APIs (Application Programming Interfaces) simplify application development by enabling your software to communicate with other tools.
However, the integration of this middleware is prone to errors and needs to be checked regularly via API tests, a crucial step not only in the development process, but also at regular intervals after production release.
In this guide, we explore every essential aspect of API testing so that you can approach it with a comprehensive understanding of its benefits, the API testing strategies available, and best practices.
API testing consists of analyzing an application program interface (API) to check that it meets expectations in terms of functionality, security, performance and reliability.
Tests are carried out either directly on the API, or as part of integration tests.
They focus on business logic analysis, application security and data response.
Typically, API tests are carried out by sending requests to one or more API endpoints and comparing the responses with the expected results.
Different types of tests can be performed to ensure that an API is working properly:
This test analyzes API projects according to three distinct sets of criteria:
Functional tests analyze specific functions within the code base to ensure that the API works within the expected parameters and can handle errors when results are outside the designated parameters.
This test is used to see how many calls an API can handle.
It is often carried out after the completion of a specific unit or code base to determine whether the theoretical solution can also function as a practical solution when subjected to a given load.
This test guarantees that the API can produce consistent results and that the connection between platforms is reliable.
This test validates the encryption methods used by the API and the access control design. Security tests include validation of authorization controls for resource access and user rights management.
Based on security tests, this test consists of attacking the API with limited knowledge of it.
This enables testers to analyze the attack vector from an outside perspective. Attacks used in penetration testing can target specific elements of the API, or the API in its entirety.
This test forcibly introduces huge amounts of random data into the system, enabling the creation of negative behavior, such as a forced crash or overflow.
API testing ensures that connections between platforms are reliable, secure and scalable.
Strong API connections are strongly correlated with a smooth user journey, ranking alongside regression testing and end-to-end UX testing as one of the most effective tools for improving customer satisfaction.
The APIs most likely to have an impact on the customer experience, known as public APIs, are also experiencing the fastest growth.
Given the growing importance of public APIs, it's highly likely that any organization within the multi-billion dollar API economy will rely on public APIs to deliver an optimized customer experience.
When API testing is integrated into development pipelines as part of continuous testing strategies, quality teams can quickly detect problems before they affect users.
Quality engineers can create comprehensive, customized UI and end-to-end (E2E) tests that take into account the true customer journey.
API monitoring in production allows developers to access the application without a user interface, helping the tester to identify errors earlier in the development cycle rather than waiting for them to become bigger problems.
API testing is important to ensure that your API performs as expected in the face of a wide variety of expected and unexpected requests.
This process is designed to test not only the API's functionality, but also its reliability, performance and security.
Broader test coverage makes it easier to identify any bugs at the unit, database and server level.
API testing uses extreme conditions and inputs when analyzing applications. This removes vulnerabilities and protects the application from malicious code.
API test automation is the process of using an API test tool to automatically execute API tests at certain times or frequencies, or in CI/CD pipelines.
QA teams that automate their API testing are able to :
There are several test libraries specifically designed for API test automation. Among the most popular are "Postman" and "RestAssured" for REST APIs, and "SOAPUI" for APIs based on the SOAP protocol.
These libraries offer powerful features for efficiently creating, executing and analyzing API test cases.
Some teams prefer to write their automated tests using programming languages such as Python, Java or JavaScript.
This approach allows greater flexibility and customization of tests to specific project requirements. It also integrates easily with existing test frameworks.
Some platforms offer an all-in-one approach to test automation, combining both UX and API testing.
These tools provide an intuitive interface for creating, managing and executing all types of tests from a single platform, simplifying the overall testing process.
Before embarking on full automation, it is important to manually validate test cases to ensure that they are correct and produce the expected results.
Teams should automate only simple, straightforward tests and implement "Retry" logic to confirm failures.
Tests that include complex logic can produce false positives, which can lead to teams wasting time solving non-existent problems.
False positives can also lead to test fatigue, where legitimate failures are ignored.
One way of ensuring that test suites run as quickly as possible is to run them in parallel.
This approach enables teams to run tests on different browsers, devices and operating systems without introducing bottlenecks.
To take full advantage of API test automation, teams need to choose a test tool that is compatible with their existing workflows.
For example, it must integrate with the chosen CI/CD pipeline and offer failure notifications via e-mail or Slack.
Some teams may also want a test solution that enables them to transmit test data to monitoring or incident response tools, such as Datadog, New Relic or Opsgenie.
By storing test data in separate files or databases, test cases can be easily reused, and data updates are made without modifying automation scripts.
First, identify the target consumer of the API, its features and functions, and the application's workflow as well as the aspects, priorities, and issues you are testing.
You must establish :
Your QA team will find value in your tests if they help them deliver fast, easy-to-understand results.
When it comes to an automated APItesting tool, the following aspects are essential:
Now that you know what you need to test, and have an automated API test tool to run your tests, all that's left to do is specify your test cases and execute them.
From there, you can compare expected results with actual results by analyzing :
Testers need to watch out for failures or unexpected inputs. Response time must be within a defined limit that teams find acceptable, and the API must be secured against potential attacks.
API tests must also be built to ensure that :
By using API test automation best practices, companies can improve their testing process and deliver high-quality products, reduce bug-related costs and protect their brand image.
The no-code SaaS solution Mr Suricate solution covers a wide range of automated tests in order to control your testing and provide your users with the best possible experience.
Take control of your applications and detect bugs in real time on your websites, applications and APIs by reproducing your user journeys at regular intervals.