Automated regression tests verify that changes made to the codebase do not affect the software's functionality.
Automated regression testing saves value time and resources, work with other automation methodologies, and streamlines complex processes.
While the regression tests can be run using automation tools, many teams are still manually selecting test cases to run bottlenecks quality and introduces risks.
Machine learning helps teams only run the tests that really matter in each situation – the ones that are most likely to uncover bugs and give you actionable insights on what to fix.
Have you ever experienced a domino effect within your software? It starts with your application being a smooth-running, well-oiled machine – all of the components are meshing, and your customers are happy with it. And then, you decide to release a new feature, and everything changes.
Things start breaking. Your team is panicking, the customers are upset, and your management is ready to pull their hair out!
How can something like this happen, with one change causing regression across your whole app? Well, because an application is so complex and its parts are so profoundly interconnected, a single harmful component or feature has the potential to wreak havoc on your entire software ecosystem. Regression testing prevents this type of chaos from happening in the first place.
Regression tests verify that changes made to the codebase do not affect the software's functionality. Regression testing should be run after any of the following changes happen:
New feature or function
Update to pre-existing feature's requirement
Software configuration change
Codebase alteration for fixing defects
Source code optimization for performance enhancement
When regression testing becomes a regular habit in your software development lifecycle, you’ll detect bugs earlier, making them much easier to fix than after they’ve traveled downstream. And it means fewer incidents later down the road after the software is released.
But as helpful as regression tests are, they can be difficult to implement manually. Many roadblocks will arise when you rely solely on your developers to facilitate them. So, it’s important to implement automated regression testing into your software development life cycle.
Automating parts of your regression testing process, instead of performing them manually, can save your team time and resources, fit better into established CI/CD pipelines, and simplify your operation.
Developers are already pressed for time as it is! You might like the concept of running all tests (including regression ones) early and often. In theory, it’s a great way to nurture a DevOps culture and shared responsibility. But if you aren’t making it easy for developers, they might tend to circumvent testing because it feels like a waste of time! In fact, tests can be a sore spot for many developers, as they can take extra hours or even days to run. And the more time your development team spends waiting around on testing, the less time they’ll have to be creative and innovative, which is likely why they wanted to become a developer in the first place!
Commonly-seen methodologies like Continuous Integration, Continuous Delivery, and Continuous Deployment focus on automating to give developers more time for creative work. Regression testing should follow this same mindset, mainly because it’s a complex process that has the potential to waste a lot of your developers’ time. Automating all types of testing, including regression tests, can make your end-to-end software development lifecycle run far more smoothly and quickly.
There’s no way around it: regression testing is complicated. It tends to evolve a lot. When your software stack changes drastically, the test suite also has to change. And the more significant and complex your software is, the more extensive and complex your regression test suite has to be.
After all, more features mean more possible paths for a user to take, which means more test cases are required to ensure that the software works well. Automated testing can expedite this otherwise-complicated process. Instead of manually testing out every possible case, your testers will only need to triage issues and run them through an automatic process.
Automated regression testing makes it easier for developers to test every change or new feature before it gets pushed into production. The key to making this process work is repetition, repetition, repetition.
This approach helps ensure that every test case is validated and that everything will run as planned – especially if the organization releases many new features regularly. Regression testing includes a few steps. Typically, automation comes into the picture halfway through the process.
Identify the exact places that changed and pinpoint any existing, interconnected components that the changes could impact. Next, choose which test cases are needed based on the specific modifications. Test case selection can vary based on the extent of the changes.
Unfortunately, this often manual stage can take a long time, as it requires testers to understand each test thoroughly and strategically decide which ones should run and which do not need to be part of the cycle. (At Launchable, we've been helping teams predict the right tests to run to speed up this phase.)
Next, your team should estimate how long it will take to run the correct test cases for the specific situation. They will need to consider test case generation and test case evaluation, along with other factors.
After time estimations are complete, the cases need to be prioritized based on how major they are and how many additional components they will affect. Each case’s business impact and functionality can help determine priority, among other considerations.
Your selected test cases now run through an automation tool. From there, it’s simple: you just run the tests in the prioritized order! If a case fails, prioritize it higher, so it runs again, and your team can properly troubleshoot the issue.
There’s sometimes a tendency to think regression testing and retesting are the same. After all, they are both repetitive types of tests and aim to catch bugs early on in the SDLC. But, they have a few significant differences.
Regression testing is a routine part of the testing process – it must run every time a change happens to the software. It is performed on a cadence and happens after the feature has passed other test types, such as unit and functional testing.
Re-testing, on the other hand, happens on an as-needed basis. When another type of testing fails (i.e., unit, functional, or regression), re-testing comes into the picture to dig deeper into why it failed and how to fix it.
To make your automated regression testing as streamlined and functional as possible, here are a few best practices that can help you and your team.
Include a mix of new regression tests and routine, tried-and-true tests in your suite. This way, you can double-check old features as well as new ones. But you have to ensure these older tests aren’t experiencing entropy. Even some of your most trusty tests can degrade and become flaky and unreliable, requiring you to retire or fix them.
Focus on creating test cases that center around the user interface’s features and capabilities. After all, there are no stricter critics than the humans who will be using your platform. And they will be testing the limits and functionality of the application simply by using it. Be sure to test it before they do!
You don’t have to write a regression testing suite from scratch each time you execute one. Use frameworks and patterns to run test cases. But as we mentioned, check these tests regularly to ensure they are still functioning well. These frameworks should also be in line with developer and testers’ requirements and tailored to your organization’s unique team needs.
As we’ve seen, there’s a lot of groundwork that has to happen before the regression testing automation tools can take over the regression testing process. Before a tool like Selenium or Serenity can take over and work its magic, there are prerequisites.
Most importantly, your team needs to pick and choose the right tests to plug into the automated testing solution. Selecting the proper tests to do manually is tedious. And unfortunately, many of today’s regression test tools only cover the second half of the process, executing the tests.
They don’t help when it comes to identifying which test cases are the right ones in each situation and which aren’t working anymore and need to be retired.
Because of this, testers must put in the time and effort to look through these regression test suites and identify which ones are relevant – all manually! It’s a lot of work, especially for organizations that regularly push new features and changes into production.
We saw how tricky it can be to pick the right tests for each situation. That’s why we developed Predictive Test Selection technology!
Instead of relying on testers and developers to choose the right tests for each situation, our ML platform does it for you. It takes your history of code changes and test results, then automatically runs the tests with the highest probability of failing.
So, you only run the tests that really matter in each situation – the ones that are most likely to uncover bugs and give you actionable insights on what to fix.
Plus, our Test Suite Insights automatically identify which regression tests seem to be degrading over time so you can avoid using them. All in all, it means happier, more productive developers and a better end product for your customers.
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