4 software testing trends coming in 2022
2021 was an interesting year for software testing. The skyrocketing of DevOps and Agile methodologies saw testers adapting to more flexible development frameworks. And, with many continuing to work remotely, their solutions had to be innovative as well as Agile.
There's no sign of this innovation slowing down, either. We predict a continued focus on speed, quality, and flexibility. Let's take a look at the top four software testing trends coming in 2022.
1. CI/CD pipeline testing
Continuous integration, continuous delivery—sounds great, right?
Well, it won't work without continuous testing. If you're considering using a CI/CD pipeline for your software development in 2022, you need to build automation testing into the framework from the very beginning.
The first step is to create unit tests for the software's features that you can automate through the UI later on. It's essential that the scripts for these tests are as thorough as possible, to catch defects that could emerge down the line.
When you have merged the coding at the continuous integration stage, you can then perform automated functional tests to identify any issues, which you'll be able to fix as they arise. So, workloads will be more manageable and your project more streamlined.
It's best practice 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 instantly.
The result? Software of a higher standard as well as a faster rate of production.
A Testing Center of Excellence TCoE isn't a physical space, but rather a framework that standardizes processes and best practices for software testing.
Instead of having QA dispersed across silos, a TCoE centralizes the protocols and tools needed to maintain the quality of testing throughout each and every project. It also centralizes skills, with the testing team coming from a variety of roles within the organization. Together, they provide a more holistic, unified approach to testing.
But, it's not just the testing team that ensures that the Testing Center is indeed Excellent. For a TCoE to work, it needs support from management across your organization. Of course, it helps that the framework improves project visibility, which in turn allows management to assess progress more easily.
If you work in a large or complex organization, a TCoE could help simplify your software development. That said, ensure your management is on board first—they can encourage separate teams to follow the TCoE's recommended protocols so that projects run more smoothly.
3. Codeless test automation
Will your upcoming project have frequent release cycles? As you well know, this means writing more scripts for testing. This will increase the time-to-market of your software, which is counterintuitive to the methodology of any good DevOps team.
Codeless Test Automation enables the writing of test scripts without any code, allowing you to:
- Implement continuous testing more quickly.
- Create test environments easily.
- Integrate tracking tools.
- Scale and alter tests for new scenarios.
And, maybe most importantly, codeless tests don't need a coder to run them. So, your testers can focus on creating the right tests and ensuring the quality of your software.
There can be instances, however, where you need customized code—like when you have a complicated user interface, for example. If your codeless tests don't cover all the bases, QA engineers can step in and adjust 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 demand more innovative testing.
Artificial intelligence (AI) and machine learning (ML) hold the promise to make testing smarter. They use reasoning to solve problems, helping teams detect and resolve issues more quickly.
By integrating AI and ML into your software testing, you will:
- Reduce the time-to-delivery of each project.
- Increase cost-efficiency by saving time (and therefore money) on manual effort.
- Reduce human error with automated code and log file scanning.
What's more, when you use AI and ML in software testing, they learn from their past iterations to make future improvements. So, as good as the benefits sound now, they just keep getting better.
Bring your software testing up to date
As you know, software development has become more Agile. While this is great for improved collaboration and faster time-to-delivery, it also places higher demands on software testing.
Luckily, the field of software testing is no stranger to innovation. We've provided you with an overview of four of the top trends you can expect to hear about this year, but there's a way to guarantee the quality of your development project. To take your testing to the next level, contact the experts.