API are the building blocks that provide means of developing applications software or making applications talk to each other (or) to the web. And they are subroutines which work in certain predefined ways or follows certain protocols.

Need for API testing strategies?

API are building blocks which provide abstraction, to be just used as service by calling and at the end gives the solution. It is much like instant soup, where we mix water with the instant soup and boil, we end up with a hot bowl of soup. And here benchmark tests are done to maintain the quality of the soup. And same goes as of the API testing, but quality-control is done by the means of tests. Here the aim is to determine whether the API is up to the mark, and does its job, without losing its magic of speed, reliability, and security.

Some of the common tests performed on API’s and these tests are much like black-box testing, where the internal logic remains a mystery to the tester. And tests are focused on input and output values, and no considerations are given to the working logic. And the tests are as follows

  • Evaluating Return Value to that of input condition – The return value from the API’s are tested based on the input condition.
  • There are certain times, where it is important that the API should not return anything, which should be verified by the tester.
  • Verify if the API has internally chained to sub-event or other sub-API. And the API and its output should be verified.
  • There are certain scenarios where the API should trigger one or more sub events, API (or)both.
  • Verify if the API is updating any data structure.

GUI testing

Some of the API testing approaches are as follows:

  • This approach begins with the creation of test cases for the API And then testing with techniques for verifying functionality, such as analysis and equivalence classes.
  • Having two or more value-added parameters and verifying the API call.
  • The definition of the APIs scope and functionality should be defined
  • While testing APIs, input parameters should be defined with values inaccurate ranges.
  • Benchmarked value or standard metric values can be used to compare the currently yielded API test values.
  • API should be tested under load to determine the reliability and performance, like handling file under bottlenecked network scenarios.

Different API testing methods:

  • Unit testing and Functional testing.
  • Load testing for testing the performance under load.
  • Running test discovery based on API documentation which range from listing, creating and deleting.
  • Consistent range ratio for usability testing and reliability testing evaluation.
  • All type of authentication should be tested for security flaws, and equally the penetration testing should also be done to validate crack proof APIs.
  • Regularly automatic testing should be carried out to on each phase of API calls.
  • End to end Integration testing and Web UI testing.
  • API effectiveness and efficiency test based on API documentation.

Difference between API and Unit Testing

Screenshot (10)

Some of the Automation tools used in API testing:

  • NUnit for .NET
  • JUnit for Java
  • HP UFT
  • Soap UI

Common protocols used in web API are also tested and are given below:

  • HTTP
  • JMS
  • REST
  • SOAP
  • UDDI

The main challenges in API testing are:

  • Parameter Selection
  • Parameter Combination
  • Call sequencing

Bugs that occur in API are:

  • Missing or duplicate functionality
  • Fails to handle error conditions gracefully
  • Stress
  • Reliability
  • Security
  • Unused flags
  • Not implemented errors
  • Inconsistent error handling
  • Performance
  • Multi-threading issues
  • Improper errors

Proprietary tools commonly used for API testing are:

  • PostMa
  • SoapUI Pro
  • Alertsite API monitoring


API consists of a set of programming logic abstraction which represent the business logic layer. And if the strategies and policy enforcement with quality controls are not enforced then, it causes a serious problem in the terms of business, and improper utilization of infrastructure(Cloud/Server/Nodes).