API Automation Testing – A Small Thing With Immense Impact

Reading Time: 14 minutes

The world would be a merrier place if people also had APIs. Just imagine being able to talk to another person specifically in a way that they would understand and receive. No miscommunication, mix-ups, or words left unspoken. Only a dialogue that’s always productive and pleasant.

That’s what API does for your software. It allows its parts to converse and exchange data. And since info swap is what makes your product work, you must understand the significance of this function’s pristine execution. So, let’s talk API automation testing.

What API Testing Automation Gives You

To better understand the role of automation in API testing, we first need to start with a fundamental question: “What exactly is API automation testing?”

Testing an API manually is often time-consuming and likely to introduce inconsistencies:

1. QA engineers define test cases outlining expected user interactions and API responses.
2. They manually send requests to the API, mimicking real-world scenarios (like a user logging into their account).
3. Then, they inspect the response data format (JSON, XML, etc.), status codes (success, error), and functionality (correct data returned, actions performed).
4. Based on the analysis, QA specialists may adjust the request or define additional test cases.

This process calls for unparalleled precision. So, yes, there are many opportunities for mistakes and delays.

When automated testing (AT) engineers handle API, it goes something like this:

1. QA professionals write scripts via a programming language. For instance, Python API automation testing is the most common choice. Also, they use an API automation framework to mechanize API interactions.
2. AT specialists configure the scripts with test data (inputs) for sending requests to the API.
3. They define expected responses (outputs) within the script for comparison with actual API responses.
4. After, the script runs autonomously, sending requests, validating responses, and reporting results (pass/fail).

As you can see, after setting up the tests, an API automation testing tool takes on the role of the executor. It runs the scripts incessantly and can do so in parallel. In other words, it can process multiple scenarios at once. Plus, there’s almost no room for error as the tool does precisely what it’s told to.

• Automated tests run much faster than manual testing. They allow for quicker feedback and faster development cycles.
• Automation can handle a vast number of test cases, covering more ground much faster.
• It also eliminates the possibility of human error in executing tests, leading to more reliable results.
• Scripts ensure tests are run exactly the same way every time, eradicating inconsistencies.
• Automated tests can be easily re-run with different test data sets, allowing for thorough testing under various conditions.
• Automation handles repetitive tasks, freeing up QA engineers to focus on other tasks.
• The process of creating automated tests often leads to clearer documentation of expected API behavior and test cases.
• Plus, automation testing for APIs is easier to maintain as you only need to worry about data updates.

To sum it up, API automation testing is a productivity booster for your project. But it can also be a drag. So, you need to pay attention to which cases you automate. For example, you’re better off with manual software testing for:

• A simple API with just a few endpoints for basic functionalities, like retrieving a static list of items or sending a simple message.
• An API might be used internally for a specific purpose, and testing only happens occasionally (e.g., monthly).
• Debugging a new API or exploring its functionalities to understand its behavior.
• Highly volatile API that’s under constant development with frequent changes and updates.
• Security and usability testing for the API, as well as overly intricate scenarios and edge cases.

You don’t want to automate the above as the effort to set up and maintain AT for them is too much work for very little reward. As with all automated software testing services, you need to know what exactly you want to get from an automated test. And if the outcome is of little value – don’t waste your time and money. Manual QA is still a strong and reliable choice for many situations.

API Testing: A Cheatsheet for Development Teams

API Elements & Their Testing

As we mentioned, API is a communication protocol for your software. But it’s not like a straightforward document with paragraphs and lines of text. It’s more like a little translation device. And for it to work, you gotta make sure parts of it perform together well.

Endpoints

Endpoints are the specific URLs within your API. They tell the API exactly where to direct an incoming request. Testing involves verifying if requests reach the intended endpoints and respond appropriately.

Request Methods

Request methods define the actions performed on the API. Common methods include GET (retrieve data), POST (create data), PUT (update data), and DELETE (remove data). Here, you need to ensure your API handles each method as expected for different functionalities.

Request Headers

Request headers are additional pieces of information attached to every request, often containing authentication details, content type (JSON, XML, etc.), or language preference. You ought to verify that the API interprets these headers correctly and processes requests accordingly.

