The mentioned terms are not the same and should not be confused!

This article clears up the confusion by exploring the key differences between HTTP and REST APIs, their use cases, and when to use each. Moreover, each subsequent concept is broader than the previous one.

What is HTTP?

HTTP (HyperText Transfer Protocol) is the fundamental Internet protocol, where hypertext documents include hyperlinks that the user can easily access. We use it to send and receive information, such as web pages, images, videos, or API data. In short, when you type a website address into your browser, HTTP is the language your browser uses to ask the server for that page — and then display it for you.

The HTTP protocol has been important since it began. It helped create the World Wide Web we use today. It was first made for simple web pages. Now, it has grown to support more complex duties.

What is HTTP API?

An HTTP API is any API that uses the HTTP protocol for communication between clients (like a web browser or mobile app) and servers. Typically, it uses standard HTTP methods like:

• GET – to retrieve data
• POST – to submit data
• PUT – to update data
• DELETE – to remove data

HTTP APIs are straightforward, flexible, and widely supported. They do not have to follow any specific design pattern or constraints beyond using HTTP to exchange data. The typical format: JSON or XML.

Status Codes

HTTP response status codes indicate whether a specific HTTP request has been completed. Responses are grouped into five classes below, follow the link to know details:

• Informational responses (100 – 199)
• Successful responses (200 – 299)
• Redirection messages (300 – 399)
• Client error responses (400 – 499)
• Server error responses (500 – 599)

What is a REST API?

A REST API (Representational State Transfer) is a specific type of HTTP API that follows a set of architectural principles defined by Roy Fielding in 2000.

It means that a server will respond with the representation of a resource (today, it will most often be an HTML document) and that resource will contain hypermedia links that can be followed to make the state of the system change. Any such request will in turn receive the representation of a resource, and so on.

An important consequence is that the only identifier that needs to be known is the identifier of the first resource requested, and all other identifiers will be discovered. This means that those identifiers can change without the need to inform the client beforehand and that client and server must be inherently loosely coupled.

Roy Fielding

Core Characteristics REST APIs

REST is not just about using HTTP to move data. It uses all the features of the HTTP protocol, namely the standard HTTP methods to perform CRUD operations (Create, Read, Update, Delete which match GET, POST, PUT, and DELETE operations, which we considered earlier). They allow quick data transfer between systems.

REST is designed to manage the chaos of Internet-scale usage, in a world of millions of users and endless data. To achieve this, it maintains a light and free connection between your app (the client) and the server. REST provides the foundation for meeting the requirements of the Web: extensibility, anarchic scalability, independent deployment of components, large-grain data transfer, and a low entry barrier for content readers, content authors, and developers.

This makes REST ideal for many modern web applications. These applications go from simple mobile apps to complex cloud services, and work with different programming languages and platforms. The program that adheres to the REST architectural constraints is informally described as RESTful.

Normally, a specific API has several endpoints, and each one links to a certain URL. Each request contains all the information needed to process it.

REST API Example:

Imagine a social media platform — it has different types of data (called resources) such as:

/users– represents users of the platform
/posts – represents posts made by users
/comments– represents comments on posts

Typical REST API Endpoints:

• GET/users – fetch a list of all users
• GET/users/123 – get details about a specific user with ID 123
• POST/posts – create a new post
• GET /posts/456/comments – extract comments for a post with ID 456
• DELETE/comments/789 – delete a comment with ID 789

As you can see, REST APIs process resources (e.g., users, posts, or products) as the core entities, accessed via unique URLs.

What is JSON?

JavaScript Object Notation (JSON) is a standard text-based format for representing structured data. It is a custom payload that contains a message with the properties and values we want to use to create or update a given resource.

Using tools such as Postman or Insomnia, you can receive a response to your request.

GET/users/123

{
  "user":{
    "id": 123,
    "name": "Educative",
    "age": 28
  }
}

Summary

HTTP API and REST APIs are ways for apps to talk over the web using HTTP rules, but do it in diferrent way.

It is like using a specific programming style, such as functional programming, in a language like Python.

Real-World API Examples to compare

• HTTP. It is a simple internet link like a https://testomat.io/ A universal addressing system (think URLs) — is the magic that powers the web.
• HTTP API. A weather app’s API might expose a single endpoint like an endpoint /weather?city=London to return data in a custom JSON format. It’s simple, so it may not follow REST principles.
• REST API: API REST, with resources like /{posts}/456/{comments} and standard HTTP methods (GET to retrieve, POST to create). It’s consistent and scalable.

Principles Guiding RESTful API Design

Not all HTTP APIs are REST APIs

The API needs to meet the following architectural requirements to be considered a REST API:

Key REST APIs principles:

• Stateless. No client state is stored on the server between requests. Nevertheless, the request must include everything needed to process it.
• Resource-based. Data is organized into resources with unique URIs (e.g., /users/123).
• Standardized methods. Uses HTTP methods (GET, POST, PUT, DELETE) consistently allows developers to build applications more easily.
• Layered system. It means each component interacts only with the next immediate layer. This abstraction supports adding features like caching static assets, proxies, and gateways to reduce response time or the server’s load.
• Scalable. Designed for performance and maintainability in large systems.
• Hypermedia as the Engine of Application State (HATEOAS). This helps clients navigate the available interactions and reduces the need for extra information outside the requests.

REST API principles help create systems that are strong, remain flexible, and work well together. They differ from other types of APIs, which may not be as organized.

REST: More Than HTTP

HTTP is the most common protocol for REST. This happens because it fits well with the above-mentioned REST principles. However, REST is flexible and not only limited to HTTP. RESTful systems can also use other methods, like FTP, if they can share data in a common way, which people sometimes forget when they explain it simply.

REST API Benefits

Let’s figure out how REST APIs enhance web services:

• Simplicity – a major benefit is the API architecture. The use of standard HTTP methods like GET, POST, PUT, and DELETE makes the REST API lightweight for understanding, implementation and maintenance.
• Separation of Concerns – clean separation between client and server logic enhances development. A main part of REST is splitting tasks between the client and the server. This way, they can work separately and be developed on their own as they grow. It makes it easier to scale and helps complex applications run smoothly.
• Statelessness – another important point is that every client request to the server needs to have all the information the server needs to understand and respond. This means the server does not need to remember any session data.
• Scalability – statelessness of REST makes it easier to scale applications and maintain them. They run fast for many users or in areas with low internet speed. RESTful APIs can handle many requests at once without issues.
• Flexibility – works with many types of data formats and can be used across different platforms and languages.
• Performance – caching and lightweight data transfers improve speed and reduce the load on servers. When clients save copies of popular resources, they make fewer requests to the server. This leads to quicker responses and a better experience for users.
• Widespread Adoption – REST API is well-supported by different tools, libraries, and frameworks, making integration straightforward.

It is also important to note that you do not have to strictly adhere to the REST software architectural style in every situation to reap its benefits. Apply REST principles when they are more suitable.

Comparing HTTP API & REST APIs

Let’s compare HTTP and REST APIs. We will discuss the main technical differences between them. These differences provide each API with unique features for various purposes. Developers need to know these differences. This knowledge helps them pick the right type of API for their projects.

We will also focus on the key factors that can affect their performance. Additionally, we will cover the best times to use each option. This comparison will show the strengths and weaknesses of both types of APIs. This way, you can test API of your project best.

HTTP APIs and REST APIs are both ways of software communication. Because of this, they are good for different situations.

Here are a few important points to consider when choosing between them:

Use Cases and Practical Applications

• REST APIs. These are great for public APIs, complex integrations, and apps that require careful monitoring and error tracking. They are the best option for developing flexible and scalable web services.

Security and Management Features

• Security Options. REST APIs usually feature strong security. They offer mutual TLS authentication, backend certificate checks, and tools like AWS WAF for better protection.
• API Management. REST APIs come with features like API keys, client-specific rate limits, and usage controls. These help to manage and keep track of API use well. HTTP API is a simpler definition and does not include these management tools.

Endpoint and Integration Capabilities

• Endpoint Types. REST APIs offer several choices. They support edge-optimized, regional, and private endpoints. On the other hand, HTTP APIs mainly use regional endpoints.
• Integration Options. REST APIs can use mock integrations. They are also good for scaling microservices. HTTP APIs are effective for private resources with load balancers, but they might not allow mock integrations.

Performance and Cost Trade-offs

• Cost Efficiency. HTTP APIs are often faster and less expensive. This makes them ideal for simple apps and times when quick development is important.
• Scalability and Flexibility. REST APIs perform better in bigger and more complicated systems. They use rest principles, such as not storing state and allowing caching. This supports being modular and growing on their own.

