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Software testing has evolved with time to detect and lessen errors in software and applications. In 2024, 63% of QA teams are prioritizing test automation over manual testing to achieve the agility needed throughout the software development lifecycle (SDLC), while also ensuring cost efficiency.
Although manual testing still holds a fair share in testing processes, enterprises is increasingly relying on automated testing to reduce the time needed for the more tedious, repetitive, and time-consuming tasks of it. Considering the direction that the industry is heading, automation testing is sure to stay, even becoming a norm that QA teams must learn to adapt to. To conduct automation testing, it is important to equip yourself with knowledge of an automation testing framework.
Let's dive in and learn more about most common types of test automation frameworks currently!
What is a Test Automation Framework?
A test automation framework is a structured set of guidelines, libraries, and tools designed to facilitate the creation, execution, and maintenance of automated test scripts. It defines how tests are organized, the rules for writing scripts, and the mechanisms for executing them across various environments.
Put simply, think of a test automation framework as a set of guidelines that provides the structure for how tests are written, where they’re stored, and how they interact with the system being tested. Many frameworks allow you to script your tests in several different languages.
Take Selenium as an example. It is one of the most popular open-source web testing framework out there that supports JavaScript, C#, Groovy, Java, Perl, PHP, Python, Ruby, and Scala. Developers and testers can leverage Selenium commands (called Selenese) to write scripts in any of those languages to automate interactions with web elements.
There are so many more components that make up a test automation framework, including:
- Test data
- Driver scripts
- Environment variables
- General user library
- Business user library
- Recovery scenarios
- Object repository
- AUT(Application-Under-Test)
- Test execution report.
4 Reasons Why You Need Test Automation Framework
Here are a few reasons why you should start using frameworks for test automation.
- Organization: Instead of having test scripts scattered around or hard to find, a test automation framework keeps everything in one neat place. Whether it’s test scripts, test data, or logs, having them all centrally stored means you can easily access, manage, and collaborate without chaos.
- Maintenance: When your software changes, your tests need to change too. With an automation framework, keeping everything in sync is a breeze. It allows you to update your tests quickly without having to redo everything from scratch.
- Reusability: A good automation framework doesn’t just save you time today—it saves you time tomorrow, next week, and beyond. By designing reusable test scripts, you’re not stuck writing new tests for every little function. Instead, the same tests can be applied across different areas of your software.
- Scalability: As your application grows or the number of features increases, your testing needs change too. A well-built automation framework is flexible enough to grow with you. It allows you to scale your tests up for more complex scenarios, like load testing, or scale them down for smaller unit tests, without a ton of extra effort.
Given that test automation frameworks also contribute to better test accuracy, it's common to find them as a crucial component of modern DevOps practices. There are several paid and open-source testing tools enterprises leverage to execute tests on applications.
Types of Test Automation Framework
1. Linear Test Automation Framework
A Linear Test Automation Framework follows a straightforward approach where test scripts are written sequentially, executing each step in the order in which it's recorded. This framework is often referred to as a Record and Playback framework. Each test case is a self-contained script, with no reuse of code or modularization, meaning every test script has its own set of instructions for interacting with the application under test (AUT). It mostly leverage the record-and-playback method to achieve this.
Not sure how that works? Let's have a look at the Record-and-Playback functionality in Katalon:
Since most actions can be recorded, this framework is ideal for users without in-depth programming skills, and tests can be executed soon after recording them. However, since each test script is independent and does not reuse code, leading to redundant steps across multiple tests. If the application changes, each test script must be updated individually. This increases maintenance effort when dealing with a large number of scripts.
Therefore, this type of framework is mostly used for projects that have basic testing needs. It is best for:
- Learning automated testing: Helping learning testers to explore test methods, underlying test code, and object repositories and use them as references for more advanced scripting in the future
- Applications with simple functionalities: A straightforward page that doesn’t have new features introduced constantly will be the perfect fit for the linear test automation framework
2. Modular-Based Testing Framework
The modular-based testing framework is the more granular version of the linear testing framework. The AUT is first broken down into smaller, independent modules. Each of these modules represents a specific part of the application, and individual test scripts are created for each module. They are then combined to build comprehensive test cases, allowing for more efficient management and reusability of code across the entire test suite.
