Three reasons to start improving your API test automation skills

Modern applications and software development methods have changed the requirements for testers and the skills they need to possess to add real value to their clients and projects. One of these emerging and sought after skills is the ability to design and execute automated tests for APIs. In this post, I will give you three reasons why it might be useful for you to start improving your API test automation skills.

API word cloud

APIs are everywhere
The first reason why you should invest in your API test automation skills is a simple question of demand and supply: APIs are becoming ever more present in current IT solutions. From mobile applications to the Internet of Things, many modern systems and applications expose their data, their business logic or both through APIs. Whether you’re building an application that uses APIs to expose data or logic to the outside world, or you’re on the other side as an API consumer, you need to be able to perform tests on APIs. Otherwise, how are you going to ensure that an API and its integration with the outside world function as expected?

Oh, and if you’re testing an application that consumes a third-party API, please don’t fall into the trap of assuming that this API you’re using works perfectly as designed, or that integration with your own application will be seamless. Can anyone really assure you that that business-critical third party API you’re relying on has been tested for your specific situation and requirements? Thought not. Make sure it does and do some proper testing on it!

API test automation hits the sweet spot between speed and coverage
The second reason why API test automation can be very useful is that automated checks on the API level hit the sweet spot between speed of execution and coverage of application features. Compared to the two other types of automated tests in the test automation pyramid, API-level tests tend to:

  • execute faster than user interface-driven tests. User interface-driven automated tests, such as those written in Selenium WebDriver, need to fire up a browser and render several web pages every time a test is executed. When your tests go through a lot of different pages, execution time skyrockets. API-level tests, on the other hand, have to wait for a server responding to HTTP calls only. The only client-side processing that needs to be done is parsing the response and performing validation checks, for example on specific elements in the response. This is a lot faster than sending (possibly many) HTTP requests to a web server to fetch all objects required for a web page and then waiting until your browser has finished rendering the page.
  • cover more business logic than unit tests. Yes, you should have unit tests. And they should cover as much of the internal workings of your application that make up the business logic. However, there’s only so much unit tests can do. For example, unit tests can check whether the salary of a given employee is calculated correctly in the back end. They cannot guarantee that the same salary is correctly sent out to the front end layer of your application (or to the IRS) upon request, though. For this, you will need to perform tests at a higher level in your application, and API tests are usually perfect for that.

Automated API tests tend to be more reliable
Apart from having the right mixture of speed of execution and coverage of functional aspects, API-level automated checks have another big advantage over user interface-driven automated tests: they’re usually far more reliable. User interface-driven tests constantly have to walk the wobbly rope of synchronization, ever changing (or ‘improving’) user interface designs, dynamic element identification methods, etc. API definitions and interfaces on the other hand are amongst the most stable parts of an application: they follow standardized specification formats (such as WSDL for SOAP or WADL, RAML or Swagger for REST) and once agreed upon, an API does not usually change all that much. This applies especially to outward-facing APIs. For example, Google can easily change its Gmail user interface without this impacting end users (apart from annoyance, maybe, but that’s a different story altogether), but sudden radical changes to its Gmail API would render a lot of third-party applications that have Gmail integration useless. Therefore, changes to an API will usually be a lot fewer and further between, resulting in less maintenance required for your API-level automated tests.

A sample API test in REST Assured

Further reading
I hope this blog post has given you some insight into why I think API test automation skills are a valuable asset for any tester with an interest in test automation. If you want to read more on API testing and test automation, I highly recommend the API Testing Dojo on the SoapUI website. Additionally, you can also check out my other posts on API testing here.

Using the TestNG ITestContext to create smarter REST Assured tests

In this post, I would like to demonstrate two different concepts that I think work very well together:

  • How to store and retrieve data objects using the TestNG ITestContext for better code maintainability
  • How to communicate with RESTful web services that use basic or OAuth2 authorization using REST Assured

Using the PayPal sandbox API as an example, I will show you how you can create readable and maintainable tests for secured APIs using TestNG and REST Assured.

The TestNG ITestContext
If you have a suffficiently large test suite, chances are high that you want to be able to share objects between individual tests to make your tests shorter and easier to maintain. For example, if you are calling a web service multiple times throughout your test suite and that web service requires an authentication token in order to be able to consume it, you might want to request and store that authentication token in the setup phase of your test suite, then retrieve and use it in all subsequent tests where this web service is invoked. This is exactly the scenario we’ll see in this blog post.

TestNG offers a means of storing and retrieving objects between tests through the ITestContext interface. This interface allows you to store (using the inherited setAttribute() method) and retrieve (using getAttribute()) objects. Since the ITestContext is created once and remains active for the duration of your test run, this is the perfect way to implement object sharing in your test suite. Making the ITestContext available in your test methods is easy: just pass it as a parameter to your test method (we’ll see an example further down).

REST Assured authentication options
As you might have read in one of my previous blog posts, REST Assured is a Java library that allows you to write and execute readable tests for RESTful web services. Since we’re talking about secured APIs here, it’s good to know that REST Assured supports the following authentication mechanisms:

  • Basic
  • Digest
  • OAuth (version 1 and 2)
  • Form

In the examples in this post, we’ll take a closer look at both Basic authentication (for requesting an OAuth token) and OAuth2 authentication (for invoking secured web service operations) in REST Assured.

