Automated Regression Testing

Regression testing is the testing of software to discover any errors whenever a change to the system has been made.

Extended reading: What is regression testing?

When developers create a new feature for an application, the new code can affect existing functionality. In some cases it can make the system more vulnerable to hackers, or bugs that can cause system downtime. 

By regression testing, you test the user interface (UI) of the software to ensure that it is working as it should, and that the system as a whole has not been impacted by the new feature. In theory, this should happen every time a new feature is released.   

Regression testing can be automated, and it can also be done manually. Generally, the larger the project under test, the more likely regression testing is automated. Because regression testing suites grow over time and take a long time to complete manually, QA teams are choosing to automate their regression suites.  

The difference between regression testing and retesting

Regression testing and retesting are often misunderstood. The two concepts are similar, but have different purposes. 

Regression testing finds bugs that are unexpected. Retesting is designed to find bug you do expect to find. 

You can find a more detailed explainer on the differences between retesting and regression testing in this article. 

We’ll give more insight into why regression testing is more effective when it is automated, below.

As we unpacked in the section above, as systems grow larger and pressure to deliver faster is growing, more teams are making the transition from purely manual to a mix of manual and automated testing. This helps them become more agile in their development practices.

And regression testing is a perfect candidate for test automation. It is a repetitive task with processes that are predictable.

By automating regression testing, computer-based tools find vulnerabilities in software before a release. As it is not carried out by a human, the tests can be run at any time. This gives more time for exploratory testing, and provides better test coverage. 

Related reading: 5 reasons why you should automate regression testing

By automating regression tests, you’re giving the opportunity for testers to focus on what matters most – the user experience.

Related reading: Automated regression testing - why and how?

Automated testing does not mean that manual testing disappears altogether. Rather, you automate the repetitive manual tests that you would usually test as part of your regression suite. 

So how do you find that perfect balance? It first requires that you understand what automation is capable of.

Automation can only do what you direct it to, nothing more. While automation is great at re-running repetitive tasks, it isn’t intelligent like a human being.

It isn’t capable of making informed decisions, or finding problems you haven’t set automated tests for.

Automated tests find the known unknowns, manual tests find the unknown unknowns.

That is why exploratory testing is so crucial. By leaving automation to monitor the repetitive tests you’ve built it to monitor, testers can think outside of the box and look for bugs outside the pre-defined tests. 

How to identify test for automated regression testing

Regression testing can seem like a mammoth. How do you find the perfect balance of tests? How do you decide what to add to your regression suite? 

The answer is simple. Is the test boring or repetitive, or likely to be susceptible to human error? Is the test very complex or high risk? Any of these scenarios provide the perfect opportunity and justification for automation.

Related reading: How to automate regression testing

Related reading: How frequently should you run your regression tests?

By automating a regression suite, there are a number of benefits to the team, the project, and the company. 

• Save resources. Rather than spending time on repetitive tasks like manual testing, robots do the work for you. This ultimately creates a more productive workforce that can improve the software being produced, giving your customers a better experience. It’s important to note here that automation does not replace jobs, it empowers teams to work on value-creating tasks. 
• Immediate feedback. By automating regression testing, you will be better set up for continuous testing. You’ll be able to test earlier in the release pipeline, and test more frequently before a release.
• 24/7 testing. With robots doing the work, you can set up regression tests at any point. You can run your tests at night, or at intervals, to catch bugs before they reach end-users. 
• Scalable. With the right automation tool and strategy, you can speed up testing, and remove unnecessary manual testing. If done right, you don’t need to spend additional resources, and you can extend your test coverage beyond your normal testing routes.
• Lowers maintenance. When you add more features to your software, you also have to add new tests. Over time, your regression suite will become too big to run manually. 

Without the right automation tool for testing, maintenance can also become a burden. For this reason, a tool that gives testers the ability to easily adjust and maintain automation without having to change or rewrite code is a must. 

The problem is, most automation tools require coding. This leads to a slew of challenges that can make or break development projects.

Regression testing is one of those tasks that can quickly spiral out of control. It’s not that it is a difficult task. Rather, it’s repetitive and it’s time-consuming. 

Done manually, it’s understandable that errors are made. One small step missed can lead to disastrous consequences. So businesses choose to adopt test automation to carry the repetitive regression tests. 

In an agile set-up, on a unit level, developers can write tests as needed and run them quickly. They make up the majority of tests in a regression testing suite. As you move to the top of the pyramid where you test the UI, it should make up the smallest portion of tests. However, this doesn’t always happen. Because the UI is fragile, slow and expensive to maintain, it often requires more testing. 