Performance and Scalability Considerations

• HTTP APIs are often faster. This is because they have a simple design and need less work. They are great for apps where speed is very important. Examples include high-frequency trading and real-time data streaming services on the public internet.
• REST APIs might be a little slower. This is because they focus on REST principles, which can lead to some delays. However, as time goes on, the advantages of using REST APIs, such as being easy to scale, often make up for this minor speed issue. They provide a simpler alternative for developers.
• REST APIs do not keep records of past requests. They can use caching to make things work better. This makes their responses quicker. It also helps them manage several requests at the same time. By using an application load balancer, they can share requests among different servers. This way, REST APIs can manage more traffic when necessary.

Conclusion

Web developers need to know the differences between HTTP and REST APIs. HTTP APIs have changed to meet specific needs in modern web development. On the other hand, REST APIs provide rules that improve web services. Both definitions have their own features and some similarities. It’s important to think about their performance and how well they can grow. Choosing the right API architecture will depend on what your project needs. By understanding the key traits of each, you can make a smart choice for your goals. If you want more information or have questions, check our Frequently Asked Questions section.

Get help from our experts to dive deeper into API integration. This can make your web development projects even better.

Choosing between API methodologies requires you to think carefully about what your project needs the most.

The post HTTP API vs. REST API: What’s the Difference and When to Use Each appeared first on testomat.io.

“Why you need Cucumber for API testing?”

What is API testing?

Typically, API (Application Programming Interface) testing focuses on analyzing the app’s business logic, security, and data responses and is generally performed by making requests to one or more API endpoints and comparing the responses with expected results.

Performed manually or with automated testing tools, application program interface or API testing is used to check the API’s functionality and security levels to prevent a negative impact on its performance and reliability.

Why do we need API testing?

When using various websites, apps, and other software products, users want them to be secure, reliable, and free of errors. While there are any issues at the application programming interface layer, it can result in user-facing errors, slow performance, and damage your reputation. Here is why API testing can be useful:

• With application programming interface tests, QA teams can define how different software components interact and check if they work correctly.
• With application programming interface testing, teams can identify potential problems and make sure that the software will handle diverse conditions effectively.
• When it comes to potential software vulnerabilities, APIs can become a potential entry point for attackers. With application programming interface testing, testers can detect weaknesses in software to protect security and privacy.
• If any changes have been made, API testing prevents disruption to existing applications that use this API and helps maintain backward compatibility.

Types of Bugs Detected with Application Programming Interface Testing

Generally, during application programming interface testing we check the following:

• Data accuracy to verify that the data returned from an application programming interface aligns with expected formats, data types, etc.
• Missing or duplicate functionality to make sure that there are no repeated or missed features.
• Authorization or permission checks to verify the identity of a user/application that is requesting access to an API.
• Response time to reveal the duration of time required to process a request and return a response to the client
• Error codes in application programming interface responses to reveal whether the API request was successful or not.
• Reliability, performance, and security issues (checking how well the software performs, finding security problems, or issues like crashes and memory leaks).

Types of API Testing

Here are some of the common API testing examples with different types of tests based on which test cases can be created:

• Functional testing. With functional testing for APIs, you send requests to an API and validate that the correct responses are returned.
• Performance testing. With this type, you can verify that the application programming interface can handle large volumes of data and high traffic.
• Unit testing. As APIs have lots of small moving components, it’s effective to test them during the development phase and validate that each software module performs as designed.
• Integration testing. With integration testing, you can check if your application programming interface works well with different parts of your software, including web services, databases, or third-party applications. But you need to remember that opting for this type is essential if your application programming interface is complicated and not isolated from other components.
• Regression Testing. With this type, you can make sure that your application programming interface is still functional after an update or bug fixing has been performed.
• Security testing. This type of testing protects your API from data breaches, unauthorized access, and other security issues by systematically assessing the application programming interface for potential vulnerabilities and implementing measures to prevent or mitigate them.
• Load Testing. This type of testing helps test an API’s performance under high-user traffic to prevent slow response times, increased server load, and poor user experience.
• Stress Testing. With this testing type, you need to test an application programming interface with large data or sudden spikes in user requests.
• API Documentation Testing. With API document testing, testers make sure that application programming interface documentation is always up-to-date and correct while the API is set up and functions as documented.

What is Cucumber?

Written in Ruby, Cucumber is a BDD framework that allows teams to use a human-readable Gherkin syntax for writing test cases. When test scenarios are written in plain language, teammates without technical backgrounds can better communicate and easily understand what is going on in the project. Cucumber tests are linked to step definitions written in a programming language, which are then executed to verify the app’s behavior.

When using the Cucumber framework for API test automation, you can efficiently test the APIs to uncover any bugs or vulnerabilities before they become problems as well as save time and money in the long run.

Why use Cucumber framework for API testing?

• With Cucumber, teams can write test cases in plain English and avoid misunderstandings about what the tests are verifying.
• Cucumber can be integrated with various tools for application programming interface testing.
• Supporting BDD, teams can focus on the behavior of the application rather than the implementation details.
• Teams can reuse step definitions across different scenarios and maintain tests more easily.
• Thanks to Cucumber, teams can see what has been tested and what the results are.

API Testing Cucumber Your Steps to Follow

With API testing, teams can validate the business logic, data responses, and performance of server-side endpoints. When using the Cucumber BDD framework, testing teams can create tests written in Gherkin and make them understandable for the whole team. However, teams should understand the application programming interface specifications before writing tests. They need to overview the API’s purpose, functionality, endpoints, request methods, expected request formats, and response structures at the very start.

How to set up Playwright & Cucumber?

Prerequisites

On the begining you need to make sure you have the following in place:

A development environment with your preferred programming language (e.g., JavaScript, TypeScript, Python) installed.

node -v
npm -v

Step 1: Start a Project

From the very start, you need to initialize the Playwright project, which can be done by running the next command:

npm init playwright@latest

After that choose the programming language as Javascript when asked in the command line.

Next, you need to add project dependencies and establish configurations for test runners. Install Cucumber and REST Assured dependencies for application programming test interface.

npm i @cucumber/cucumber

Also, add the Cucumber extension to your VSCode:

Finally, you need to install the node-fetch library to your project using:

npm install node-fetch

Anyway, you can use any other HTTP library.

Step 2: Create Feature File

After you start the project and establish the appropriate configuration, it is imperative to create a structure so that your the feature files and step definitions will be well-organized for better clarity and understanding. Cucumber tests start with feature files, which describe the behavior of your application and when creating a feature file, you need to use Gherkin human-readable format with the following structure:

• Feature: it gives explanation to the feature that is going being tested.
• Scenario: it provides information about test scenario.
• Given: it describes the starting condition.
• When: it defines conditions.
• Then: it determines the expected outcome.

Here’s a Cucumber API testing example of a Feature file for the JS project:

Feature: Login User

  Scenario: Successful user login
    Given I send a POST request to the user endpoint with the following payload:
      | email                | password          |
      | jolir86609@ikaid.com | pass              |
    When the response status code should be 201
    Then the response body should contain "John Doe"

We have to create a feature folder and add our file to insert this code. After that add the path to this file and the steps file in vs.code =>settings.json Refer to the screenshot below for guidance:

Create a cucumber.json file and also add a path. It should look like this:

Step 3: Create Step Definition Directory

At this step, you can create a directory called step_definitions and add a JavaScript file (for example, login.js) Similarly, look at the structure of the file tree on top.

const { Given, When, Then } = require("@cucumber/cucumber");
const fetch = require("node-fetch");

Given("providing valid url", async function () {
    this.res = await fetch("https://app.testomat.io/api/login/", {
        method: "POST",
        headers: { "Content-Type": "application/json" },
        body: JSON.stringify({
            email: "jolir86609@ikaid.com",
            password: "pass",
        }),
    });
});

When("the response status code should be 201", async function () {
    const status = this.res.status; // fetch returns status as a property
    if (status !== 201) {
        throw new Error(`Expected status code 201 but got ${status}`);
    }
});

Then("the response body should contain John Doe", async function () {
    const body = await this.res.json(); // fetch returns JSON via res.json()
    console.log(body);
    if (!JSON.stringify(body).includes("John Doe")) {
        throw new Error(`Response body does not contain 'John Doe'`);
    }
});

In the created file, you can implement the logic for each step defined in your feature file. Generally, step definitions are used to interpret Gherkin’s steps, execute actions like making API requests, and use assertions to validate API responses.

Step 4: Execute Tests

At this step, you can run your tests using the following command:

npx cucumber-js features

With this command, you can execute the tests defined in your Cucumber feature file and step definitions.

My test failed as the email is wrong, I know it. In addition, I checked this POST request with Postman also, you can see it better now.

Step 5: View Test Reports

To generate reports, you can integrate Cucumber’s built-in reporting features or use third-party tools like cucumber-html-reporter Based on test reports, you can get information about test coverage, success/failure rates, and potential areas of improvement.

