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API Testing in 2024: 3 Benefits & 8 Different Types

APIs have taken over the software world, as almost 90% of developers use API in some form. However, 40% of API users have reported API breakages. Given the high importance of APIs and their adaptation, ensuring correct and consistent API functionality has become crucial.

In this article, we will explore different types of API testing that help firms to detect errors in APIs and take action accordingly.

What is API testing?

API testing is a black box test evaluating APIs either independently or as part of the integration testing to ensure that an API meets the:

  • Functionality
  • Security 
  • Performance
  • Reliability 

Many applications use a 3-tier architecture model (See Figure 1). These tiers are:

  1. Presentation tier: The user interface. Users communicate with the application in this tier.
  2. Application tier (logic tier): Data is processed and modified in this tier based on the rules that have been defined. APIs are used to communicate with the data tier, and API testing is conducted in this tier.
  3. Data tier: All information processed by the application is stored in this tier.

Figure 1. 3-tier architecture model

3-tier architecture model
Source: AWS

3 Benefits of API testing

1- Faster & earlier development

API components are usually developed before UI, so tests can be done independently of GUI. Thus, testing can be done in the early phase of the project to detect errors and bugs. The GUI independence of API testing makes it faster compared to GUI testing as it will not require loading interface elements and website rendering. According to QASOURCE, 3000 API tests may be completed in about an hour. However, a company needs more than a day to run the same number of GUI tests (In parallel execution). 

Recommendation: It is recommended to use API testing instead of GUI testing for test automation as it is more appropriate with the current short release cycle, fast feedback loops of apps, and increasing system complexity.

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CAST is a low-code test automation tool by Testifi. It offers API, web, mobile, and desktop testing with static code analysis. Major well-known companies such as BMW, Amazon, and Vodafone use Testifi services. 

2- Language independence

Any language can be utilized for automating testing because data and information are exchanged using JSON or XML format. These formats are easily readable in different programming languages using libraries. 

3- Comprehensive coverage

API testing covers a broad scope. API tests are designed to ensure all system components function as intended. They cover areas such as :

  • Functionality
  • UI
  • Security

The rest of the article will continue with 8 types of API testing and our recommendations for executives to improve the API testing process.

1- Functional testing

It ensures that the API output generated by specific functions matches the expected output in different scenarios. For example, an API function should return the price of a mutual fund based on the fund code or the fund name. Let’s assume that the fund code is “FXAIX”, and its name is “Fidelity 500 Index Fund”. If the user types “fxaix” or “FIDELITY 500 INDEX FUND” will the function work as intended? If the result is an error or does not match the correct output, then the necessary measures must be taken to fix it.

Recommendation

  • Define different scenarios for each function.
  • Automate testing for functions that you test repeatedly.
  • Test periodically.

2- Fuzz Testing

It is a security test where a large amount of miscellaneous data is input into the system to make it crash or behave negatively. This is a stress test of the API for the worst-case scenario. 

Recommendation

  • Follow the fuzz testing phases.
  • Choose between dumb fuzz & smart fuzz strategy.
  • Choose or combine behavioral and coverage-guided fuzz testing types.
  • Choose the right fuzz testing tools.

3- Load testing

API load testing test checks if the theoretical solutions work under different amounts of traffic. It is tested against regular (baseline) and theoretical maximum traffic. 

Recommendation

  • Begin testing your API from the lowest level functions and build it up from there.
  • Build one test for each API.
  • Define performance measures and goals for your API.

4- Penetration testing

The API is attacked by someone with limited knowledge of the API to break the whole API, disrupt specific processes or get access to information. API penetration testing will discover potential security flaws.

Recommendation

  • Choose between different penetration testing methodologies based on your objective.
  • Find suitable penetration testers, ideally someone or a group specializing in API penetration testing.
  • Prepare for penetration testing by taking actions such as cleaning the test environment, granting authorization if needed, and setting up monitoring solutions for the penetration test.
  • Prioritize test results based on the vulnerability’s importance & severity. 

5- Runtime & error detection testing

This test focuses on the actual running of the API, while other tests focus on the results of the API. This test focuses on the following areas :

  • Monitoring
  • Execution errors
  • Resource leaks
  • Error detection 

Recommendation: There are automation tools to conduct this test.

6- Security Testing 

Security is one of the most critical aspects of APIs, as security vulnerabilities can lead to the loss of data, which can lead to the loss of customers and revenue. In 2020, 95% of APIs suffered at least one security incident (See Figure 2).

Figure 2. API security problems

Top security problems of APIs
Source: SALT

Security tests ensure that the API is secure from external threats. It includes testing for :

  • Users right management
  • Validation of encryption methodologies
  • Structure of access control
  • Authorization validation
  • Validation of encryption methodologies

Recommendation

  • Invest and pay more attention to API security measures; only 40% of APIs in the production stage have an intermediate or advanced level API security strategy.
  • Analyze 3rd party dependency for vulnerabilities.
  • Use data encryption to increase API security.
  • Set multi-factor authentication requirements for making API calls.

7- Validation testing

It is among the final tests in the development process. It looks to confirm if the developed API is the correct API to satisfy user needs and requirements. This test checks :

  • Product
  • Behavior
  • Efficiency 

Recommendation

  • Define the scope and goals of the validation project.
  • Define the requirements and features that the API must have.
  • Make necessary changes according to validation testing results.

8- UI testing

It tests the user interface of the API and its essential parts of it. It does not focus on testing the API itself. This test provides a general overview of the following for the front and backend :

  • Health
  • Usability
  • Efficiency

Recommendation: APIs are considered to be used by machines which is why not much attention is given to their design and looks. Ronnie Mitra, the Lead Designer at the API Academy, said, “in the API space, we build something on a machine for a machine to use, and this is wrong because there are people on the other side of API clients.”. UX honeycomb (See Figure 3) framework can be used to make well-designed APIs.

Figure 3. UX honeycomb 

User experience honeycomb framework
Source: Semantic Studios

Further Reading

For more on AI and automation

If you are ready to deploy automated testing, check out our data-driven, transparent list of top vendors that can enable testing automation.

If you are interested in investing in AI solutions, check out our data-driven list of Data Science / ML / AI platforms.

And if you need help choosing the best tool for your business, reach out to us for guidance:

Find the Right Vendors
Access Cem's 2 decades of B2B tech experience as a tech consultant, enterprise leader, startup entrepreneur & industry analyst. Leverage insights informing top Fortune 500 every month.
Cem Dilmegani
Principal Analyst
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Cem Dilmegani
Principal Analyst

Cem has been the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 60% of Fortune 500 every month.

Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.

Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised businesses on their enterprise software, automation, cloud, AI / ML and other technology related decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.

He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.

Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.

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