6 test automation frameworks and how to pick one

This post is a guide on test automation frameworks. Of course, you already know that testing is vital for shipping high-quality software, but why are automation frameworks a topic worth your time?

Every change to a codebase could result in a regression (i.e., breaking something that worked up until that point). So, it’s crucial that the whole application is tested after every change, no matter how small that change appears to be.

Doing so manually is economically unviable, thus highlighting the importance of automated testing and test automation tools.

Let’s dig in.

A test automation framework is a structure to support and guide your test automation efforts.

What is a test automation framework?

A test automation framework is a structure to support and guide your test automation efforts. It helps you get started quickly while giving you a set of guidelines to follow.

There are no rules regarding frameworks; they can assume various shapes and sizes. However, a test automation framework typically comes with tried-and-true solutions to common test automation challenges, such as:

• a set of patterns, including coding standards, to organize and manage test scripts

• a well-defined workflow that QA professionals, testers, and developers can follow

• a shared vocabulary around testing and quality

Trying to conduct your tests manually would be too expensive and time-consuming. By using a test automation framework, you don’t have to start from scratch.

Fortunately, there are many intelligent people who have already done the hard work to solve testing problems in safe, efficient, and cost-effective ways.

They then packaged their solutions and published them, using a variety of programming languages, so that we can benefit from their work.

“Tests that run end-to-end through the UI are: brittle, expensive to write, and time consuming to run.”

Martin Fowler, in “Test Pyramid”

Benefits of using a test automation framework

Now that you know what a test automation framework is, we’ll explain the “why.”

The benefits we’ll cover here apply regardless of your choice of programming languages, development frameworks, or even development style. Java or Python, BDD or ATDD, web or mobile development—it’s all the same.

Here are some benefits you can expect:

1. Reduced time to market

With the use of a test automation framework, teams can test much faster than they would manually, which means shipping features much faster.

2. Increased quality

An automated suite of tests acts as a safety net, catching defects before they make it to production and improving quality and user experience.

3. Team efficiency

With a defined workflow and shared vocabulary, teams are much more efficient in their testing strategies.

4. Lower costs

An automation framework lowers costs by making the testing process faster and catching more defects earlier when they’re cheaper to fix.

5. Increased test coverage

With automation tools, you can have much more comprehensive tests than you would by testing only manually.

6. Fewer regressions

As a consequence of the previous item, the tests catch more bugs sooner, resulting in fewer regressions.

7. Improved onboarding

A well-defined testing strategy can make onboarding new hires easier if they already know the organization’s test automation framework.

Types of test automation frameworks

Remember earlier when we said that there aren’t any rules regarding test automation frameworks? We weren’t kidding. As you’ll see, there are many types of frameworks out there, and we’ll walk you through the main ones.

Linear automation framework allows users to create tests without having to write any code.

1. Linear automation framework

The linear automation framework is the simplest of test automation framework types. It allows users to create tests without having to write any code.

Instead, they use a process called “record and playback,” in which they interact with the application, performing the sequence of steps they want to verify. The framework records those steps and can then run tests by replaying them.

Here are the main advantages of this type of framework:

1. No need for coding skills

That way, developers can focus on creating new features, and people who don’t necessarily know how to code can create test scripts.

2. Easy and low-friction

A linear automation framework is the easiest and quickest way to start with test automation. The learning curve is shallow, and since the resulting steps are sequential, they’re easy to understand.

Now, here are the main disadvantages of linear automation frameworks:

1. Low reuse

You can’t typically reuse the test cases created with a linear framework. If you need the exact same step again, you’ll have to re-record it.

2. Low modularity

As a consequence of the previous step, there’s no way to achieve modularity using a linear framework.

3. High maintenance

Changes in the application’s UI tend to break these kinds of tests, resulting in high maintenance and low scalability.

With a modular-based testing framework, you break your applications (be they web applications, Android apps, or what have you) into many modules.

2. Modular-based testing framework

If many test cases start with the step “Go to the login page and sign in to the app,” then when the login page changes, all of those tests will break.

Wouldn’t it be nice to be able to “extract” the login step as an independent, reusable unit? That’s where modular testing frameworks come in handy.

With a modular-based testing framework, you break your applications (be they web applications, Android apps, or what have you) into many modules.

Then, you create test scripts or test cases targeting each module individually. Finally, you assemble all of them into a larger test script that orchestrates all of the smaller ones.

Here are the advantages of modular-based testing frameworks:

1. Higher reusability: With modular tests, you can easily reuse common steps.
2. Lower test maintenance: When a module in the application changes, only the tests targeting that module break.
3. More efficiency: Reusable steps mean testers don’t spend time recreating them, resulting in more efficiency and agility when creating test cases.
4. Higher scalability as a result of all of the above.
5. Higher test coverage as a result of more efficiency and reuse.