Pay attention to the “format” settings in your cucumber.json file.

{
  "default": {
    "formateOptions":{
      "snippentInterface": "async-await"
    },
    "paths": [
      "tests/features/*.feature"
    ],
    "publishQuite": true,
    "dryRun": false,
    "require": [
      "tests/steps/*.js"
    ],
    "format": [
      "progress-bar",
      "html: cucumber-report.html"
    ]

  }
}

Cucumber Playwright Reporting with modern test management

Also, you can integrate test case management systems like testomat.io to get access to test results, metrics, and trends and quickly address any issues that arise during testing.

Push the Import button and just copy and paste the command in your CMD offered by TCMS to download your automated tests. By the way, it is a perfect option to sync your manual and automated tests in one place, consolidate Steps:

Similarly, with UI tips our test management suggests – launch a test execution of your Cucumber API Playwright framework.

Do not forget the recommendation to add a Playwright code runner plugin code to playwright.config.js file:

reporter: [
  ['list'],
  [
    '@Testomat.io/reporter/lib/adapter/playwright.js',
    {
      apiKey: process.env.TESTOMATIO,
    },
  ],
];

As a result, you can see such rich test result Report. It provides detailed insights into your test execution and comprehensive test run summaries, it ensures you have a clear view of your testing progress and quality metrics.

Best Practices for API Testing with Cucumber

• You need to remember that grouping your test cases by functionality is important. It will give you a better overview of the app status and improve maintainability.
• You can use mocking and stubbing techniques to simulate interactions with the application programming interface to isolate the application code from external dependencies and make the API testing process more efficient.
• You can apply hooks in Cucumber to set up preconditions and clean up post-conditions for test scenarios.
• You need to automate only what is not possible to be tested via unit or integration tests to avoid additional costs.

Bottom Line: What about using Cucumber test automation framework for Application Programming Interface (API)?

When you develop API-driven applications, you can use Cucumber for API testing. It offers a structured approach for writing human-readable feature files and linking them to step definitions. It helps teams create tests that are easy to understand and maintain.

There is no doubt that API testing is a critical part of the software development process. With Cucumber, you can make it more efficient and effective. By opting for Cucumber, you can deliver high-quality APIs and make sure that different app components function correctly.

If you have any questions, do not hesitate to contact our specialists for consultation!

The post Cucumber framework for API testing with Playwright example appeared first on testomat.io.

Of course, you might think Why not utilise all-in-one solutions? I chose it for API testing using the Newman command instead of HTML reports because it can be very useful for short APIs or only to make sure that some microservices are working properly without requiring long reports and generating many files. Usually, I use it for microservice testing on my project App.

Before starting this guide, it would be a good idea if you had a look at some articles related to API tests with Postman and Newman, plus making your Python APPs with Tkinter:

Namely, they are:

• Postman Basic Guide
• Create the First GUI Application using Python-Tkinter

And please make sure to pay attention to the article on this blog. Opting testomat.io testing tool also could serve as an alternative to get informative Python test reporting swiftly.

• How to make a rich report Using Postman and Newman

Pre Requirements:

1. Install python3 and pip3 in your system
2. Then, install the following Tkinter packages:

   sudo apt-get install python3-tk

3. This project was created in an OS Ubuntu 20.04
4. Install Newman in your system.
5. Create a folder for saving the files of your Tkinter App.
6. Export your Postman collection and Environment to the repository of your Tkinter App.

Let’s start the creation of our Tkinter testing App. The full code you can find in my GitHub repository.

First of all, create a Python file called menu.py Next, import the tkinter lib and create a class called Application which will contain all the elements of the main menu. Then, call the screen by adding the if __name__ == "__main__": instructions:

As a result, if you run your Python file, you should see the Thinker GUI window.

Create a new method within the class Application called screen with some information of the main menu and call this method when initializing the class:

Create a new method within the class Application called screen_buttons including the information of the Python Tkinter style buttons in the main menu and call the method in the class initialization:

Here are the button styles; You will see how they work in the following section of our Python Tkinter testing tutorial. The full code of our testing App is here

def screen_buttons(self): 
    self.bt_execute_api_tests = Button(self.main_screen,
 
            text="Execute API Tests", 
            border=2, 
            bg="#9ac7d2", 
            font=('verdana',10, 'bold'), 
            activebackground='#108ecb',
            activeforeground='white',
    command=self.openExecuteAPI
        ) 
    
    self.bt_execute_api_tests.place(
            relx=0.11, 
            rely=0.22,
            relwidth=0.2, 
            relheight-0.06
        ) 
    
    self.bt_quit = Button(self.main_screen,
 
            text="Quit Menu", 
            border=2, bg="#9ac7d2", 
            font=('verdana',10,'bold'), 
            activebackground='#108ecb', 
            activeforeground='white',
 
    command=self.main_screen.destroy
        ) 
    
    self.bt_quit.place(
            relx=0.11, 
            rely=0.52, 
            relwidth=0.2, 
            relheight=0.0
        )

Right after creating the method screen_buttons, create a new class called ScreenFunctions(), in which you put all the methods to redirect to the API tests page when we click on the button self.execute_api_tests.

Now, create a new file under the APP folder called execute_api.py. Under this file (execute_api.py), import the lib Tk and then create a class also called as Application in which you should write the following code:

Come back to the file menu.py, and import the execute_api file by writing the following line:

Include the class ScreenFunctions within the Application class as Application(ScreenFunctions) in the file menu.py

Execute the main menu again by opening the menu.py file. You should get the following screen:

If you click on the Execute API Tests, you should be brought to the screen initialized in the execute_api.py file. In the case you click on Quit Menu, the app will be closed.

Now, please open the file execute_api.py and let’s create the screen for executing our Newman tests through the methods attached to the buttons of the page by importing the Tkinter library in the execute_api.py file.

Our following step is to create some global variables identifying our folders and the Newman commands to execute each folder separately. In our example, our Postman collection has the following structure:

Considering that, create the following variables.

Note: The Execution of all folder indicates that you want to execute the collection as a whole, not only one specific folder.

Variable commands_to_execute_tests indicates each Newman command to execute the tests for each collection folder.

As in the menu.py file, create the ScreenFunctions class and create a function for returning to the main menu. Include class ScreenFunction in the Application class (same as did for the menu.py file).

Create a method called screen under the class Application and call it in the initialization to set up the screen.

Obs: Import the menu file to make sure it will be called!

Also, create two variables called x and y that will be used to place some buttons with the name of each folder and execute all options as well.

Under the ScreenFunctions class, create a function called create_button as the following code:

Now, within the Application class, create a method called buttons which will be in charge of the creation of the buttons displayed on the screen.

Call this function in the initialization of the class Application

If you open your Python file execute_api.py, you should have the following result:

Under the class Application, create a method called text_area which will send the terminal output generated from the Newman command execution. Call this method in the initialization:

The last method within the class Application is called  scroll_bar_screen, it will be used to scroll up and down the text area for looking at the output information from Newman execution (also call it in the initialization of the class Application):

Import the following libraries in the file execute_api.py before starting the final steps. Also, create two more global variables called  stop_thread and call it.

Let’s do the final steps to show the results of the Newman command in our screen in the file execute_api.py. Under the class ScreenFunctions, create the following methods as shown below clock method.

Now, enjoy your own Python Tkinter testing App and execute your Newman tests in a friendly and easy way by clicking on the folder or executing everything, as you prefer. Hope you revolutionize your approach to API testing!

Please let me know if you have any questions, reach out to me at my LinkedIn profile Pedro Carvalho. Once again I provide a Github repo of this project with full code. It will help you understand how the code works and how you can customize my experience for your test projects.

The post Test API Python automation with <br>a friendly Tkinter APP appeared first on testomat.io.

So let’s find out more about Cypress framework and REST API testing and what benefits it can bring into your workflow.

What is API testing?

API testing is utilized to confirm the functionality, performance, and security of application programming interfaces (APIs). Generally, APIs help provide communication and data exchange between diverse applications and services as well as allow them to interact and share information.

With testing the APIs, you can test various aspects of an API, including its endpoints, input/output data, error handling and so on to make sure that the API behaves as expected and meets the requirements of the apps/services relying on it.

What are the categories of API testing?

• Web APIs: With HTTP or HTTPS protocols, they are used for data exchange in a client-server architecture.
• REST APIs: Using HTTP methods like GET, POST, DELETE and PUT to perform operations on resources, they follow a set of architectural principles.
• GraphQL APIs: this type allows clients to request and get specific data they need and offers an efficient approach to data fetching.
• SOAP APIs: they use XML-based messages over protocols like HTTP, SMTP, or others for communication.

Why do teams choose Cypress for REST API testing?

