Software Testing Class

9 Common Errors Made During API Testing

API stands for Application programming interface. It is a generic piece of software utility which accepts input parameters and provide desired output based on the specific business logic. When we talk about API development then such process requires a strict testing in terms of security, business logic processing, valid input data parameters, data type, etc. If testing for any API is not conducted thoroughly then such API will be flawed with number of issues and those issues can lead to malfunctioning of partner application and even security breaches throughout their lifespan.

In order to conduct API testing thoroughly, we are going to discuss on frequently occurring 9 common errors during
API testing . Not only we are going discuss about these errors but also provide the simple solution that may help to improve the API testing methodologies, health, and test results.

Misbehaving Entries:

Often it is observed that API works fine when it is individually tested with set of required input parameters but it starts misbehaving and malfunctioning when integrated with partner. It is because the partner may be sending ‘NULL’ values for certain required fields which may be difficult to figure out during integration mode. It has simple solution that during testing, we should have the test cases to cover the behavior of API when it receives ‘NULL’ or errant entries as input parameter. API should send the response back to the partner with appropriate error message in which it can state that input data from partner application was incorrect and API is working smoothly.

Invalid Response:

API responses could be successful like HTTP 200 code or failure like 404 i.e. resource not found. Sometimes, the format returned from API is not digestible to the partner application as it may vary in number of fields. Solution to test is very simple, the number of fields in response should be clearly defined for both success as well as failure response messages and should tested consistently across all kind of API responses.

Caching API Response:

API acts as a black box that accepts input parameters and provide response against the desired business function triggered. Partner application has the choice to cache the output response from API for the same repeating set of input parameters. Now, if the output from API is changing frequently for same input parameters then the cached output result at partner application is stale and conveys incorrect information. It has a simple solution, though API is working as expected but partner application has to decide on what results they need to cache and what not. If the result is changing frequently from API as in case of live data, then caching should not be done but if any result like product image, description, etc. which is not expected to change very frequently can be cached at partner application.

Handling False Negative Response:

API when returning response by HTTP as 200 is considered as success but such response could also have NULL values which is the case of False Negatives. Though partner application is going to read such responses as success but do those NULL values in response make sense to them? This is where the actual test coverage is required against false negative response.

Team Communication Failure:

As API grows based on user experiences and business changes, the API maintenance becomes very important. This is where the best team communication is required. It should not happen that API changes were made and it has started impacting all partner applications. Any kind of change to API or partner application should be well communicated, implemented, integrated, and tested. Also, the version of standard interface API document should be updated from time to time in order to avoid any bad development practices from developer.

Non-standard Coding Approach:

API development team should agree on a particular standard approach in terms of input parameters and output response parameters and any deviation from such standard should straight lead to rejection of input by API or response by partner application. Sometimes developers accept blank or null as input or output partner which may cause problem in long run. The data type, mandatory or not, range, thresholds, etc. should be clearly defined and testing should test the API against such standards and any deviation from such standards should not be acceptable at all by any means.

Ensure Character Set:

API should specify about the accepted character set such as ASCII, Unicode, etc. for input and output parameters. This is to make sure that partner application is interacting with API for the agreed character set and any character received outside the agreed range such lead to straight rejection. Also, the language such as English, French, Spanish, etc. in response should be well agreed in advance. Our test cases should complete all such requirements for agreed character sets as well as languages.

API Compatibility With Partner Application:

APIs are built keeping in mind about the partner applications compatibility. Any release from API side or partner application side should be regression tested against all existing test cases on top of new functionality added to the API or partner application. In other words, all release for API or partner application should always meet the compatibility criteria.

Use Your Testing Skills:

API can have many hidden issues which could be actually unveiled through the testing skills possessed by an experienced testing team. Testers are advised to execute negative scenarios in order to catch defects which could not be caught through traditional testing practices. Testers can do monkey testing to broke the API which will provide a great room to the developer to code an efficient API which is very robust and smart.

Conclusion

In API testing, defects are inevitable for any API if it not well coded as well as tested. It the call for the tester to design efficient test cases, avoid common error as discussed in this article and leverage their testing skills in order to deliver an efficient well tested end product for production.


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