It would be unfair to underestimate the challenges of api testing.
Now-a-days when most of the business heavily rely on Restful APIs to connect application and facilitate seamless data exchange.
A provider service interacts with multiple consumers, each having different contracts and requirements. This presents numerous challenges in API testing that cannot be ignored if we aim to ensure software quality. API testing involves navigating through various obstacles and hurdles, with authentication and authorization complexities being among the common challenges. Additionally, non-functional aspects of API testing also pose their own set of challenges.
In this comprehensive blog discussing "Challenges faced in API Testing", we will delve into different types of obstacles and learn effective strategy to overcome them.
1. Authorization and Authentication challenges
Varied Authentication methods
Different authentication mechanisms, such as OAuth, API keys, or tokens. Each mechanism requires a distinct approach to access and interact with the API securely. QA testers need to understand and handle these various authentication methods effectively, which can be time-consuming and complex.
How to overcome
Understand the authentication mechanism, best way to learn it in detail to go through their official documentation. Collaborate with developers to understand the edge cases, token life time, and other important details. Automate the authentication related scenarios.
Security Concerns
Ensuring the security of APIs is crucial as they handle sensitive data and provide access to critical functionalities. QA teams must verify that the authentication process is robust and cannot be easily compromised, protecting the system from unauthorized access or potential data breaches.
How to overcome
Generally companies prefer to have a separate team or vendor of security testing as they are the experts of this domain but QA can also learn the basics for security testing so that can identify the low hanging fruits.
Access Control Verification
APIs may provide different levels of access to different user roles. QA testers need to verify that the appropriate roles have access to specific resources and actions, while unauthorized roles are restricted from accessing sensitive information.
How to overcome
Design a matrices for access control users and their permissions, based on that design your test scenarios. Negative testing is mush for access control verification. Other than that, leverage automation testing for this purpose, data-driven test could be good approach for such kind of testing.
Token Expiry and Refresh
Many APIs use tokens for authentication, and these tokens can have expiration times. QA testers need to verify that tokens are refreshed appropriately and that APIs respond correctly to expired tokens, either by issuing new tokens or denying access.
How to overcome
It is similar to authentication test, understand the different timeouts of token and based on that design your test scenarios.
2. Data Validation Challenges
Data Format Validation
Ensuring that the data conforms to the expected format and schema is crucial for accurate parsing and processing. Many api service provider returns the response based on the request parameter. Example a api can return xml response if it accepts `?responseType=xml` query or header. In these scenarios, you have to write test case for each data format.
How to overcome
The best approach for this is to use model classes to serialize and deserialize the response content so that change in response format does not need a separate test or assertion code.
Data Completeness
Verifying that the API returns all expected data fields and values is vital for comprehensive data validation. Missing or incomplete data can lead to issues downstream in the application.
How to overcome
Schema testing for such cases is important to ensure that all the required fields are present in api response.
Handling Large Datasets
Some APIs return large datasets, which may challenge the performance and efficiency of the client application. Testing how the API handles and delivers large data payloads is critical for scalability.
How to overcome
By automation testing you can parse and verify the large datasets.
Data Type Validation
Ensuring that the API returns data in the correct data types (e.g., string, integer, boolean) is essential for proper data processing and prevents type-related errors in the client application.
How to overcome:
Schema testing for such cases is important to ensure that all the fields have correct data type.
Handling Null and Empty Values
APIs may return null or empty values for certain data fields. Properly handling and validating these values are critical for maintaining data integrity.
How to overcome
Schema testing for such cases is important to ensure that null values are correctly returned.
Timestamp and Date Validation
Verifying that timestamps and dates are correctly formatted and within the expected range is essential for time-sensitive applications.
How to overcome
Schema testing for such cases is important to ensure that date format is correct. Other than that, you can verify the date if necessary as time verification can change with the test execution time.
3. Error handling & Messaging challenges
Error Code Validation
Ensure that the API returns appropriate and standardized error codes for different types of errors. Test that each error code corresponds to the specific error encountered.
Error Message Accuracy
Verify that the error messages returned by the API accurately describe the encountered error and provide relevant details for troubleshooting.
How to overcome
Negative testing is mandatory to ensure that correct error code and error message returned by api.
4. Async operation challenges of API Testing
In this real-life API testing situation, we're dealing with an asynchronous API used for generating financial statements. When a user requests a statement, the API initiates a background process to create the statement, and it might take a bit of time to complete. On the frontend, we display a loading indicator to keep the user informed. To check if the statement is ready, we've set up a polling mechanism using a separate polling API. This polling API checks the backend at regular intervals to see if the statement is ready or not. Once the statement is generated, the polling API gives us a response indicating success, and we can then display the statement to the user. The challenge here is that the time it takes to generate the statement can vary, so we need to handle this unpredictability in our tests and make sure the test does not fail because of timeout.
How to overcome
In this case, a mocked response can be served to polling api to ensure that it correctly shows the information. Other than that, you also need to have coverage for scenarios when polling api receives error message in that case the test should cover the negative aspect. Dynamic waiting can also be an option but it significantly impacts the execution time so it should be used only when there is not other better approach. Additionally, synthetic test data can be used for faster processing.
5. Versioning challenges of api testing
Versioning challenges in API development arise from the need to evolve APIs while maintaining compatibility with existing clients and avoiding disruptions in service. As APIs evolve, versioning becomes critical to ensure smooth transitions and continuous support for both older and newer API consumers. Backward compatibility, handling multiple versions and maintaining consistency across different versions.
To overcome this, providers needs to plan their version precisely and properly communicate the changes to consumers. QAs needs cover different version in their automated test to ensure the coverage.
6. Non-functional challenges of api testing
Non-functional challenges typically revolve around performance, security, scalability, and reliability. Overcoming these challenges is crucial to ensure the API's overall quality and its ability to handle real-world scenarios effectively. To tackle non-functional challenges practically, we can adopt several strategies. Firstly, for performance testing, we can use tools like JMeter or Gatling to simulate different loads and analyze API response times under various conditions. Secondly, to address security concerns, we should conduct thorough security testing, including vulnerability scans, penetration testing, and authorization checks. Thirdly, for scalability testing, we can use cloud-based infrastructure to assess how the API performs under increasing user loads. Finally, to ensure reliability, we should implement robust error handling and conduct stress testing to determine the API's breaking point. By combining these practical strategies, we can comprehensively address non-functional challenges in API testing and deliver a high-quality and resilient API.
Conclusion
In conclusion, the challenge of API testing lies in navigating through these obstacles efficiently and strategically to deliver a robust and high-quality API that meets the diverse requirements of its consumers. By understanding the complexities and adopting effective testing approaches, QA teams can effectively ensure the seamless functioning of APIs in today's interconnected world.
About Author
Dheeraj is an experienced QA consultant with over a decade of expertise working with diverse clients. He possesses comprehensive knowledge of test automation, test strategy, and test planning. Dheeraj is passionate for quality, he ensures the quality mindset in the team where he works by his quality advocacy skills.
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