Originally created to address the challenges and limitations of traditional end-to-end testing frameworks, Cypress Javascript frontend testing framework provides a developer-friendly approach, robust features, and seamless integration into the development workflow. Operating in the browser, it runs directly alongside your application and has more control over the browser and the ability to interact closely with the application.

Development and testing teams can easily install and set up it as well as simply add it as a dependency in the project or use it as a standalone tool. In addition to that, Cypress comes with a user-friendly interactive Test Runner that displays live test results, logs, and interactive debugging tools.

Let’s go more in-depth into some of the reasons why teams opts for Cypress when conducting REST API testing:

• With Cypress, teams can seamlessly integrate both end-to-end (E2E), Component and testing the API within a single platform. This helps them maintain a consistent test automation strategy across different layers of their applications.
• Thanks to JavaScript-based syntax, teams can leverage existing JavaScript skills for both frontend (E2E) and backend testing as well as drive efficiency and code reusability.
• In terms of in-browser testing capabilities, teams can visually observe API interactions in real time, get immediate feedback and improve the debugging process.
• Cypress’s automatic waiting mechanism eliminates the need for explicit waits in API tests. Before executing commands, it waits for the app to be stabilized. This reduces flakiness and improves the tests reliability.
• With Cypress’s time-travel debugging feature, developers can inspect the state of API calls at different points during test execution. This ultimately makes the issues identification and resolution easier.
• With easy setup and configuration, teams can quickly adopt Cypress into their testing workflow without difficulties.
• With a rich set of comprehensive commands specifically designed for API testing, teams can cover a wide range of functionalities, from making HTTP requests to handling authentication, simplifying the process of creating effective API test scripts.
• Thanks to real-time reloads and dual-view features, teams can dynamically reload the API configuration or specifications during development as well as display simultaneous viewing of test execution and API interactions.
• Teams can combine API tests with frontend tests to cover end-to-end scenarios and make sure that interactions between the UI (user interface) and the API (application programming interface) are smooth.

To sum up, teams choose Cypress in API testing in terms of its seamless integration and the ability to simplify testing strategies across different layers of apps. Cypress’s JavaScript-based syntax, real-time in-browser testing, and unique features, such as time-travel debugging, offer a developer-friendly and efficient approach for testing, streamlining it.

What are the benefits of Cypress REST API Testing?

Here we are going to overview what key advantages testing with Cypress brings in the testing workflow:

• Real-Time Reloads. With Cypress features, you can automatically reload the application in real time and make appropriate changes to your test code if there is a need. This makes the development and debugging process highly efficient.
• Fast Execution. With Cypress fast test execution, you can minimize the common flakiness issues in end-to-end testing and provide reliable and quick feedback to developers.
• Debugging Capabilities. With Cypress, you can pause and inspect the state of your application at any point during the testing process and simplify the bug fixing process.
• Simplified Syntax. When it comes to writing tests, Cypress requires less boilerplate code compared to other testing frameworks. This speeds up the learning curve of developers with varying levels of testing experience.
• Built-in Assertions and Commands. With Cypress built-in assertions and commands features, you can make the process of writing and organizing tests easier.
• Parallel Execution. Thanks to Cypress, you can run tests in parallel. This speeds up the software testing process and improves efficiency, especially when running tests in a continuous integration or delivery pipeline.
• Test Data and Mocking. With Cypress, teams can manage test data, mock API responses and validate status code. It provides using fixtures to load test data from external files and creating custom Cypress commands to encapsulate API-related logic.

What are the challenges QA teams face in Cypress REST API testing?

Here we are going to overview some challenges the teams face when conducting Cypress API testing:

• Limited HTTP Method Support. In terms of focusing on e2e testing tailored for interacting with the UI, Cypress’s support for various HTTP methods and edge cases in API testing might be more limited compared to other API testing tools.
• Lack of Granular Request Control. When conducting API testing, you need precise control over HTTP requests, including headers, query parameters, etc. Primarily designed for UI interactions, Cypress might not provide the same level of granularity and control.
• Data-Driven Testing Challenges. Compared to other tools specifically designed for testing, Cypress may not offer built-in features for efficient data-driven testing to handle a variety of data inputs and scenarios.
• Dependency on UI for Setup. As Cypress has a focus on interacting with the UI, there are additional complexities when trying to set up test data or authentication without involving the UI components.
• Test Execution Speed. Known for its fast test execution in the context of end-to-end testing, API testing might require repetitive and rapid execution of numerous requests. The overhead of the Cypress architecture may impact the speed of execution for API tests.
• Learning Curve for Testers with API Focus. QA engineers may find Cypress less intuitive for API-specific scenarios. The learning curve might be steeper for those who are more familiar with tools specifically designed for testing the API.
• Limited Reporting and Documentation for API Tests. Cypress’s reporting and documentation features are more tailored towards end-to-end testing scenarios. Reporting for API tests might not be as comprehensive or customizable compared to dedicated tools for testing APIs.

How to perform Cypress API testing

Before diving into automated Cypress API testing, let’s overview some of the key commands:

• cy.wait() facilitates the loading of async data and allows waiting for a network request.
• cy.route() directs test requests to specific handlers.
• cy.server() helps to maintain an entire server for a test suite.
• Test Runners: provides parallel execution of tests for quick turnaround time.
• cy.intercept() keeps the responses under control or simulates the behavior by intercepting the requests.
• cy.request() allows you to send HTTP requests and interact with APIs directly within your test cases.

Prerequisites

1. You need to install or update Node.js to make the HTTP requests to the API server.
2. You need to check if you have a version of Node.js compatible with Cypress. *On the moment of writing this article Cypress supports minimum Node.js 14+ version.

   node -v

3. You need to install your chosen code editor and configure it according to your preferences.

Once all the prerequisites are in place, you can follow these steps to carry out automated Cypress API testing:

Step 1: Set Up Your Cypress Project

Start from creating a directory for your Cypress API testing project named cypress-api by navigating to your preferred location with the following commands

mkdir your_cypress_api
cd your_cypress_api

By running the mentioned above command, you need to initialize a Cypress as a project dependency to automate web interactions and perform Cypress API testing:

npm install cypress --save-dev 
npx cypress open

Step 2: Write Your First API Test

When writing a simple Cypress API test script, you can use the cy.request() command to initiate HTTP requests, specifying the method, URL, headers, etc. This command allows you to perform testing with ease and provides assertions on the response status, body, headers, and other relevant details. Here is an basic example that demonstrates the simplest API response.

In this example, test hits the API server with the URL and checks whether a valid login request returns a status code of 200. This means the status code to be 200 for successful test execution.

describe("HTTP Requests", ()=>{
    it("Get Call", ()=> {
        cy.request({
            method:'GET', 
            url: 'https://reqres.in/api/users/2',
        })
        .then(function(response){
            expect(response.status).to.equal(200);
            cy.log(JSON.stringify(response.body));
            console.log(response.body);
        });
    })
});

Meet

Simple examples of REST APIs tests for starters using Cypress from official site

**Examples of uses of the Cypress API from Cypress Doc

Step 3: Run Cypress Tests via Cloud

Once you’ve written your first Cypress API test or already had the tests, the next step is to execute them. Running your tests allows you to validate the functionality and reliability of your API endpoints. Use npx cypress open command to open the Cypress Test Runner with an available list of your test files for your project to be executed.

You can choose to run all tests in the file or select specific ones for execution and ensure thorough examination of status code or status codes during the testing process. As the tests run, Cypress provides real-time feedback in the Test Runner interface. This helps you observe each test step, including API requests and assertions, in the interactive dashboard.

Step 4: Analyze Test Results

After test execution is complete, Cypress displays a summary of the results. You can discover information not only about passed and failed tests but also about errors. This helps you inspect test details, logs, and snapshots of your application. Based on test results, teams can make improvements and address issues.

Step 5: Integrate API Tests with CI\CD

Consider integrating your Cypress API tests into your Continuous Integration/Continuous Deployment (CI\CD) pipeline for automated testing. This helps you provide consistent validation with each code change and contributes to a continuous testing workflow. This practice also improves the overall quality and reliability of your software by validating the API endpoints throughout the development process.

Step 6: Visualize Test Results

Opt for third-party tools like testomat.io test management system helps you visualize test results.

With clear visual feedback, you can quickly identify successful builds and pinpoint any issues that require attention. In addition to that, continuously iterate your Cypress API test scripts based on feedback and changes in your API. This allows you to improve your test suite and add more tests to handle different API scenarios.

More detail step-by-step:

• Playwright Testing Tutorial on How to Organize an Advanced (Scaled) (e2e/unit) Testing Framework

Best Practices for Writing Robust API Tests in Cypress

These best practices help you maintain the highest quality of your test data and also make sure that each team member keeps up with relevant changes in the software testing process.