And now, for the disadvantages:

1. Need for coding skills: This depends on the actual framework, but it’s common.
2. Hardcoded test data: With modular testing, you often embed test data into the tests themselves, making it hard to reuse the same step with a different set of data.

3. Library architecture testing framework

You can think of the library architecture testing framework as a variation of the modular testing framework. Like its counterpart, it allows for reuse and modularity.

But instead of dividing the app up into modules, this approach consists of creating groups of testing scripts that target common tasks in the app and then collecting these groups into a library.

Test scripts can then access the library to use the saved scripts whenever needed.

The advantages of library architecture testing frameworks are virtually the same ones from the modular testing framework:

1. Higher modularity
2. Higher reusability
3. Lower test maintenance

The disadvantages are also similar:

1. Altered scripts: Hard-coded data can mean you need to alter the scripts to operate with different sets of data.
2. Complexity: This might increase due to the introduction of the library concept.

4. Data-driven framework

The main goal of this type of framework is to enable the use of the same test script against several possible data sets, where the data comes from external sources such as:

1. Excel spreadsheets
2. CSV files
3. XML files
4. SQL scripts that query database tables

Here are the main advantages of a data-driven framework:

1. Test coverage: By separating the test logic from the test data, you can quickly test a variety of scenarios just by varying the test data source.
2. Maintainability: Changes in the data don’t require editing the test scripts.

The main disadvantage of this model is the complexity that it creates. Typically, in order to enable this approach, you need an experienced software engineer who can write code that extracts and parses the test data from external files.

The keyword-driven approach consists of storing actions a user can perform on the application in a source separate from the test code itself

5. Keyword-driven framework

The keyword-driven framework is one of the most interesting options when it comes to reusability and modularity. It has several points in common with both the modular and library approaches.

The keyword-driven approach consists of storing actions a user can perform on the application in a source separate from the test code itself and using keywords to uniquely identify each action.

Test scripts can then use the keywords to call the actions, achieving great flexibility and reusability.

Here are the advantages of this approach:

1. Modularity: Actions identified by keywords are small and very focused, which means you can easily compose them together.
2. Reusability: Many different test scripts can use the same action/keyword.

And here are the disadvantages:

1. Higher learning curve: Keyword-based solutions might present a steeper learning curve than most other types of frameworks.
2. Higher barrier to entry: This is due to the effort needed to catalog all of the necessary keywords.

6. Hybrid testing framework

Each of the test automation framework types we’ve seen so far has its share of advantages and downsides.

Where one type excels, another one struggles, and vice versa. Wouldn’t it be great to have a type of framework that combined the strengths of all these other types?

That’s where the hybrid testing framework comes in handy. As its name suggests, it consists of combining other types of frameworks with the intention of creating a superior approach.

For instance, you can have a combination of the modular and data-driven approach, in which there are scripts that target specific modules of the application but obtain their test data from an Excel spreadsheet.

Or a linear test framework can help create small, reusable test steps that you can collect into a library.

In other words, the hybrid approach draws from all the other approaches, seeing what worked and what didn’t, and combining the best pieces of each into a better approach.

The hybrid approach draws from all the other approaches, seeing what worked and what didn’t, and combining the best pieces of each into a better approach.

Top tools and resources for test automation frameworks

We’ve covered a lot of ground in this post, and we’re not done yet. Having explained the differences between the types of test automation frameworks, it’s time to treat you to a high-level view of some available frameworks and tools.

1. Tricentis

Tricentis is an AI-powered test automation platform that helps teams automate end-to-end testing for their applications.

Additionally, Tricentis Tosca is able to generate robust test cases from plain English descriptions and user requirements, as well as being able to analyze and merge similar test cases, making your test suite more efficient.

It also produces self-healing tests, so your test suite becomes robust and doesn’t break every time the system under test changes.

With Tricentis Tosca, you can test across a wide range of enterprise technologies, which means you can leverage a single, very capable tool for all your test automation needs instead of having to rely on a number of disparate tools that often don’t play well together.

Last but not least, this platform comes with great test data management capabilities, so you can create and provision test data automatically, on demand, even if your scenarios are complex.

2. Robot Framework

Robot Framework is an open-source automation framework. Written in Python, you can use it for test automation following a keyword-driven approach.

You can extend Robot’s capabilities using libraries written in Java, Python, JavaScript, and other programming languages.

3. Selenium

Selenium is one of the most popular automation tools out there. Rather than just a testing framework, Selenium is a browser automation tool. You can use it to automate many tasks, but it’s usually for end-to-end testing.

Selenium comes in different editions, but the most flexible one is Selenium WebDriver. Through the use of Selenium WebDriver, it’s possible to use programming languages such as Java and JavaScript to drive browsers, creating automated flows.

