April 12, 2021

RESTful APIs and Testing

A software application product has various software layers such, as the user interface (UI), the business logic layer, middleware, and a database. Testing and certification primarily focuses on data integration tests on the Business layer. API testing is software testing that involves direct API testing, unlike other generic tests, which primarily involve the UI:

The preceding diagram depicts the typical layers of software, with API testing on the Business layer and the functional or UI testing on the Presentation layer.

Understanding API testing approaches

Agreeing on an approach for API testing when beginning API development is an essential API strategy. Let’s look at a few principles of API testing:

  • Clear definition of the scope and a good understanding of the functionality of the API
  • Common testing methodologies such as boundary analysis and equivalence classes are part of API test cases
  • Plan, define, and be ready with input parameters, zero, and sample data for the API
  • Determine and compare expected and actual results, and ensure that there are no differences

API testing types

In this section, we will review the various categories of API testing.

Unit tests

Tests that involve the validation of individual operations are unit tests. The following is one of the sample code snippets of a specific unit test case that validates getting all the investors from the API:

API validation tests

All software needs quick evaluation and to assert its purpose of creation. The validation tests need to be run for every function that is developed, at the end of the development process. Unlike unit tests, which focus on particular pieces or functions of the API, validation tests are a higher-level consideration, answering a set of questions so that the development can move on to the next phase.

A set of questions for validation tests could be the following:

  • A product-specific question, such as, is it the necessary function that is asked for?
  • A behavioral question, such as, is the developed function doing what is intended?
  • An efficiency-related question, such as, is the intended function using the necessary code, in an independent and optimized manner?

All of these questions, in essence, serve to validate the API in line with the agreed acceptance criteria and also to ensure its adherence to standards regarding the delivery of expected end goals and meeting user needs and requirements flawlessly.

Functional tests

Tests that involve specific functions of the APIs and their code base are functional tests. Validating the count of active users through the API, regression tests, and test case execution come under functional tests. The following screenshot demonstrates one such functional testing example of investor service validation for user authentication:

UI or end-to-end tests

Tests that involve and assert end-to-end scenarios, including GUI functions and API functions, which in most of the cases, validate every transaction of an application, are grouped under end-to-end tests.

Load testing

As we know, an increase in the number of end users should not affect the performance of the functions of an application. Load testing will uncover such issues and also validate the performance of an API in normal conditions too.

Runtime error detection tests

Tests that help monitor the application and detect problems such as race conditions, exceptions, and resource leaks belong in the runtime error tests category. The following points capture a brief about those factors.

Monitoring APIs

Tests for various implementation errors, handler failures, and other inherent concerns inside the API code base and ensures it does not have any holes that would lead to application insecurity.

Execution errors

Valid requests to the API return responses and asserting them for expected valid responses is common; however, asserting invalid requests for expected failures is also essential as part of an API testing strategy and those tests come under execution errors:

The preceding screenshot depicts an example of expecting an error when the user gives an ID that is not present on the system.

Resource leaks

Negative tests to validate the underlying API resource malfunctions by submitting invalid requests to the API. The resources, in this case, are memory, data, insecurities, timeout operations, and so on.

Error detection

Detect network communication failures. Authentication failures from giving the wrong credentials is an example error detection scenario. These are tests ensure the errors are captured and then resolved as well:

Here’s an authentication error, and the previous screenshot depicts this, as the code returns 401 (as it should); this is an example of an error detection test.

If you found this article interesting, you can explore Hands-On RESTful API Design Patterns and Best Practices to build effective RESTful APIs for enterprise with design patterns and REST framework’s out-of-the-box capabilities. Hands-On RESTful API Design Patterns and Best Practices helps you explore the concepts of service-oriented architecture (SOA), event-driven architecture (EDA), and resource-oriented architecture (ROA).

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