The PayPal sandbox API
To illustrate the concepts introduced above I chose to use the PayPal sandbox API. This is a sandbox version of the ‘live’ PayPal API that can be used to test applications that integrate with PayPal, as well as to goof around. It’s free to use for anybody that has an active PayPal account. You can find all documentation on the API here.

Retrieving an Oauth2 access token
The first step – after creating the necessary test accounts in the sandbox environment – is to construct a call in REST Assured that retrieves an OAuth2 authentication token from the PayPal web service. This request uses basic authentication and looks like this:

public void requestToken(ITestContext context) {

	String response =

The actual values for client_id and secret are specific to the PayPal sandbox account. Note that we have stored the JSON response as a string. This makes it easier to parse it, as we will see in a moment. The response to this request contains our OAuth2 authentication token:

Our OAuth2 access token

In order to store this token for use in our actual tests, we need to extract it from the response and store it in the TestNG ITestContext:

JsonPath jsonPath = new JsonPath(response);

String accessToken = jsonPath.getString("access_token");
context.setAttribute("accessToken", accessToken);

System.out.println("Access token: " + context.getAttribute("accessToken"));

The System.out.println output shows us we have successfully stored the OAuth2 access token in the ITestContext:

Access token has been stored in the ITestContext

Using the OAuth2 access token in your tests
Next, we want to use the previously stored token in subsequent API calls that require OAuth2 authentication. This is fairly straightforward: see for example this test that verifies that no payments have been made for the current test account:

public void checkNumberOfAssociatedPaymentsIsEqualToZero(ITestContext context) {

		body("count", equalTo(0));

Note the use of context.getAttribute() to retrieve the token from the ITestContext. This test passes, which not only tells us that no payments have yet been made by this account, but also that our authentication worked as expected (otherwise, we would have received an authentication error).

Download an example project
The Maven project containing all code from this post can be downloaded here.

API testing best practices

This is the second post in a three-part series on API testing. The first post, which can be found here, provided a brief introduction on APIs, API testing and its relevance to the testing world. This post will feature some best practices for everybody involved in API testing. The third and final post will contain some useful code example for those of you looking to build your own automated API testing framework.

As was mentioned in the first post in this mini-series, API test execution differs from user interface-based testing since APIs are designed for communication between systems or system components rather than between a system or system component and a human being. This introduces some challenges to testing APIs, which I will try to tackle here.

API communication
Whereas a lot of testing on the user interface level is still done by hand (and rightfully so), this is impossible for API testing; you need a tool to communicate with APIs. There are a lot of tools available on the market. Some of the best known tools that are specifically targeted towards API testing are:

I have extensive experience with SOAtest and limited experience with SoapUI and can vouch for their usefulness in API testing.

Structuring tests
An API usually consists of several methods or operations that can be tested individually as well as through the setup of test scenarios. These test scenarios are usually constructed by stringing together multiple API calls. I suggest a three step approach to testing any API:

  1. Perform syntax testing of individual methods or operations
  2. Perform functional testing of individual methods or operations
  3. Construct and execute test scenarios

Syntax testing
This type of testing is performed to check whether the method or operation accepts correct input and rejects incorrect input. For example, syntax testing determines whether:

  • Leaving mandatory fields empty results in an error
  • Optional fields are accepted as expected
  • Filling fields with incorrect data types (for example, putting a text value into an integer field) results in an error

Functional testing of individual operations or methods
This type of testing is performed to check whether the method or operations performs its intended action correctly. For example:

  • Is calculation X performed correctly when calling operation / method Y with parameters A, B and C?
  • Is data stored correctly for future use when calling a setter method?
  • Does calling a getter method retrieve the correct information?

Test scenarios
Finally, when individual methods or operations have been tested successfully, method calls can be strung together to emulate business processes, For example:
API test scenarios
You see that this approach is not unlike user interface-based testing, where you first test individual components for their correct behaviour before executing end-to-end test scenarios.

API virtualization
When testing systems of interconnected components, the availability of some of the components required for testing might be limited at the time of testing (or they might not be available at all). Reasons for limited availability of a component might be:

  • The component itself is not yet developed
  • The component features insufficient or otherwise unusable test data
  • The component is shared with other teams and therefore cannot be freely used

In any of these cases, virtualization of the API can be a valuable solution, enabling testing to continue as planned. Several levels of API virtualization exist:

  • Mocking – This is normally done for code objects using a framework such as Mockito
  • Stubbing – this is used to create a simple emulation of an API, mostly used for SOAP and REST web services
  • Virtualization – This is the most advanced technique of the three, enabling the simulation of behaviour of complex components, including back-end database connectivity and transport protocols other than HTTP

Non-functional testing
As with all software components, APIs can (and should!) be tested for characteristics other than functionality. Some of the most important nonfunctional API test types that should at least be considered are:

  • Security testing – is the API accessible to those who are allowed to use it and inaccessible to those without the correct permissions?
  • Performance – Especially for web services: are the response times acceptable, even under a high load?
  • Interoperability and connectivity – can be API be consumed in the agreed manner and does it connect to other components as expected?

Most of the high-end API testing tools offer solutions for execution of these (and many other types of) nonfunctional test types.

More useful API testing best practices can again be found in the API Testing Dojo.

Do you have any additional API testing best practices you would like to share with the world?