Request Parameters

Request parameters act like qualifiers or filters that tell the API exactly what data you’re looking for or how you want it processed. Testing focuses on ensuring the API handles parameters, validates their format (e.g., numeric values), and uses them appropriately within the request.

Request Payloads (Body)

Request payload is the main data sent to the API in the request body. With testing, you secure the API’s ability to parse and understand the payload format (JSON, XML, etc.), validate its content against the expected schema (structure), and use the provided data for the intended action.

Response Status Codes

Response status codes are numerical codes returned by the API in the response, indicating the success or failure of the request. Common codes include 200 (success), 404 (not found), and 401 (unauthorized). Testing ensures the API returns the appropriate code for different scenarios.

Response Payloads (Body)

Response payload is the data sent back by the API in the response body. So, your API is to return the expected data format, validate the content against the schema, and check for the presence of relevant information.

Authentication & Authorization

These two mechanisms ensure that only authorized users can access specific API resources. Software testing services confirm that the API validates credentials correctly, enforces access controls for different user roles, and handles unauthorized access attempts well.

Error Messages & Codes

This duo offers informative messages and specific error codes when a request fails. Testing ensures the API returns clear and informative error messages, along with relevant error codes that help developers understand the cause of the issue.

Data Validation & Schema

The API should enforce data integrity by validating the format and content of data received in requests. Here, QA engineers center on checking that the API validates data types (numbers, strings), checks for missing required fields, and rejects invalid data to ensure data consistency within the system.

Versioning

APIs might evolve over time, leading to version changes. Hence, you ought to see how your app interacts with different API versions. You might also want to test how the API handles requests targeting deprecated versions.

Also, do note that these elements might differ depending on your API testing architecture. Many of them are common across most architectures. For instance, REST API testing automation is the most popular variant. But there are also SOAP, GraphQL, gRPC APIs, etc.

And the elements within them may be dissimilar. For example:

• Unlike REST’s focus on JSON or plain text, SOAP APIs use XML for both requests and responses.
• GraphQL relies on a defined schema that outlines the available data and relationships. But REST APIs don’t necessarily have a separate schema document.
• gRPC utilizes its own communication protocol built on top of HTTP/2. REST APIs typically use standard HTTP methods over HTTP/1.1.

Don’t feel pressured to choose REST API automation testing because it’s the most popular option. Always focus on what you need and what’s best for your project. The same goes for an automation framework for API testing. Remember, it’s not so much about what you work with, but how you work with it.

And in case you want to know more about what is REST API automation testing and its alternatives, be sure to check the article below.

The One Swagger API Walk-Through to Answer All Your Questions

Testing Types to Automate for Swift APIs

Now, let’s discuss the testing types you should include in your test automation strategy. All of them secure the flawless execution of your APIs from multiple angles. In other words, besides checking that an API runs well, you also need to investigate how it handles large user volumes, how it behaves in distinct environments, how protected it is, etc.

Integration Testing

Integration testing ensures that the API interacts correctly with other APIs, services, or databases. Automated integration tests can:

• Validate data exchange between different systems.
• Ensure that API endpoints correctly call external services.
• Detect issues in the communication protocols.
• Confirm that combined functionalities of multiple components meet the expected outcomes.

Functional Testing

Functional testing ensures that the API performs its intended functions correctly. These tests validate that each endpoint in the API works as specified by the requirements. Automated functional tests typically include:

• Checking that the API returns the correct status codes for various requests.
• Verifying the accuracy and format of the response payload.
• Ensuring that CRUD (Create, Read, Update, Delete) operations work as expected.
• Testing the API’s response to valid and invalid input data.

Performance Testing

Performance testing evaluates the responsiveness, stability, and scalability of the API under different conditions. Automated performance tests can:

• Measure response times for various API endpoints.
• Simulate high traffic to assess how the API handles load.
• Test the API’s behavior under stress conditions to identify breaking points.
• Ensure that the API meets performance benchmarks and SLAs (Service Level Agreements).

Compatibility Testing

Compatibility testing ensures that the API works correctly across different environments, configurations, and versions. It usually centers on:

• Verifying that the API functions as expected with different operating systems and browsers.
• Ensuring compatibility with various versions of client applications.
• Checking that the API works correctly with different database systems or third-party services.

