Types of Output of an API
- JSON: A lightweight data-interchange format, easy for humans and machines to use. Common in APIs due to its compatibility with many languages.
- XML: A markup language for encoding documents in a human-readable and machine-readable format. Used for data interchange on the web.
- HTML: The standard markup language for web documents. Some APIs return data in HTML, especially if they interact with web pages.
- Text: Some APIs return plain text data. Less common as it lacks the structure of JSON or XML, but useful for simple responses.
- Binary: Used when an API returns non-textual data, like an image or a file. Often encoded in base64 format for correct transmission.
- Images: APIs dealing with multimedia content may return images in formats like JPEG, GIF, and PNG.
Test Cases for API Testing
- Validate the API keys: API keys are often used for authentication. A test case should be created to validate that the API keys are within the expected range or length. This test case should also ensure that the keys are correctly responding to call requests, especially if JSON or XML APIs are being used.
- XML and JSON Schema Validation: XML and JSON are common formats for sending and receiving data via APIs. A test case should be created to validate the XML and JSON schema. This involves checking that the data is correctly structured and that the necessary fields are present. The parse response should also be verified to ensure that the server is correctly parsing out portions of the response data.
- Check JSON Schema Validation, Field Type, and Mandatory Fields: This involves checking that the JSON schema is correctly validated, that the field types are as expected, and that all mandatory fields are present in the response. This is important to ensure that the API is returning the correct data.
- Verify HTTP Response and Code Status: HTTP response codes are used to indicate the status of the request. A test case should be created to verify that the correct HTTP response code is returned for each API request. This can help identify issues such as server errors (500), not found errors (404), or unauthorized errors (401).
- Test Request Chaining: APIs often involve multiple requests that depend on each other. A test case should be created to test request chaining, which involves making multiple API calls in a sequence and verifying that they all work together as expected.
- Validate CRUD Operations: CRUD stands for Create, Read, Update, and Delete – the four basic operations of persistent storage. Test cases should be created to validate that all four operations work correctly for the API.
- Error Handling: APIs should be able to handle errors gracefully. A test case should be created to send invalid or blank input to the API and check how it responds. The API should return an appropriate error message and should not crash or stop functioning.
- Security Testing: Security is a crucial aspect of API testing. Test cases should be created to check the encryption of your API for vulnerabilities. This could involve trying to intercept the data using a packet analyzer, like Wireshark, to check whether sensitive data like API authentication tokens or API requests and responses can be viewed.
As you wrap up this deep dive into API Automation Testing, let’s remember that this isn’t just about code—it’s about shaping the digital world. APIs are the building blocks of today’s tech giants like Google, Amazon, and Facebook. They are the invisible threads that connect systems, applications, and services.
API Automation Testing ensures these threads are strong, reliable, and efficient. It’s about making sure that when you book a ride on Uber, the app communicates seamlessly with Google Maps to get the driver to your location. It’s about ensuring that when you order a book on Amazon, the system communicates flawlessly with the inventory, the payment gateway, and the delivery service.
So, as you step back into your role as a developer or tester, remember the importance of what you do. Every test you run, every bug you catch, every improvement you make, contributes to the smooth functioning of the digital world you all rely on.
In the world of API Automation Testing, it’s crucial to have a reliable and efficient platform to ensure your APIs are functioning as expected. That’s where BrowserStack comes into play.
- BrowserStack is a cloud-based web and mobile testing platform that provides developers with the ability to test their websites and mobile applications across on-demand browsers, operating systems, and real mobile devices.
- Moreover, BrowserStack’s Local Testing feature allows secure testing of private and internal servers, providing an extra layer of security for your API testing.
- In addition, BrowserStack’s Integrations with popular tools like Jira, Slack, and GitHub make it easier for teams to collaborate and stay updated on the testing process.
With BrowserStack, you can ensure your APIs are robust, reliable, and ready for the real world.
1. Which API is used in automation testing?
Various APIs like RESTful, SOAP, and GraphQL are used, with tools like Postman and SoapUI.
2. Is API automation testing easy?
It’s straightforward with the right knowledge and tools, but requires understanding of APIs.
3. Is API testing part of automation testing?
Yes, it’s crucial for testing functionality, reliability, performance, and security at service and integration levels.
4. Which language is used in API testing?