Why is this a helpful practice? It's because modularization improves isolation. If one module of the software changes or breaks, it won’t mess up everything else. You can fix or update that one module without touching the whole system. It’s like being able to replace a single puzzle piece without having to redo the entire puzzle.
In testing, this isolation makes it much easier to pinpoint issues, maintain tests, and keep things running smoothly as the application evolves.
However, the downside is that the initial creation of the modular framework requires more effort compared to linear frameworks. Each module needs to be carefully designed and integrated into the test suite. This requires a more organized approach to testing. Building a modular framework also typically requires testers to have programming skills to design reusable components and properly structure the test scripts.
If not handled carefully, modules may become dependent on one another, which can lead to issues when changes in one module affect others.
To make it easier to work with a modular-based testing framework, you'd also need an Object Repository. An object repository is a centralized storage or database where all the UI elements (like buttons, text fields, and links) used in your tests are stored. These elements are identified by their properties (such as their ID, name, class, or XPath) and are given meaningful names. The purpose of an object repository is to make managing and using these elements in your test scripts easier.
Instead of hardcoding element locators (e.g., XPath, CSS selectors) directly in the test scripts, you reference them by their name in the object repository. The test script interacts with the UI by looking up the element's locator in the object repository and then performing actions like clicking a button or entering text.
For example, you can have an entry like “LoginButton” with a locator call //button[@id='login']. Why is this important? If an element's locator changes (e.g., the XPath of a button), you only need to update it once in the Object Repository instead of updating all the test scripts that use it.
3. Data-Driven Testing Framework
Simply put, the idea behind data-driven testing is that you only have to create one test script that stays the same, but you plug in different data (like usernames, passwords, or inputs) from an external file, like Excel or a database. The test runs over and over, each time using a different set of data.
A data-driven testing framework is especially helpful when you have hundreds (sometimes thousands) of different data points to test for one single scenario. Login page testing is a good example. For one single login page, you usually have to run a lot of test cases, such as:
- Verify login with valid username and password.
- Verify login with an invalid username.
- Verify login with an invalid password.
- Verify login with both invalid username and password.
- Verify the login when the username field is left blank.
- Verify the login when the password field is left blank.
- Verify login functionality with case-sensitive usernames and passwords.
- Verify that the password is hidden (masked) when typing.
- Verify that the user is redirected to the correct home page after successful login.
- Verify the behavior when the "Enter" key is pressed after entering credentials.
- Verify the "Forgot Password" link functionality.
- Verify if the login form can be submitted by clicking the "Login" button.
If you throw two-step authentication, CAPTCHA, or a verification email flow into the process, the number of test cases surely won't stop at 12. That's why you only write one test script, but dynamically change the credential values for different scenarios.
The benefits? It allows for broad test coverage with minimal additional scripting. Also, if you need to update or modify test data (e.g., changing input values), you can do so in an external data file (like Excel or CSV) without altering the underlying test script, making managing test cases easier, especially in large projects where frequent changes occur. Excel/CSV, GraphQL, Oracle SQL or databases with JDBC drivers are common datasets used for data-driven testing.
Learn How To Do Data-driven Testing
4. Keyword-Driven Testing Framework
The magic of a keyword-driven testing framework happens behind the scenes. Each of keyword is essentially just a code snippet that tells the system exactly what action to perform. They usually have parameters that testers can fill in to specify on which element should the action take place.