And a business can choose a test automation tool with the best of intentions at the start, believing that the technical capabilities of the tool will meet the business expectations. But this is rarely the case. 

This is because, when testing the UI of software, whether it is on the web or desktop, is a task mostly carried out by business-users. It is only unit testing that requires a developer like person, and when you move up the agile testing pyramid, it is not the code being tested. Rather, it is the user interface that is tested, and the connection to other software (API testing). 

The test automation paradox

This creates a paradox. Those who do regression tests aren’t developers, but in order to automate regression testing, they are required to develop automation using code. Now, that’s not to say there are no testers with coding skills. There are, but they are incredibly expensive, and they will still encounter problems along the way.

The workload of maintaining code based test cases holds back teams from realizing the full potential of automation. If you are automating the regression testing of a large system, it is likely that it is highly customized.

And when you couple this with the pressure of getting products to market as fast as possible while minimizing risks like customer churn and product down-time, the maintenance burden has to be resolved. To meet the goal of faster releases and a positive customer experience, test automation has to be scalable. 

What are businesses then doing to ensure that their testing is both maintainable and scalable? They are choosing tools that lower the bar to entry in terms of building automation.

In addition to continuously selling the benefits of your automation tool to your managers to gain their continued support, you have to measure the ROI of an automation tool before you purchase it. Estimating the return of investment (ROI) of a project should always happen at the start of a project. However, the way you approach this should be well considered.

For example, some companies may try to justify an investment into automation by comparing manual testing and automated testing and the time it takes to run both. While this information is useful, it won’t provide the full picture. 

There are key points to factor into your ROI calculation. These include: 

• The time it takes to implement tests
• The maintenance of tests 
• The time it takes to analyze failed tests

If you combine these factors, the time spent on automation can quickly outweigh the benefit of adopting it in the first place. 

Of course, you should also consider the coverage, time to market, and software quality with the introduction of test automation. However, these points are much harder to quantify. They can be predicted, but they can only be realized after test automation has been implemented. 

There are, however, solutions that set you up for better test coverage, a faster time to market, and better quality software for an improved customer experience. We’ll talk about this in the next section.

Related reading: How to make regression testing automation cost effective

There are many available options for automating regression testing. But here’s the truth. Every business has a unique set of circumstances that dictate the requirements they have, so there is no one “best” solution. Rather, it is about looking for the “right” solution for your team, your business, and your customers. 

Related reading: Evaluating regression testing tools - a checklist

That being said, there are guiding principles that will aid you in your search. These are listed briefly below: 

• Easy-to-use, enabling testers to set up test cases from day one
• Visual, providing you with a good overview of your regression test suite
• Collaborative, allowing your team to work together on the software
• Code-free, enabling all testers to set up and understand test cases
• Adaptable, working across all web, mobile and desktop apps and technologies
• Trackable, capturing why test cases fail in recorded videos and logs
• Supported, getting you the help you need when you need it

With the guiding principles in mind, how can a codeless test automation tool help your business have a leg up from competitors and maintain a focus on quality assurance?

Codeless test automation helps you become agile. Instead of getting held up by implementing automation, maintaining it, and spending too much time trying to figure out why a test failed, the process is simplified. 

You don’t need coding experience, meaning non-developers can contribute towards building automation from day one. 

It’s visual, so you can easily identify why a test has failed. This makes it simpler for anyone on a QA team to set up, execute, and analyze tests. At the same time, it eliminates dependencies on developers, as it limits the time needed to set up tests. 

As long as you have the necessary knowledge of the system under test, as business users and QA managers have, you can build a test case.

Maintenance is kept to an absolute minimum so you don’t have to spend hours combing through lines of code, updating it with every change of an element ID or new feature release.

And lastly, it keeps repetitive work to a minimum, freeing up testers to work on what they do best, exploratory testing. 

Leapwork is a one-of-a-kind automation tool that enables business users and QA managers to build and maintain tests. No coding skills needed. 

Our Automation Platform can test across desktop, web, greenscreen and mobile, making end-to-end testing of the UI much simpler. We do this by offering dedicated recorders for desktop technologies, and Selenium-based web automation. 

Related reading: Comparing regression testing tools - Leapwork vs. Selenium

So no matter the underlying technologies you’re using, you can use the same visual approach to automate across your IT landscape. 

What you can achieve with Leapwork

• Faster time to market
• Better quality, lower risk
• Maximum efficiency
• Scalable automation