#1: Think of Modularization and Reusability

When it comes to creating Cypress API tests, you should organize your API tests into separate modules based on functionalities or endpoints to improve test structure. You can also apply Cypress custom commands to encapsulate complex API interactions that promote a cleaner and more readable test code. With modularization and reusability, you can adapt to changes in the API, facilitate easy updates, minimize repetition, and drive a scalable and efficient testing process.

#2: Establish a Structured Approach to Test Organization

Organizing tests into logical structures using describe blocks based on the functionality or feature they are testing is essential. Also, don’t forget about maintaining consistent names for test files and describe blocks. This helps team members quickly understand the content. A well-structured test organization not only improves readability but also simplifies test maintenance and collaboration within the development team.

#3: Encourage Continuous Debugging

A culture of continuous review and refinement of your tests helps you make sure that tests adhere to coding standards. Fast identification and resolution of flaky tests are vital. With automated monitoring tools, you can detect flaky tests, report inconsistencies in test behavior and resolve them. When encouraging regularly scheduled code reviews coupled with refactoring, teams drive a collaborative environment where code quality is continually improved and the codebase remains maintainable.

#4: Keep documentation up to date

A well-maintained API documentation becomes an invaluable resource for onboarding new team members and supporting collaborative efforts to maintain a robust API test suite. This also drives a shared understanding within the development team. Regular updating the API documentation allows each team member to better understand expected responses, error codes, and data structures and resolve any issue as quickly as possible.

#5: Incorporate Test Data Management System

Keeping test data closely associated with the tests provides clarity and simplifies maintenance. With a well-organized and efficient test data management system, you can regularly review and update test data to align with evolving application requirements. This improves visibility and comprehension, speeds up easier updates and troubleshooting when necessary and guarantees accurate testing outcomes.

Ready to drive innovation and use Cypress for API testing?

Cypress appeared to be a dynamic, powerful and user friendly testing framework to perform API testing. It not only establishes a developer-friendly ecosystem for creating resilient API tests but also provides unique functionality to test the integration between the UI and the API.

With Cypress, you invest in an efficient, reliable and scalable software testing process that helps you deliver the software products of high quality.

Drop us a line if you want to delve deeper into the realm of REST API testing with Cypress and discover more testing practices!

The post 🚀 Cypress and REST API Testing appeared first on testomat.io.

Alternatively, this prompts API providers support various integration scenarios. It is obviously integrating APIs into product has advantages.What’s more, reliable and well-designed APIs let organizations improve their applications, connect with external services, and achieve high SLAs.

Explore these article featured on testing blog:

• What is API Testing? Learn The Basic Go-to Guide
• Introduction to Web Services Testing

With various testing types in mind API testing is crucial as part of the SDLC process to reduce errors, improve predictability, and catch nasty bugs. You should incorporate API testing in your own testing lifecycle.

That’s where the concept of API testing reports especially with CI\CD concept comes in handy for the development teams and stakeholders to get fast and actionable testing results, visualize them, thanks to a clear and concise summary of the test results. API testing reporting represent a holistic view of the API’s performance and quality

Keep on reading to learn more details about API testing using Newman and Postman when creating API testing reports

Understanding the Importance of API Testing Reports

Being a crucial component in the software development and testing process, API testing reports provide valuable insights into the quality, performance, and functionality of APIs that are being developed. These reports work as a validation mechanism to make sure the API functions as expected and meets the specified requirements.

Based on API requirements described with documentation, developers and testers can not only identify issues and defects in the API implementation, such as incorrect responses, unexpected behavior, or security vulnerabilities but also assess the API’s performance under different conditions and user loads.

Also this enables them to detect unexpected behavior or security vulnerabilities as well as track these problems in detail and resolve them.

Additionally, exploratory of reqs are helpful in the following:

• validating the seamless API integration with other systems and data;
• tracking and prioritizing issues for the developers to be resolved;
• making informed decisions on the next steps in the development process;
• providing a transparent view of the API’s progress to facilitate communication with stakeholders, such as project managers, business analysts, product owners, clients, etc.;
• delivering comprehensive documentation of the testing efforts and results;
• monitoring the API’s stability by integrating automated API tests into CI\CD pipelines.

What role do Postman and Newman play in API Testing?

As well-known tools for API testing, they are powered with their own unique set of features and fulfill specific purposes.

→Postman serves as a comprehensive API development and testing platform and delivers a user-friendly graphical interface.

→Newman command-line tool, created by Postman – is specifically designed to run Postman collections in the same way they are executed inside a Postman collection runner. It sends API requests, receives the response, and then runs the tests against the response. Newman lets developers easily integrate Postman into continuous integration systems like Jenkins.

Let’s take a look at some of the most important features of Postman and Newman

• Instant Response Viewing: Teams can test any API and instantly observe the responses.
• Test Suite Creation: Teams can create test suites or collections with a combination of multiple API endpoints.
• Collaborative Teamwork: Teams can collaborate effectively by working together on multiple collections.
• Simple Import and Export: Teams can import or export collections as JSON files with ease to make sure that sharing and management are seamless.

What are the benefits of using Postman and Newman in API testing?

Conducting API testing from A to Z is no simple as it may seem. You have to oversee such aspects as request and response data validation, error handling, API versioning, and so much more. Luckily, there are tools such as Newman and Postman that can simplify this process. Let’s now quickly discuss what are the primary API testing benefits of these tools:

• When using Postman and Newman, teams can test a great number of API requests and responses, including GET, POST, PUT, DELETE, and ensure secure access to APIs thanks to various authentication methods, query parameters, request headers, and request bodies.
• Whether your team members are experienced developers or newcomers to API testing, Postman and Newman’s user-friendly graphical interfaces empower them to efficiently create, organize, execute, and automate API tests without extensive coding knowledge.
• With Postman and Newman, you can not only set up and manage different environments (e.g., development, staging, production) but also switch between them during testing.
• By providing a command-line Newman’s interface for running Postman collection, it is easy for the teams to integrate API tests into continuous integration and continuous deployment (C\CD) pipelines. When used together, Postman and Newman teams can run API tests automatically whenever there are code changes or deployments. This helps facilitate test automation and identify issues early in the development process.
• Thanks to integration capabilities, these tools help development and testing teams meet various testing and development needs.
• With Newman which supports JSON reporter and standard HTML reporter, you can generate collection run reports and communicate test results effectively.
• Supporting JavaScript’s pre-request scripts and test scripts, these tools help teams automate the setup and validation of API requests and responses to execute faster and eliminate human errors.
• With a cloud-based workspace provided by Postman, teams can accelerate the API testing and development process by staying in sync when sharing API collections, creating multiple environments, such as development, staging, and production, and keeping track of the version history of collections and environments and so on.

Overall, using Postman and Newman for API testing streamlines the testing process, enhances collaboration among team members, supports test automation, and provides comprehensive test reporting capabilities. These factors contribute to the popularity and effectiveness of using Postman and Newman for API testing in a wide range of software development projects. But not only these factors influence, QA teams also choose these tool of the next reason, we gathered them below for you. So,

Why do teams choose Postman and Newman in API testing?

Working together in API testing, Postman and Newman allow teams to streamline the testing process, enhance collaboration, and provide comprehensive reporting. Below you can find out how they complement each other:

• Both Postman and Newman are available on multiple platforms, including Windows, macOS, and Linux, making them accessible to developers using different operating systems. Their command-line interface allows teams to automatically run tests and generate test reports directly from the command line.
• User-friendly graphical interface, testers and developers with Postman can create and organize API tests with ease – from designing API requests, and setting up test scenarios to validating the responses.
• Postman offers a structured way of organizing tests as collections. This simplifies the process of managing, executing multiple tests and sharing them with team members.
• Teams can automate API tests runs of Postman collections with the Newman, and integrate them into continuous integration and continuous deployment (CI\CD) pipelines, eventually make them a part of their CI\CD process.
• Teams can automatically run collections and provide prompt feedback on potential issues with each code change or deployment.
• Completely remove the human elements in the testing, using Newman to prevent or minimize human errors during API testing.
• JSON-based test results can be turned into comprehensive and visually appealing HTML reports to provide stakeholders with a clear and concise overview of the API’s quality and performance and help in further decision-making. Using Newman enables teams to generate API test results in JSON format and deliver more detailed information about them. Moreover, these test results can be used for further analysis and reporting.

Have take a look the potential of crafting such Report with the help of our test management solution. Furthermore, the Report incorporates Analytics and makes possible synchronization of your API tests with other automated and manual tests within a one platform.

Integration Postman and Newman from example

It is simple visualization of how we can set up a simple API test automation framework tests saved in Postman Colection, running these tests in the command line using Newman — a command-line Collection Runner for Postman, set up throuch Test Management Workflow with CI\CD pipeline and send test reports to test management app backward.

