In a nutshell, an API is a set of functions that allows the sharing of data between independently run applications. Over the past 24 months, more enterprises have begun to modernize their applications by adopting an API (Application Programming Interface) first strategy. This represents a major move away from traditional SOAP-based APIs to RESTFul APIs. This strategy has increased the demand and complexity for the test automation.
Automated API Testing – Essential for Cloud Migration & Modernization
Automating API testing is essential for functional, load, regression, and integration testing. API automation streamlines integration and regression testing every time a new change is made. It allows the testing of business functions separately from the user interface. API test automation also reduces the turnaround time in the software development release cycle, feedback, fixes, and redeployments, which makes applications more reliable and successful. In addition, OpenAPI specifications and API test automation with the use of generated mock data makes it easier to discover any integrations issue sooner in the lifecycle of the API development.
What is API Contract, and Who Writes it?
Where do you start with API automation? An API Contract. An API contract is nothing more than a user manual for the API that basically tells the users how to utilize or consume the API. The OpenAPI Specification (OAS) standard that has made it easier to document APIs. The OpenAPI Specification is a community-driven open specification within the OpenAPI initiative, a Linux Foundation Collaborative Project. API developers in collaboration with the business sponsors can put together OpenAPI compliant specifications that can serve as a contract. In our practice, we always start with an API contract in OpenAPI standard format before writing any code. The contract serves as our baseline to develop the service and create test cases. It also lays out how to accomplish a number of tasks, such as creating mock data and test cases. Mock data enables your team to automate API testing in the Continuous Integration (CI) pipeline.
Testing An API
Testing an API is different than testing other parts of a software product, because APIs operate on the business layer of an application rather than the presentation layer and don’t directly interact with users. Through API testing, testers get access to the full application functionality even before the GUI is implemented. API tests are generally created out of individual request-response interactions based on the API contract and the mock data. The inclusion of such test execution in the CI pipeline results into quick feedback. This way, developers can ensure that the API made available to test with the application is error free. Detecting API bugs early and failing fast helps to reduce the time to production.
The following approach is considered while creating test cases for testing an API:
- Input validation – Developers will use different input parameters and verify the response to test the API. For each set of input parameters, the data, response code, and the message should be correct, and the API should return correct HTTP error codes – 200 for a valid input parameter and 400 for an invalid input parameter.
- Response validation – You should validate the response for its correctness against the API contract.
- Negative test cases – You should consume the API with incorrect/invalid parameters, missing/extra values, and null values for mandatory fields, and observe the output. You also need to verify that the API can handle long strings, integers, and incorrect data types for parameters. You should also determine how it behaves in the case of conditions like timeouts and server failures, and, assuming that the exception handling mechanism works correctly, you need to make sure that error messages are clear and relevant.
- Reliability tests – You should verify whether the API can consistently return a correct response or if response failure occurs often.
- Call sequencing verification – Verify if the output of the API includes modification of a data structure, firing of an event or call to other APIs are functioning correctly.
- Security testing – All business-critical APIs should go through security testing to make sure that the code and associated features are not vulnerable to unauthorized users. Security testing also includes user authentication, data encryption, and user access control.
- Performance testing – You should ensure that the remote services can handle a large number of concurrent requests from clients and is capable of sending responses back to the application on time.
Methods for Performing Automated API Testing
Automated API testing is used to ensure the reliability and performance of an API when it goes into production. Here are a number of areas that should be covered as part of your automated API testing approach:
- Repeated test design for API functional testing.
- Creating loads of dynamic data to enter in API testing.
- Analyzing functional test coverage.
- Increasing the speed of the testing process.
- Utilizing multiple data sets coherently to cover various test scenarios.
- Testing protocols in a single, unified framework.
- Testing in various languages.
- Using command-line to connect tests to the build system.
- Testing in different test environments, including development, testing, and staging.
- Test forced errors at the API to understand how it will react.
How Do You Measure Success?
The answers are simple:
- Your applications are secure, high performance, and largely free of defects.
- Data is easily accessible to the users and applications that need it and no one else.
- You can deploy updates rapidly and reliably without impacting users to add new functionality and address issues.
- You get your applications into production quickly.
- You don’t have issues with application security.
- Most importantly, your users are happy with the new, modernized applications that you delivered to them.
By 2023, 80 percent of new application starts will be in the Cloud, and some exuberant analysts are predicting that the creation of new, on-premise data centers will end by 2025. In addition, enterprises are migrating existing workloads to the Cloud at a rapid...
At Optimoz, we spend a lot of our time helping companies migrate their important applications to the Cloud. It’s harder than you might think. Most Cloud applications are built using technologies and tools that weren’t mainstream five years ago. Cloud...
Driven by the power of the Cloud, the software development process – and development lifecycles - is transforming. Downtime is becoming a thing of the past with highly available architectures and immutable infrastructure. The scale of utilization is increasing as...