Security Testing

Security testing is critical for identifying vulnerabilities in the API that could be exploited by attackers. So, you should:

• Check for common vulnerabilities such as SQL injection, XSS (Cross-Site Scripting), and CSRF (Cross-Site Request Forgery).
• Validate that authentication and authorization mechanisms are properly enforced.
• Ensure that sensitive data is encrypted during transmission.
• Test the API’s resilience against DDoS (Distributed Denial of Service) attacks.

Other Types of Testing

In addition to the types mentioned above, other tests can also be automated to enhance API quality:

• Usability testing helps make the API easy to use and well-documented for developers.
• Regression testing ensures that new changes do not break existing functionality.
• Data validation testing checks that the data processed and returned by the API is accurate and conforms to the expected format and constraints.
• Compliance testing validates that the API meets industry standards and regulatory requirements.

Test Automation Strategy PDF

As you’ve noticed so far, API automation testing isn’t that simple (as is the case with AT in general). So, the best advice we can give you is not to think too much about API automation testing frameworks or automation tools for API testing. Instead, get yourself a skilled team who can treat every one of your worries as a simple task.

Whether you want to cultivate your in-house talents or take advantage of QA outsource, just make sure that your people are indeed experts. That’s the only way to build a well-functioning product. A product that people will remember.

Test Cases to Automate – The Baseline

Since API testing automation is rather intricate, you might be wondering how to write automation scripts for API testing. The good news is that it’s no different from creating any other AT script. So, no surprises here.

Plus, we already have a resource dedicated to this topic. Instead, allow us to give an automation baseline, so to speak. We’ll review a few examples of API test cases that you definitely should consider for automation.

How to Write Automation Scripts. The Basics AQA Engineers Should Know

• Status code confirmation. Ensure that the API returns the correct status code (e.g., 200 OK, 404 Not Found) for a given request.
• Response time audit. Verify that the API response time is within the acceptable limits (e.g., the API should respond within 200ms).
• Response payload inspection. Check that the response payload contains the expected data structure and values (e.g., correct JSON structure, proper field names, and data types).
• Authentication and authorization. Test that the API properly enforces authentication and authorization. For example, ensure that endpoints requiring authentication return a 401 Unauthorized status code when accessed without valid credentials.
• Data integrity. Validate that the API correctly processes input data and returns accurate results. For instance, when creating a new resource, verify that the returned data matches the input.
• Boundary value analysis. Test the API with boundary values for input parameters to ensure it handles edge cases properly (e.g., testing with maximum and minimum input values).
• Error handling. Verify that the API returns appropriate error messages and status codes for invalid requests (e.g., 400 Bad Request for malformed input).
• Rate limiting. Test the API’s rate-limiting functionality to ensure it restricts the number of requests from a client within a specified time frame and returns the correct status code (e.g., 429 Too Many Requests).
• Dependency verification. Ensure that the API correctly interacts with its dependencies, such as databases or other APIs, and handles scenarios where dependencies are unavailable.
• Schema validation. Validate that the response matches the expected JSON schema, ensuring the correct data format and required fields are present.

These test cases help keep the fundamental aspects of your APIs healthy and running. And that’s what you should take away from this. Automate test cases that deliver value to your product quality and team efficiency.

API Automation Testing Challenges

When working, our QA team loves imagining what can go wrong. But we’re not pessimists. We’re just proactive. And thinking ahead, especially about potential hurdles, helps you be better prepared. It also safeguards you from unpleasant surprises. So, here are some of the most influential challenges of automation API testing to consider.

Documentation Deficiencies

This is a frequent roadblock. Incomplete or unclear API documentation makes it difficult to understand the API’s functionalities and what aspects to test. Without this knowledge, you might write irrelevant tests or miss crucial areas entirely.

Complex Test Scenarios

APIs often interact with multiple systems and services. This means you’re likely to come across complex test scenarios that involve various dependencies and integrations. Accurately simulating these interactions and their combined behavior can be difficult and time-consuming.

Dynamic & Large Data Sets

The main task for APIs is to handle data. Lots of it. Plus, this info can be highly dynamic, changing with every request or over time. In turn, you need robust data handling strategies and mechanisms to ensure consistency and reliability.