Our team prepared a bunch of demonstration projects for to ensure your success with testomat.io TCMS. In addition to the Newman template following through the link, access examples Cypress, Playwright, Cucumber, Jest, CodeceptJS and plenty of other testing frameworks. Download the needed test project there and explore how it works firsthand.

These are the steps you need to follow to run the example with test management:

• Create a new test project
• Generate API key and import auto tests into TCMS
• Install Reporter
• Execute Postman collection of test scripts
• In result receive HTML report and Analytics, saved test run retrospective

Prerequisites for installation Postman and Newman tools

npm install -g newman

On top is how to install Newman client globally otherwise install modules in project below

npm i

#1 Create a new test project

Start by Sign Up or Sign In to the TMS, and then create your test project by honouring the system tips.

After you create your project, get into it. Select Import Automated tests on the dropdown menu in the top right corner. Thanks to the Advanced Importer you can import your automated tests to the test management system with a few clicks and make them visible there for the whole team.

#2 Generate API key and import autotests

Our TCMS is a wise tool. TCMS recognizes your laptop OS and generates a command with API key according to it. You should copy this command and execute it on CMD. This one uploads your API tests from source code to test management.

Look at the console, how the importer analyzes code accurately and displays the number of founded tests in the test framework. If you enter your project, you will see these tests. You can view their structure by expanding the tree. You may enter your suites and check test cases inside.

#3 How do I create a report for Postman?

Track test results to test management with our advanced reporter. It is an open-source part of our test automation tool. Copy and paste this command into CMD to install reporter:

npm i --save-dev @Testomat.io/reporter

#4 Execute Postman collection of scripts

You are ready now to run your API tests with test management. Execute your Postman collection and receive results synced in test management.

Run the following command from your project folder just replace API key and file name on yours:

TESTOMATIO=<API Key> npx newman run <File Name> -e env.json -r Testomat.io

Once the tests have finished running, the CLI will generate a report link. Test results will appear through the console on the test management dashboard. Share this test result link with stakeholders by email or messengers. Choose whom available detailed report. The type of public report does not contain security-sensitive info.

We have performed tests oft, and each of these runs saves some historical data.

We can analyze the results of running tests using advanced analytics. The following testing metrics are available on the Project Analytics dashboard and Global Analytics dashboard. Our team are currently working on expanding with new widgets.

Analytics shows the history of your test runs and failures, flaky tests, slowest tests, never run tests as well as test automation coverage of your test scope.

In detail, we describe each step precisely and in order in official Documentation as well. Check it for more options.

Best Practices for Rich API Testing Reports

Here are the most essential pieces of information from the best practices for API testing reports with Postman and Newman:

1. Define Clear Objectives and Select Relevant Metrics. To get the most out of your API testing reports, it is crucial to clearly understand what you want to achieve with them. When clear goals and objectives are defined, you have a concrete game plan to stick to it in achieving the testing goals. In addition to that, it is mandatory to select the right metrics to make sure that the testing efforts are focused on the essential aspects of the API’s performance, functionality, and security as well as help you pinpoint the API’s bottlenecks.
2. Visualize Data Effectively to Highlight Test Outcomes. If you tend to understand vast amounts of test data and communicate that understanding with team members and stakeholders, visualizing your results is critical. Results visualization empowers teams and stakeholders to explore data in a more interactive and dynamic manner. With charts, graphs, and tables, they can delve deeper into specific information to gain actionable insights about the testing process by checking the status code of the responses. Through test results visualization, they can identify testing opportunities, uncover inefficiencies, and make informed adjustments to the testing strategies.
3. Include Request and Response Details and Add Contextual Information. With detailed information, teams can identify patterns in API behavior quickly, compare requests and responses between versions to validate consistency and reproduce reported bugs easily. Adding contextual information allows stakeholders to quickly grasp the API’s status and performance without being overwhelmed by unnecessary data. This not only helps them interpret the test results accurately but also allows them to draw data-driven and meaningful conclusions.
4. Automate Report Generation. If you want to save precious time and effort for teams, automating test report generation is a way out for you. This will significantly improve the efficiency and effectiveness of API testing and eliminate manual compiling and formatting of reports as well as reduce the risk of human errors. Moreover, you can provide real-time insights into the API’s performance, functionality, and security after each Newman Postman run to identify issues early and take immediate actions.
5. Review Data Accuracy. Data presented in the test reports should be accurate and complete. That’s why teams must check configurations, input data file, expected outcomes, and the process of capturing and recording data to ensure that the test results reflect the actual API behavior. What’s more, this confirms that test scenarios represent real-world use cases and provide valuable insights.
6. Solicit Feedback. Gathering feedback from stakeholders is fundamental to understanding their expectations and views about the test reports. When collected, you can make improvements to the reports based on their needs and preferences. However, be prepared to look at the negative aspects of the process and learn from mistakes. Both positive and negative feedback can work for the better of your API reports and should be considered as improvement points.

Harness the Power of API Testing Reports Using Newman & Postman

Creating API testing reports with Postman and Newman is still a key ingredient in building a successful and robust product. The benefits of using these tools speak for themselves and deliver a competitive boost to your organization while improving collaboration and communication, minimizing human errors, and making informed decisions during development and testing.

On the end with Postman and Newman tools in place, you can achieve the API testing goals with greater efficiency and provide the delivery of reliable and high-quality APIs.

Ready to learn more? Our experts are ready to answer all your questions about API testing and help you get started on creating API testing reports.

The post API Testing Essential Guide: <br>How to make a rich report 📊<br> Using Postman and Newman appeared first on testomat.io.

An example of this interaction between two digital solutions can be the ability to access a personal account on a particular resource through another existing account. We are talking about those “Sign in with Facebook” or “Sign in with Google” buttons that most modern developers place on their web pages. The two platforms must be linked through an API to make this possible.

Thus, to successfully use the API to create or optimize your software product, it is important not to neglect such a critical stage of the software development lifecycle as running API tests.

API Testing: The Essence and Components of the Process

The API testing process is the testing of the functionality, performance, and security of the application programming interface. This procedure consists of making requests to the API and then analyzing the responses. To speed up the testing process, you should automate such test cases. Automated test scenarios can include:

• requests to a single API endpoint;
• requests to multiple endpoints;
• testing different endpoint variations under changing test environments (e.g., running tests on other devices).

Such tests can be conducted independently or as part of integration testing because this type of testing allows you to trace the quality of interaction of multiple software components.

API testing often contrasts with user interface testing because of the drastically different objects being tested. While the latter focuses on the outer shell of the application, quality assurance of APIs focuses on the business logic of the software system, i.e., the middle layer of the three-tier architecture of software products.

Challenges and Benefits of API Testing

By paying proper attention to the quality assurance of APIs, QA teams can significantly improve the quality of the created digital solution and, as a result, increase the business’s profitability.

Among the advantages of this type of testing are:

1. Obtain a wide range of product information. Thanks to API testing, you can:
   → Check whether third-party applications can integrate with your system based on the API.
   → Send API calls, i.e., send a request to the API to extract data from the external app and deliver it back to the user. Once a response is received, you can check it for accuracy and consistency with expectations.
   → Evaluate the integration capabilities of your application.
2. Opportunity to automate test cases. You can reduce the cost of QA processes on the project and release products faster than with manual testing.
3. It is possible to use any language to write automation scripts. For communication and data exchange, APIs use JSON or XML formats; they are language-independent.
4. A comprehensive approach to error detection testing. Not all types of testing show a complete picture of the software’s performance. For example, unit tests check individual components of a program. Their results make it unclear how the entire system will behave. API testing, however, allows us to ensure that all the software components work correctly.
5. High speed of execution. If we compare this type of testing with UI tests, the latter is 35 times slower. Thus, API testing allows for identifying more bugs in a shorter period.
6. Ability to run early in the development lifecycle. The earlier you identify various bugs and performance bottlenecks, the cheaper it will be to fix them.
7. Improved test coverage. The specifics of API testing allow you to create functional and non-functional automated tests with great coverage.

