Top Software testing trends coming in 2022

021 was an interesting year for software testing. The skyrocketing of DevOps and Agile methodologies saw testers adjusting to more adaptable development frameworks. And, with many continuing to work remotely, their solutions had to be unique as well as Agile.

There’s no indication of this innovation delaying down, either. We anticipate a continued focus on speed, quality, and flexibility. Let’s take a glance at the top four software testing trends coming in 2022.

1. CI/CD pipeline testing

Continuous integration, continuous delivery—sounds amazing, right?

Well, it won’t function without continuous testing. If you’re considering employing a CI/CD pipeline for your software development in 2022, you require to build automation testing into the framework from the very start.

The first step is to build unit tests for the software’s characteristics that you can automate through the UI later on. It’s important that the scripts for these tests are as detailed as possible, to detect defects that could occur down the line.

When you have combined the coding at the continuous integration stage, you can then perform automated functional tests to identify any problems, which you’ll be able to resolve as they appear. So, workloads will be more manageable and your project more streamlined.

It’s the best method to carry out performance and regression tests, too. Here, you can weed out any bugs that have crept into the main branch. So, at the continuous delivery stage, you can apply updates to the finished product almost immediately. The result? Software of a higher standard as well as a faster rate of production. 

2. TCoE

A Testing Center of Excellence TCoE isn’t a physical space, but instead a framework that standardizes methods and best practices for software testing.

Instead of having QA spread across silos, a TCoE concentrates the protocols and tools required to maintain the quality of testing throughout each and every project. It also centralizes skills, with the testing team arriving from a variety of roles within the organization. Together, they deliver a more holistic, unified procedure to testing.

But, it’s not just the testing team that assures that the Testing Center is absolutely Excellent. For a TCoE to work, it requires support from management across your organization. Of course, it helps that the framework enhances project visibility, which in turn lets management assess progress more easily.

If you operate in a large or complex organization, a TCoE could help simplify your software development. That said, assure your management is on board first—they can stimulate separate teams to track the TCoE’s recommended protocols so that projects operate more smoothly.

3. Codeless test automation

Will your upcoming project have frequent release cycles? As you well know, this implies writing more scripts for testing. This will enhance the time-to-market of your software, which is counterintuitive to the methodology of any good DevOps team.

Codeless Test Automation allows the writing of test scripts without any code, letting you to:

• Execute continuous testing more quickly.
• Build test environments easily.
• Integrate tracking tools.
• Scale and modify tests for new scenarios.

And, maybe most importantly, codeless tests don’t require a coder to run them. So, your testers can concentrate on creating the right tests and assuring the quality of your software.

There can be examples, however, where you require customized code—like when you have a complicated user interface, for instance. If your codeless tests don’t cover all the bases, QA engineers can step in and alter them accordingly.

4. AI and ML

While DevOps and Agile make software development faster and more flexible, the quicker releases and higher expectations on delivery time need more innovative testing.

Artificial intelligence (AI) and machine learning (ML) have the promise to make testing smarter. They employ reasoning to solve problems, helping teams catch and fix issues more quickly.

By incorporating AI and ML into your software testing, you will:

• Decrease the time to delivery of each project.
• Increase cost-efficiency by saving time (and therefore money) on manual effort.
• Decrease human error with automated code and log file scanning.

What’s more, when you employ AI and ML in software testing, they learn from their past iterations to create future improvements. So, as good as the advantages sound now, they just keep getting better.

Also Read: AI is Revolutionizing Software Test Automation

Bring your software testing up to date

As you know, software development has become more Agile. While this is excellent for improved collaboration and faster time-to-delivery, it also puts higher demands on software testing.

Luckily, the area of software testing is no stranger to innovation. We’ve delivered you with an overview of four of the top trends you can expect to listen about this year, but there’s a way to ensure the quality of your development project. To take your testing to the next level, contact the experts.

At TestUnity, we strive for the highest quality in every project, and our professional QA specialists are ready to ensure it. Contact us if you’re looking for a dedicated team to enhance your product’s quality.

TestUnity

Testunity is a SaaS-based technology platform driven by a vast community of testers & QAs spread around the world, powered by technology & testing experts to create the dedicated testing hub. Which is capable of providing almost all kind of testing services for almost all the platforms exists in software word.