Maintaining Test Scripts

Due to ongoing development and updates, APIs undergo frequent changes in endpoints, parameters, and response structures. And your test scripts need to keep pace with every modification. Doing so requires a continuous effort with diligent version control, documentation, and maintenance practices.

Environment & Data Dependencies

API tests depend on specific environments and data configurations to run correctly, including databases, servers, and network conditions. Ensuring consistent and isolated test environments, managing data dependencies, and avoiding conflicts with production data can be challenging, especially in CI/CD pipelines.

Flaky Tests

Automated tests can sometimes produce inconsistent results due to timing issues, network variability, or other external factors. For you, that translates to regularly identifying and stabilizing flaky tests. And you need to constantly maintain a suite’s reliability to avoid false positives or negatives.

Tool Selection & Skill Gaps

These two issues are as old as grandpa time.

With so many options on the market, picking an API automation testing tool is a surprisingly tricky task. Consider these common mistakes companies make when choosing a tool:

• Selecting a tool based on reviews and ratings alone.
• Prioritizing popular options due to their proven value (the buzz around them).
• Focusing solely on the features of automation tools for API testing.
• Disregarding the learning curve and ease of use.
• Not considering the QA team’s input regarding the selection.

The secret to finding an option that’s right for your project is to mix all of the above.

• Do inspect the ratings but remember that not everything is as it seems.
• Review tools that are tried and tested. But don’t be afraid to go for less-known variants if they suit your product better.
• What a tool can do for you is paramount. Yet, it’s not the only thing that matters.
• Assess how simple the tool is to use daily and for long periods of time. You don’t want your team struggling during their work. And you don’t want to present them with a tool they know nothing about – this will only slow down the SDLC.
• Be sure to gather QA engineers’ insights on what tools they consider worthwhile for your product. Their expertise and experience will help you land an option that’s both productive and convenient.

And as for the skill gap conundrum, well, we hope you know nothing about it. Yet, unfortunately, struggling with finding talent is an ever-present matter. In the IT industry, its impact is felt most sharply. So, before you set out to build a strategy, pick tools, and so on, focus on people.

People and their authentic expertise are what make a memorable product possible.

IT Recruitment Insights from a QA Outsource Company

Dos & Don’ts in API Automation Testing

People who are genuinely skilled in automation API testing will also be able to offer you insights that can enrich your product. And we believe in the power of knowledge exchange. Most importantly, we want your project to succeed. Thus, we asked QA Madness’ professionals about API testing wisdom nuggets. Go ahead and fill your plate.

Prioritize These Aspects for Fruitful Automation API Testing

The following tips let you build a strong AT strategy and simplify the testing process.

Understanding the API Documentation

Thoroughly review and understand the API documentation to know the endpoints, request types, parameters, authentication methods, and expected responses.

Writing Clear & Concise Tests

Use descriptive names for your tests and structure them for readability. This improves maintainability and collaboration.

Using Externalized Data

Avoid hardcoding data directly in your tests. Leverage external data sources like CSV files or databases for reusability and easier test maintenance.

Automating Key Scenarios

Focus on automating critical and frequently used scenarios. Prioritize tests that cover essential functionalities and common use cases.

Testing Error Handling

Don’t just focus on happy-path scenarios. Design tests to verify the API’s behavior when encountering errors or unexpected inputs.

Performing End-to-End Testing

Ensure that your tests cover end-to-end scenarios, including all dependent systems and services, to validate the complete workflow.

Using Mock Servers

Employ mock servers to simulate the behavior of external services, allowing you to test your API in isolation.

Applying Continuous Integration

Integrate your API tests into the CI/CD pipeline to ensure tests are run automatically with each build or deployment, catching issues early.

Avoid These Aspects to not Sabotage Your Automation Testing API

At the same time, preventing these troubles from occurring will fortify your testing efforts and unload your team from unnecessary revisions and fixes.

Overcomplicating Tests

Don’t make your tests too complex. Aim for simplicity and readability to make maintenance easier and reduce the risk of false positives/negatives.

Overlooking Negative Testing

Positive test cases are not everything. Ensure you include tests for invalid inputs, incorrect data formats, and other negative scenarios.