In contrast to the above positive aspects, we should mention some challenges that testers may face. Among them:

• Limited API knowledge. In addition to other types of testing, your team should have a good understanding of the API testing approach. An in-depth knowledge of API’s basic functionality will allow you to create an effective testing strategy and qualitatively test the API. To build the necessary knowledge and skills among testers, you should run pilot projects and hold regular API testing training and other events for specialists.
• Creating tests that do not mimic user interaction. Sometimes testers limit themselves to running tests for individual web services and consider their results relevant. However, we should not forget that real users rarely interact with them separately. So, it makes more sense to create integration tests for the API to check the work of all the program modules.
• Ignoring the “response time” indicator. Often testers focus on checking the core functionality of the API and do not pay attention to the time it takes to process the request. When the team receives the expected results, it treats the test as passed. However, this can’t be 100% true if the API is slow. As a rule, high-performance APIs process a request in 0.1-1 second. If this increases to 5 seconds or more, users experience a noticeable delay, which can cause them to stop using the site.
• Not including API dependencies in the testing strategy. Quality assurance of only the application programming interface can give an incomplete picture of how your application works. Modern APIs depend on third-party web services, so you need to monitor each of them as well. If a partner server fails, your product won’t work properly, which will surely affect the satisfaction of your customers. Keep it in mind.
• Not only testers are involved in API testing. To optimize the development of APIs, it is necessary to make their testing transparent to all teams involved in the API development lifecycle, including Back-end developers and Manual QAs. To do this, it is important to set up notifications of the actual results of API tests for development teams and all stakeholders.
• Manual testing of APIs. Running an API test manually can be a real challenge for QA engineers, as it requires a significant investment of time and resources. Using advanced API testing tools enables teams to automate repetitive tasks, thus speeding up product testing and development as a whole.
• Writing inappropriate test cases and prioritization errors. To ensure that API testing does not go to waste, it is important to consider before creating automated test scenarios which API functions and properties need to be tested. After you have defined the list of tests, you should prioritize the actual running. First, you should test the most critical functions; those that have the strongest impact on the user experience.

Despite some difficulties arising during testing, APIs offer developers, customers, and end users more advantages. Improve your team’s knowledge, analyze product and testing requirements before writing API test cases, collaborate on the project as a team, and you will be able to perform efficient API testing strategy and create first-class software.

Types of API Testing: Check Your Software Comprehensively

The quality assurance process involves dividing software testing into many types, depending on which functions or features of the system are being tested. When it comes to API testing, the situation is the same; testing each feature and function of the API involves running tests of different types. Let’s deep into them more…

Load testing

With load testing, the QA team determines how well the API can handle many requests for a certain period. As a rule, it is performed in three stages.

→ First, tests are run for a “basic” scenario, which assumes an average, scheduled load.
→ The second stage of testing is performed with the maximum traffic.
→ The third stage is called the “overload test”; in this case, 10-20% additional traffic is added to the maximum possible traffic.

Security testing

As the name implies, this type of testing checks the security of the API. Such tests evaluate an extensive list of parameters, including the reliability of encryption methodologies, the ability to withstand cyber threats, and the implementation of API access control mechanisms.

Penetration testing

It is planned hacking attacks on the interface as a whole or its functions, processes, and resources. Testers, in turn, evaluate the severity of the threat from external sources.

Fuzz testing

Fuzz testing involves introducing many randomly generated requests to the system to detect failures, errors in data processing, or other variants of the negative behavior of APIs.

Security, Penetration, and Fuzz testing constitute the API security audit process.

Runtime and error detection

This type of testing allows you to comprehensively assess how the API works. It focuses on implementation error monitoring, predictability of response to valid and invalid requests, resource leakage, and correctness of error detection, processing, and routing.

Functional testing

Functional testing checks if a particular function is executed correctly according the API endpoints. It involves checking the code base to ensure the API processes requests according to the planned parameters.

UI testing

When considering this testing from the source code perspective, the focus is less on the API and more on the user experience of the corresponding interface. User interface testing allows you to assess how user-friendly, efficient, and functional it is. This type of testing is similar to previous functional testing type.

Eventually, test validation of API play a crucial role in API testing. It is one of the main stage of the SDLC and provide a comprehensive view of the software interface. Validation testing helps developers and testers answer several questions, including:

1. How efficiently does the API do what it needs to do?
2. Does the API solve the problem?
3. Does the API get access to the data it needs, and how well does it meet privacy requirements?

During APIs quality assurance, paying sufficient attention to every aspect of testing is essential. This is the only way to ensure the final product will be user-friendly, secure, functional, and high-performance.

API testing best practices imply performing this procedure in several stages. We do not recommend neglecting any of them. The desire to reduce the time required for testing will decrease the quality of the work performed.

Step #1. Learn the API specification

Before proceeding to error detection, answer a few questions:

1. What is the purpose of using API in your application?
2. How do the APIs work?
3. What results do you expect from using the interface?

You can find all endpoints and needed information in the API specification, a JSON or YAML format document containing a list of functions, elements, and a description of the expected API’s behavior.

Step #2. Defining testing requirements

The QA team must understand what exactly it will test at this stage. It is necessary to study the end users to understand for what purpose and how they will use the application. This analysis will allow you to determine the areas to test API. For example, it could be the system’s response data or time.

Step #3. Setting input parameters

Before launching the API test, identify all possible input combinations of parameters. This is extremely important because input parameters provide the API with the necessary information for its operation. For instance, when performing a function on an object, the parameters may include the object’s name and library.

Step #4. Creating positive and negative tests

To obtain fair results, it is essential to conduct not only positive but also negative API testing. The first one is focused on checking API functioning using mandatory and additional parameters. The second one is aimed at error detection when wrong input values or negative behavior of the consumer are specified. In other words, a QA specialist knowingly accepts incorrect data and checks what will happen with the API respond in a non-standard situation.

Step #5. Choosing API testing tool

The global API testing market offers testers a wide range of specialized software for API test automation. When choosing among dozens of available solutions, it’s essential to consider the needs of your project, the characteristics of the digital product being tested, and your team’s experience. Users can access open-source offerings and paid platforms, so you can select a testing tool regardless of your project’s budget.

Now, let’s discuss in more detail what to consider when choosing the right API testing tool and briefly explore the most popular solutions in today’s market.

How to Choose the Best Tool for API Test Automation?

To make your API testing experience a success, we recommend that you pay attention to such criteria, when you will choose your API testing tool:

• Ability to import settings and artifacts from one project to another. This will save the team time and resources.
• Ease of use. Learning to use a too complex tool will result in a longer project time frame.
• Integration capabilities. Support for seamless integration with CI\CD tools like Jenkins will help you quickly set up your testing process. Also, check if you can integrate the testing tool with your team’s project management system, task management (like Jira), bug tracking tool and corporate messengers (like Slack). This will allow professionals to work in a familiar environment and increase productivity.
• Support for collaborative project work. One of the Agile methodology principles is to involve non-technical people in the workflow of the software product. Check whether the tool supports BDD testing and whether it provides documentation that all team members can understand.

Among the most popular solutions on the API testing market are Katalon Platform, Postman, Soap UI, JMeter, ReadyAPI ect.

Along with them, the testomat.io test management system also allows work with API as manual tests as well as automated tests through Newmam integration and track their results in one plaсe. Many QA teams choose this TMS because of its wide range of features:

• support the most popular testing frameworks like Cypress, Playwright, Cucumber, CodeceptJS, WebdrivewrIO, Testcafe and many more…
• easy writing of manual test cases due to wide reusable functionality;
• detailed reporting in an understandable format and access to in-depth analytics;
• integration with popular CI\CD tools: GitHub, GitLab, Jenkins, Bamboo, CircleCI;
• seamless integration with Jira, Linear, AzureDevOps task management;
• ability to import tests from other testing tools.

	Description	Pros & Cons	Pricing
	Cloud-based full cycle API management platform.	Checkmark Fast Many features and integrations Popular, active worldwide community	Free Up to 3 users Plans user/month: Basic $12 Professional $29 Enterprise Plans price for asking
	Open source platform for testing, debuging and documenting RESTful APIs	Easy-to-use Collaboration and Version Control Extensive Plugin Ecosystem Multi-protocol Support	All core functionality up to one cloud project free Plans user/month: Individual $5 Team $12 Enterprise $25
	Open-source written in Java application for performance and API testing.	Highly customized Large community support	Free
	Open-sourse REST API client library for .NET	Rich functionality Support both synchronous and asynchronous requests	Free
	Open-source Pythons library for making HTTP requests	Rich functionality Customization options Clear documentation	Free
	Low-code Java based tool for E2E API testing	Rich functionality Drug-n-drop UI Integrated with CI\CD tools	It is open-sourced and Free Ready API license costs $796 to $6, 339 per year
	Open-source Java library for testing and validating REST APIs	CI\CD integrations Community support	Free

Bottom Line

API testing is a type of testing that is necessary to ensure that the application programming interfaces being used are functioning properly. To ensure effective quality assurance, conduct comprehensive API testing using various tests, automate the process to save resources, and choose an API test automation tool that best suits your team.

We hope this information has been helpful to you in understanding API testing. If you have any questions, please don’t hesitate to contact us. Our experts will be more than happy to answer each one.

The post What is API Testing?<br> Learn The Basic Go-to Guide appeared first on testomat.io.

What is a Web Service?