Instead of writing the full script, testers only need to piece those keywords together, with each keyword being a test step. For example, to build a test case to test the Login page in a keyword-driven framework, they'll need the following keywords:
1. OpenBrowser (Chrome)
2. NavigateToURL (https://website.com)
3. Click (ID of Username field)
4. SetText (username)
5. Click (ID of Password field)
6. SetText (password)
7. Click (ID of Login button)
8. WaitForOnScreenElement (check for the successful login popup)
At its core, a keyword-driven testing framework is trying to separate test logic and test execution. Even non-programmers can create and manage tests by simply piece together the sequence of actions (keywords) they want to perform. The beauty of this approach is that it’s highly reusable—once you define a keyword like "Login," it can be used in hundreds of tests, saving time and reducing duplication. It is the beginning of plain-language testing (before Generative AI comes into play).
5. Library Architecture Testing Framework
Instead of writing the same test code over and over, you create a collection of reusable functions (or "Common Function Libraries") that can be called upon whenever needed. It is literally a modular-based testing framework and keyword-driven framework on steroid.
Let’s say you're testing a login feature. In a library architecture framework, you’d write a reusable function like login() that knows how to enter the username, password, and click the login button. Now, any time you need to test something involving login, you don’t have to write those steps again—you just call login() from your test script. This is the framework that promotes reusability and maintainability the most.
The idea is to highly modularize your test scripts. Each function or library does a specific job (like logging in, searching, or adding items to a cart), and your test cases simply mix and match these libraries to create complete workflows. This way, you don’t just save time, but if something changes in the login process, you only have to update it in one place, not everywhere you used it. Of course, the only downside is that you need the technical expertise to build and then maintain this type of framework.
6. Hybrid Test Automation Framework
A hybrid testing framework is like a “best of all worlds” approach in test automation. It combines the strengths of different testing frameworks, from data-driven, keyword-driven, to modular frameworks, to create a more flexible and powerful system. For example, you can:
1. Use data-driven testing to run the same test with different sets of data.
2. Leverage keyword-driven testing to let non-technical users define actions through simple keywords.
3. Apply the modular approach by breaking your application into smaller pieces and creating reusable test functions (like login, search, or navigation).
Katalon - The Hybrid Test Automation Framework
Enterprises often face the challenge of speeding up their testing processes without sacrificing the quality of their products. That’s where Katalon comes in—delivering the perfect solution by building on a powerful hybrid test automation framework. Katalon takes the guesswork out of automation and hands testing professionals a complete toolkit to test software and applications with ease.
Instead of struggling to build frameworks from scratch or piecing together open-source libraries, Katalon provides everything you need, packaged into one platform that’s ready to go. Let’s dive into what makes it a game-changer:
- Page-Object Model Design: Think of it as recycling for testing—reusing test objects, profiles, and cases across multiple tests to save time and avoid redundancy.
- Record-and-Playback Testing: Effortlessly capture every action taken on your System Under Test, view object properties, and generate automated scripts without lifting a finger.
- Keyword-Driven Testing: Turbocharge your test creation with a library packed full of built-in keywords, doubling your speed in designing steps and actions.
- Data-Driven Testing: Easily test your application with different datasets from CSV/Excel files or databases like Oracle SQL, SQL Server, or anything supported by JDBC drivers.
- AI-driven Testing: Be the pioneer and stay ahead of the curve. While enjoying all of the features above, you have StudioAssist by your side to Generate Code from plain language instructions and Explain Code for non-technical stakeholders.
And Katalon doesn’t stop there. It understands that every tester works differently, which is why it offers three test creation modes: No-code, Low-code, and Full-code.
- In No-code mode, simply use Record-and-Playback to capture your actions and turn them into automated test scripts, making repetitive tasks a breeze.
- Low-code mode gives you a library of ready-made Built-in Keywords, so you can customize actions—like clicking elements—without diving deep into code.
- For the tech-savvy, Full-code mode offers full control, letting you write your scripts from scratch when you need that extra flexibility.
Katalon’s seamless switch between these modes gives you complete flexibility, whether you prefer no-code simplicity or full-code control. With Katalon, the focus shifts from the “how” of test writing to the real objective—what needs to be tested. Not just that, Katalon also pioneers the AI testing wave. While crafting your tests, you
Katalon integrates all testing stages into one workspace, enabling seamless planning, test creation, organization into suites, execution across environments, and report generation.