An additional testing tool—such as JUnit for Java—is necessary for the creation of test cases that are self-validating and self-reporting.

4. OpenTest

According to its official site, “OpenTest is a free and open-source automation framework for web applications, mobile apps, and APIs.”

It operates by integrating with tools such as Selenium and Appium. OpenTest also supports keyword-driven and data-driven approaches.

5. Gauge

Gauge is yet another open-source test automation framework. It specifically targets automation testing. With Gauge, you write test cases using markdown, creating reusable test scenarios.

For the actual test execution, you wire up the test scenarios to the actual code you write using languages like Java, JavaScript, C#, and more. Gauge also supports data-driven testing.

How agentic AI is changing test automation frameworks

That AI is changing test automation is undeniable. But what do those changes look like in practice?

There are several pain points that test automation frameworks—and the teams using them—have had to contend with over the years.

One of them is the burden of test maintenance, which is caused by fragile tests that break easily when the application changes. This is primarily true for UI and/or end-to-end (E2E) testing frameworks that relied too much on DOM locators.

Another pain point is the amount of effort involved in achieving great test coverage. Doing so took time, often required handling multiple tools at once, and often required coding skills—at least when it came to code-based testing frameworks.

Test case reuse, or the lack of reuse, is also a big pain point. Sometimes the same scenarios are tested several times because the discoverability of existing test cases isn’t great.

But even if they’re easy to find, they might turn out to be hard or impossible to reuse. (And then, of course, when that part of the application changes and the tests break, many test cases will break as a consequence, due to the lack of reusability.)

Maybe the biggest pain of all is the cost of opportunity a team incurs when they waste talented people’s time and intelligence in repetitive tasks, instead of leveraging them for higher-level activities.

AI-powered test automation can and does address those pain points. First, agentic testing can generate self-healing tests that are immune to changing locators, resulting in more robust test suites.

Additionally, achieving more test coverage becomes easier with AI-powered test automation tools that can literally generate test cases out of plain English prompts and requirements from user stories and tickets.

Lack of reuse is addressed by the AI-powered capability of analyzing and merging test cases that are similar, resulting in less duplication and more efficiency.

Finally, the cost of opportunity decreases dramatically. When AI does the drudgery work, humans are free to engage in more rewarding activities within the team.

Use case: Jaguar Land Rover speeds up project deployment by 80% with the Tricentis platform and TCS

Problem

Jaguar Land Rover (JLR) relies on a complex SAP setup to manage the most important facets of their organization, including finance, manufacturing, and after-market services.

Their testing strategy was in dire need of modernization, since it relied on a toolset that was approaching end of life and lacked modern features. Because of that strategy, their full regression testing session before a major migration required at least 7 days.

Solution

JLR partnered with Tricentis to create a new testing strategy, based on three products: Tricentis Tosca for automated regression testing, Tricentis LiveCompare for change impact analysis, and Tricentis NeoLoad for performance testing.

The main priority was improving the slow and inefficient regression testing, which was done by rolling out Tosca Cloud.

Outcome

The main outcome was the reduction of regression testing time, from 7 days to 12 hours, enabling much quicker project deployments.

Another important result was a reduction of 15% in overall program delivery time. Finally, the project established an initial 40% test coverage, with 520 automated Tosca test cases being built during the initiative.

Source: https://www.tricentis.com/case-studies/jaguar-land-rover-sap-testing-tricentis

Final thoughts

This post was a deep dive into test automation frameworks. A test automation framework consists of a scaffold that can get you started quickly on your testing journey, and at the same time keep you grounded with a series of guidelines and conventions.

A test automation framework is a crucial part of the modern software development process.

Manual testing is no longer enough by itself. Automated test suites that can run continuously and avoid regressions are imperative in today’s highly competitive industry.

As you’ve seen, there are many types of testing frameworks, each with its own advantages and disadvantages. Frameworks that opt for a hybrid approach are clear winners here, as they bring together the best of several worlds.

Hopefully, by now, you not only know what test automation frameworks are and why they’re important, but are also convinced how AI is a game changer when it comes to these frameworks.

The impact of agentic testing goes way beyond simply making testing take less time—even though that by itself is nothing to sneeze at.

Furthermore, agentic frameworks efficiently address major test automation pain points that teams have been fighting for years or even decades, from test maintenance burden to lack of reusability.

An AI-powered solution like Tricentis Tosca can have a dramatic impact on how fast and efficiently your team delivers high-quality software. Give Tosca a try today.

This post was written by Carlos Schults. Carlos is a skilled software engineer and an accomplished technical writer for various clients. His passion is to get to the bottom (the original source) of things and captivate readers with approachable and informative technical content.