On the World Wide Web, a web service is a standardised method for propagating messages between client and server applications. A web service is a software module that is intended to carry out a specific set of functions. Web services in cloud computing can be found and invoked over the network.

It is a set of open protocols and standards that allow data to be exchanged between different applications or systems.

Software programs use web services through a variety of programming languages that run on a variety of platforms to facilitate a smooth exchange of data via computer networks such as the Internet in a similar way to inter-process communication on a single computer.

In other words, any software, application, or cloud technology that uses these standardised web protocols (like HTTP or HTTPS) to connect, interoperate, and exchange data messages – commonly XML (Extensible Markup Language) – across the internet is considered a web service.

How Web Services Work?

A web service works on the principle of Request and Response. These are typically in the form of XML, though other types are also supported. A client invokes a web service by submitting an XML request, which the service responds with an XML response.

What is the difference between an API and a web service?

There is a general consensus that web services and APIs are one and the same thing. This is not correct!

While all web services are APIs, not all APIs are web services.

Web service is a collection of open-source protocols and standards used for exchanging data between computer systems or software applications, whereas API is a software interface that allows two applications to interact with each other without any user involvement.

The other differences API and web services are:

• Web service is used for REST, SOAP, and XML-RPC for communication, while API is used for any style of communication.
• Web service supports only HTTP protocol. API supports both HTTP and HTTPS protocol.
• Web service supports XML, while API supports XML and JSON.

Why is Web Service Needed?

Most softwares today works on principles of request and response. Users send requests for the data they want to see and receive the response. It is not advisable or feasible to develop each and every software because they are already developed and are ready as plug and play versions.

For example:

You want to check the flight availability from city A to city B. You can buy the services from the people who already are well-established in processing and publishing such kind of data rather than developing the entire application, collecting data, processing it and then finding the usefulness of it.

The same goes with weather forecasts, stock markets, sports scores or any other data.

What is Web Service Testing & What Are Web Services Testing Tools?

Just like any other piece of software, Web Services also requires to be validated so we can ensure the functionality, reliability, performance, and security of an API (Application Program Interface) works as intended.

You can test a Web service manually by using tools like SoapUI or Postman (available as an addon to chrome ) or create your own automation code. EIther way, it is important to test if the Web service is giving a correct response to the request in the desired timeframe.

Automating Web Services Testing

Automating Web Services testing is critical for testing web applications in an efficient manner. Automation helps quality test engineers study how specific web services work in varying situations.

Web services automation testing allows engineers to isolate and automate one aspect of a web service, whether it be load testing, API testing, etc., and see what factors affect performance and behaviour.

At the end of the day, web services test automation tools help developers and designers confirm that web applications meet business standards and requirements while providing a quality User Interface and high functionality for end-users.

Web services automation testing includes:

• Validating API calls
• Checking API responses
• Running integration tests
• Executing test cases within test suites

This also ensures better test coverage and smoother test execution, especially when incorporated into the CD pipeline.

How are Web Services Implemented?

Before beginning automation for Web services, one should understand how web services are implemented. This knowledge will certainly help when automating them.

Web services are nothing but communication enablers between two machines, software applications or web applications. There are two main ways that web services are implemented: SOAP and REST.

SOAP

SOAP stands for Simple Object Access Protocol. SOAP is a standard web services protocol that is used to send, receive, and respond to web service requests. XML format is used to send and receive web service requests. This allows data to remain independent from the platform that is being used.

Example: A SOAP request to fetch user data of user “Mike”

<soapenv:Envelope
	xmlns:soapenv="http://schemas.xmlsoap.org/soap/envelope/"
	xmlns:sch="http://www.soapexample.com/xml/users">
	<soapenv:Header/>
	<soapenv:Body>
		<sch:UserDetailsRequest>
			<sch:name>Mike</sch:name>
		</sch:UserDetailsRequest>
	</soapenv:Body>
</soapenv:Envelope>

The response, just like the request, consists of a SOAP envelope and a SOAP body. The SOAP body represents the requested user data.

<soapenv:Envelope
	xmlns:soapenv="http://schemas.xmlsoap.org/soap/envelope/">
	<soapenv:Header/>
	<soapenv:Body>
		<ns2:UserDetailsResponse
			xmlns:ns2="http://www.soapexample.com/xml/users">
			<ns2:User>
				<ns2:name>Mike</ns2:name>
				<ns2:age>33</ns2:age>
				<ns2:city>Cambridge</ns2:city>
			</ns2:User>
		</ns2:UserDetailsResponse>
	</soapenv:Body>
</soapenv:Envelope>

REST

REST is an acronym for Representational State Transfer. REST follows HTTP protocol with an emphasis on client and service interaction. Instead of using XML like SOAP, REST uses simple URLs and built-in HTTP headers to relay metadata between web applications.

Representational State Transfers have a limited amount of operations when compared with SOAP.

Example: A REST request to fetch user data of user “Mike”

A REST API accepts GET parameters from the URI.

GET https://restexample.com/users?name=John

The user is represented in JSON like this:

{ 
"name": "Mike", 
"age": 33, 
"city": "Cambridge" 
}

Automating Web Services Testing:
Challenges and the Role of Web Services Tools

Just with the decision that web services need to be automated does not make the case easy. Automating web services is complex and you should be well versed with automation techniques, tools and knowledge of how web services work.

While planning for web service automation, the following challenges are faced and organisations should have plans to tackle them:

• Setting up Metrics to measure
• Finding the starting point
• Making sure Code coverage is high
• A robust and efficient QA process

Setting up Metrics to measure

KPI (Key Performance Indicators) are important criteria to assess the value of your quality assurance tests in the information they provide. There are decisions that are taken by the team with data getting produced through the automated tests. These will drive the direction of the development projects and the overall success of your business.

Setting up key performance indicators for your team is very important as it measures success.

Your development, testing, and other teams need to agree on what success looks like and which key performance indicators are the most important measure of it.

With a clear vision and solid KPIs, web service test automation can be a long-term benefit to your organisation.

Finding the starting point

When to start automation remains the biggest question in front of all developers. Setting goals and agreeing on measurables will help define your starting point, but you’ll still need to create a web services automation testing strategy. We answer this tricky question by using one of the two popular philosophies in quality testing. The first is risk-based testing, and the second is the Test Automation Pyramid.

A risk-based testing approach highlights the riskiest areas of a web service in terms of the costs involved or the probability of failure; often, these two concerns overlap. This approach structures web service test automation based on the areas that present the most risk.

On the other hand in the Test Automation Pyramid approach, we structure the web services test automation differently. In this approach, organisations structure their web services testing like a pyramid. In most cases, the Test Automation Pyramid begins with unit tests, then moves on to integration, component, and API testing, and finally, ends with UI testing.

Both of these approaches are fine strategies to optimise your web services’ testing resources.

Making sure Code coverage is high

The code coverage by the automation scripts determines the success or failure of any automated web services testing. Code will likely be integrated regularly as you work on a web application.

The challenge is to ensure that your test cycles are optimised to include the code changes being made, so errors are not potentially missed. Web applications need to be tested against multiple different combinations of browsers, operating systems, and devices to ensure high quality.

Robust and Efficient QA Process

The QA team and management team need to be organised and on the same page when it comes to the QA process and the desired results. Clear communication lines at every stage of the QA process are just as important as the automation tools being used to streamline your web services testing.

The project should have a clearly defined RACI matrix, and enough stress should be done on the reporting part as well.

Web Services Automation Testing

Web Services Automation Testing involves following steps –

1. Preparing the WSDL file
2. Finding what the particular web service provides
3. Preparing the XML request which we need to send
4. Determine the response XML format
5. Writing code to send request and validate the response

E.g. first 4 steps are explained via a code snippet

There are lots of WebService Test tools available to test web service. SoapUI is one of the popular API tools which will help us to test SOAP web services. In fact you can use any programming language which is capable of sending the XML request to the web service provider application over the http and able to parse and validate the response XML against the expected result. Java is a huge language preferred when testers want to write scripts from scratch.

Summary

• Software Applications communicate and exchange data with each other using a WebService
• SOAP and REST are 2 popular protocols to create a WebService
• SOAP supports XML based data exchange
• REST supports XML, Json or exchange of data in simple URL for WebServices API Testing.
• WSDL is a XML based language which will be used to describe the services offered by a web service. SOAP is defined using WSDL.

To test WebService you can

• Create your own code. For instance use Axis2 API for Java
• Use WebService Test Automation tools like SoapUI
• Automation Tools like SoapUI or Postman will jumpstart your Web Services Automation Testing efforts, will require less coding effort compared to creating your own code using Axis2 API

Thorough software testing of web services ensures that your application programming interface is robust, scalable, and secure.

The post Introduction to <br>Web Services Testing appeared first on testomat.io.