Let’s find you the right test automation framework to build your web application efficiently.
We’ve done the hard work for you—exploring the top options and breaking down their pros and cons—so you can build the right automated testing framework for your project needs.
Whether you need a framework for specific tests or a hybrid solution that supports your entire development process, you'll find it here.
As a whole, seven types of test automation frameworks stand out. These include module-based, linear (record and replay), behavior-driven development (BDD), keyword-driven, library architecture, data-driven, and hybrid frameworks.
Each has unique strengths and weaknesses, but the right choice will help you deploy application updates swiftly, efficiently, and with fewer bugs.
Automated testing frameworks are sets of guidelines, tools, and practices. The design simplifies the process of creating and executing automated tests and collecting thorough reports of your test results.
It provides a structured approach to testing by defining standards for test definition, test data management, result validation, and reporting.
Well-designed test automation frameworks bring the following key benefits:
To figure out how to build a framework for automation testing for your web application, you need to first know what common automated testing frameworks are out there. This will transform your testing workflows.
Instead of stumbling your way through bugs and errors as you deploy code, you'll be able to spot and fix problems before they reach your users.
Also known as the record-and-playback framework, this approach is straightforward and ideal for:
However, it lacks proper scalability and is difficult to maintain for complex scenarios.
Linear automation is a simplistic method to validate and check applications automatically. It works in a ‘linear’ manner, guiding the testing process step-by-step. Tests execute in a predetermined order, one action after another.
Testers create the test using ‘record and playback’. This involves operating a user interface and recording each action. Then, they can replay these recorded steps to automatically run the tests. It’s a helpful way to check the performance of visual and interactive elements in an application—think buttons, forms, and menus.
It’s not great for large-scale testing and isn’t reusable or scalable. The framework is best applied to testing smaller apps thanks to its straightforward approach and non-complex setup.
Best for: Prototyping and testing simple web applications, UI components, and desktop applications with minimal variations in input and output.
This framework divides test scripts into smaller, reusable modules.
Why it matters:
The framework requires initial effort to design modules but pays off in long-term maintenance.
Module-based testing is an approach that uses abstract models to generate test cases. The focus is on the requirements of system behavior rather than directly testing the code.
In Layman's terms, this means instead of looking directly at the code, you create a simplified version (the model) to capture how the application responds and behaves in different workflows, inputs, outputs, and states.
The model is created to reflect what the software is required to do. From this model, you can run test cases to see if the software meets these requirements. You can focus on how your software should operate instead of getting bogged down by large code bases.
Best for: Complex systems like enterprise applications, e-commerce platforms, and systems requiring frequent updates or component reuse.
The data-driven test automation framework separates test logic from test data, enabling:
It is particularly useful for scenarios requiring extensive input variations.
Data-driven testing (DDT) uses data stored in an external source like Excel, CSV, or other databases to run the same test scripts with different data sets. You can use the same testing logic and execute it multiple times with several sets of data.
Best for: Data-oriented applications such as Inventory and Resource Planning (IRP) systems, Customer Relationship Management (CRM) software, Enterprise Resource Planning (ERP) systems, and financial applications. These systems often involve large datasets requiring extensive input validation and processing.
Keyword-driven testing (also known as table-driven frameworks) is a methodology that uses keywords to run actions.
Why it matters:
Maintenance may become challenging as the keyword library grows.
The methodology uses predefined keywords to run a set of actions. Each keyword includes one or more sets of parameters that the test must pass. This approach enables the separation of test development and test design.
Let’s imagine a simple example:
You have a list of commands or keywords such as ‘click,’ ‘enter text,’ or ‘verify.’ This allows you to use predefined words to create tests rather than complicated code.
It doesn’t require you to be a coding genius to create the tests. Although, the initial setup can be complicated and time-consuming.
Best for: Applications with frequent UI changes, legacy systems, and projects involving non-technical testers who need to create tests without programming knowledge.
Hybrid frameworks combine the key features of multiple frameworks mentioned above.
Why it matters:
These frameworks are suitable for large, diverse testing needs.
For example, a hybrid testing framework could operate using both keyword-driven and data-driven methodologies. This makes it easy for non-technical team members to understand tests, while the application is evaluated against variable data sets.
Best for: Large-scale enterprise systems, applications requiring both functional and regression testing, and projects with multiple testing needs, including APIs, databases, and UI testing.
BDD frameworks focus on collaboration between developers, testers, and stakeholders by using plain language syntax.
Why it matters:
Popular tools include Cucumber and SpecFlow.
Behavior-driven development is a vital link between technical and non-technical team members during software development. It's a method that aligns with business goals while maintaining the integrity of the code.
Within BBD testing, testers use a special kind of language; it is simple and clear to ensure everyone working on the project can understand it.
The language generally follows this format:
Given: Describes the content
When: Describes the action
Then: Describes the outcome
And: Add more information
Here’s a simple example:
Scenario: A user creates a LinkedIn account
Given: The user is on the LinkedIn registration page
When: The user enters all the required registration information
And: The user initiates the account creation
Then: A LinkedIn account is created
Best for: Applications where business requirements and user behavior are closely tied, such as customer-facing applications, e-commerce platforms, and banking systems requiring clear communication and documentation.
This framework helps you create reusable functions grouped into libraries. Library architecture testing is similar to modular frameworks but with added benefits.
Why it matters:
It requires careful planning to design a robust library structure.
Like the module framework, it breaks down the application into smaller sections. Rather than dividing the software into separate scripts, it groups scripts by task similarity. So, we break down the testing based on common goals or actions.
The grouped tasks become functions saved in a library to be used whenever needed. This makes the testing process organized and more efficient, with common tasks stored in a centralized base for use across different tests. It also improves the reusability of the testing framework, although it can be more time-consuming and skill-intensive to create.
Best for: Applications requiring high scalability, shared functions, and backend processing, including middleware systems, API testing, and service-oriented architecture (SOA) implementations.
There’s a wide range of test automation frameworks for your development team to rely on when building your application. Depending on your requirements and application size, some will be better suited than others in spotting bugs, vulnerabilities, and errors in your code.
At Y Soft, we’ve spent over a decade developing AIVA, a robot testing system to help businesses build better ways of working through simplification and automation.
Today, AIVA addresses new norms (where complex, responsive, and rapidly evolving web applications reign supreme). It is an innovative test automation framework that merges the simplicity and speed of linear automation with the robustness of hybrid frameworks.
📖 Read on → Rethink Your Application Testing with an Inverted Test Pyramid
Moving beyond outdated approaches that rely on web page code (DOM), which often undermines ROI, AIVA employs a purely visual approach. It allows you to define tests using an intuitive record-and-replay tool, enhanced by advanced AI models and semantic analysis to ensure stability and easy maintenance.
Intrigued? Sign up for the AIVA waitlist today and experience smarter, faster, and more reliable test automation.