Over-Automating Everything

Not every API interaction needs automation. Focus on critical functionalities and areas prone to frequent changes.

Neglecting Environment Configuration

Avoid running tests in only one environment. Test your API across different environments (development, staging, production) to catch environment-specific issues.

Skipping Documentation Updates

Don’t forget to update your test documentation and API documentation whenever changes are made. This helps maintain alignment between tests and actual functionality.

Forgetting about Manual Testing

Automation complements manual testing, not replaces it. Manual exploratory testing helps uncover edge cases automation might miss.

API Automation Testing Tools

Now, allow us to offer you a few high-value API testing automation tools you could look into. But remember, these options are indeed very useful. Yet, you don’t have to rush and use them exclusively. Carry out your own analysis and pick only those tools that fit your project needs and team expertise.

Postman

A popular all-in-one API platform used for designing, developing, testing, and documenting APIs. It has an intuitive UI and is great for:

• Building API requests.
• Sending requests with various methods (GET, POST, PUT, etc.).
• Validating responses.
• Data visualization.
• Automating with Newman (command-line collection runner).
• Collaborating, sharing, and documenting APIs.

SoapUI

A mature and feature-rich tool specifically designed for SOAP and REST API testing.

• Supports various protocols (SOAP, REST, GraphQL, etc.).
• Offers comprehensive test suite creation with Groovy scripting.
• Provides powerful assertions for validating responses.
• Has security testing capabilities.
• Presents lots of reporting features.

Katalon Studio

A free and open-source automation testing platform that supports web, mobile, API, and desktop applications.

• Has a drag-and-drop interface for building test cases.
• Supports various scripting languages (Groovy, JavaScript, Python, etc.) for customizing tests.
• Simplifies data-driven testing with external data sources.
• Easy to integrate with CI/CD pipelines.
• Boasts many reporting functionalities.

JMeter

A popular open-source tool for performance and load testing, also capable of handling functional API testing.

• Simulates multiple concurrent users for load testing.
• Holds extensive test components for building complex test scenarios.
• Provides comprehensive assertions for response validation.
• Also has convenient reporting features with graphs and visualizations.

Swagger

Primarily an API design and documentation tool, but also offers built-in functionalities for API testing.

• Easily generates interactive API documentation from code.
• Tests API endpoints directly from the documentation.
• Facilitates validation against API specifications.
• Integrates with various testing frameworks.

REST Assured

A Java-based DSL (Domain-Specific Language) for writing clean and readable API tests.

• Has concise syntax for building REST API requests and assertions.
• Offers BDD (Behavior Driven Development) style for writing tests.
• Effortlessly integrates with JUnit and other testing frameworks.

Karate DSL

• A lightweight and easy-to-learn DSL for building API tests in a Java or Kotlin environment.
• Presents a readable syntax similar to Gherkin (used in BDD).
• Can reuse test cases across different APIs.
• Supports data-driven testing with examples.
• Integrates with a range of testing frameworks and CI/CD pipelines.

Apigee

A comprehensive API management platform from Google Cloud that includes API testing functionalities.

• Delivers built-in tools for designing, securing, monitoring, and analyzing APIs.
• Defines and executes API tests.
• Integrates with other Google Cloud services.
• Supports various testing scenarios (functional, performance, security).

Paw

A Mac-specific API client that offers features for development, testing, and documentation.

• Has a user-friendly UI for building and sending API requests.
• Offers environment management for different API versions.
• Makes response validation with assertions a breeze.
• Lets you collaborate and share API collections.
• Supports various authentication mechanisms.

Insomnia

A free and open-source API client that provides functionalities for development, testing, and debugging.

• Possess an accessible interface for building and sending API requests.
• Delivers environment and workspace management features.
• Secures response validation with code snippets and assertions.
• Works with various test modes (manual, collection runner).

To Sum Up

People who are great communicators often find more success in life. The same can be said for software that has its “talking points” figured out. After all, every product functions via endless, incessant strings of dialogue going around its systems. And if you secure flawless info exchange within your app, it’ll also find more success in the market.

Never forget that users value quality. And it should be a core aspect of any procedure, including API automation testing.