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22 December 2021

Quality Assurance

Quality Assurance trends for 2022

10 minutes reading

Quality Assurance trends for 2022

Today’s world is dominated by the still ongoing digital transformation of nearly every aspect of our lives. Many of us can’t imagine the world without electronic devices (which are continuously forming the IoT world) or online services. The world of IT keeps growing alongside the industries within it. Although nearly all of us are consumers of digital services, not everyone is aware of what’s behind the quality of the end product that we experience. 

The ‘insiders,’ namely the people working in the IT industry, are usually aware of the term Quality Assurance, yet many only associate it with testing. It’s definitely more than that. The concept is as old as the industry (or even older!), and it has been following different trends among the sub-genres of the Big Tech world over the years. Now, on the verge of 2022, many may be wondering how the QA world will evolve. Here are the most likely trends in Quality Assurance for 2022!

Is DevOps still enough? Or is it QAOps time now? 

The DevOps approach is well known and widely used across various businesses. Is it still enough to cover a teams’ needs? Probably yes, but that does not mean there is no room to seek out something different, and better.

Recently, different variations of Ops have shown up. DevSecOps, MLOps, and DataOps are domain-specific approaches, but all combine the same principles of bringing teams closer together to improve overall delivery time without loss of quality while reducing costs. However, one player wants to mark its presence in the Ops world—QAOps

QAOps appeared in 2019, but 2022 could be the year of QAOps. Now the systems are more complex, and the whole concept has become more mature. How does QAOps work? This concept aims to bring QA engineers closer to development and operations by triggering cycles of testing, and maintaining and developing solutions. All of which are elements of the CI/CD cycle. QAOps will help establish testing activities earlier in the software development life cycle, making them more efficient.
Overall, the process is split into stages, as follows:

  • planning,
  • development of tests,
  • automation,
  • triggering,
  • releasing,
  • reporting.

However, you can choose from different test types—it is worth knowing the differences between them and why they are important for the SDLC. 

Test automation as part of the cycle

Continuous testing is an integrated part of the CI/CD process. CI/CD helps organizations improve and optimize their businesses by applying regular cycles of integration and frequent releases. The testing cycle is faster and begins earlier compared to more traditional approaches. Low quality code and inconsistent structure are immediately detected in every run, so failure detection and repair rates are high in the early stages, which in turn reduces the risk of technological debt.  

TestOps helps with ensuring and strengthening automated testing cycles. Why TestOps, and how is it different from DevOps? TestOps focuses on automation to centralize and streamline software development planning, monitoring, and testing. TestOps informs processes and operations to implement the necessary tests, and monitor if they can be executed. DevOps has a slightly different aim—providing a proper environment to run the tests.

The CI/CD process has a lot more to offer. Here, you can check out how CI/CD can benefit your business

How can you support test automation to make it effective and effortless? With wisely chosen tools. Which ones might be worth your attention in 2022? 

  • LambdaTest—a tool for desktop and web applications that enables manual and automated cross-browser testing. 
  • QMetry Automation Studio (QAS)—scalable test automation for web, mobile, and web services for Agile and DevOps teams. 
  • Katalon Studio—helps in transforming automated testing into continuous testing. This solution can be integrated with tools like  JIRA, Git, or Slack (and more).
  • Worksoft—is dedicated to enterprise applications with a code-free, Agile-plus-DevOps continuous automation platform onboard. 
  • Avo Assure—is a code-free, test automation platform to perform end-to-end tests for applications, web, mobile, desktop, and mainframes. 

IoT testing 

The internet of things continues to grow, expanding greatly over the past few years. And, you can be sure, this growth will not stop. In this industry, integration feels like a primary goal.  More and more complex devices and systems need adjustment in terms of the selection of tests that can match current requirements. From this we get IoT testing. This approach focuses on checking that every protocol, operating system, hardware, and software implementation in various devices is synchronized and ready for delivery. However, there is something more. IoT testing also cares about keeping device security levels high by eliminating possible bugs and vulnerabilities and making them more robust in the face of possible hacker attacks. 

Artificial intelligence in testing 

Artificial intelligence is increasingly visible in many fields, and so it is in quality assurance. AI is often presented as the perfect solution for every problem, but is that true? One has to give credit to the power of AI in image analysis and unit/API/UI test automation. However, it is worth keeping in mind that this field of study is still far from reaching perfection. Currently, AI can resolve only specific problems, such as increasing test coverage levels in unit tests.

AI testing automation has potential for some companies to limit unnecessary costs in the supervision of software solutions and products. 

Besides cost reduction, AI in automation testing provides benefits like eliminating lone errors, which are more likely to escape the tester's eye.

How can you use the potential of AI test automation in 2022? 

  • Visual testing to check UI design quality.
  • Spidering—AI collects the data based on continuous website visits, so it can compare it later on for potential downgrades. It still needs a human touch in the end though.   
  • For now, AI cannot provide full test coverage automatically. The current test production process is based on training on a specific dataset,  with the test cases being generated later, with checking required by the tester. However, AI systems could take some of the testing load, reducing a lot of the repetitive work.

There are many reasons why this tech is predicted to be worth 310 billion dollars by 2026, and those mentioned above are only a few of them.

Performance engineering 

Performance engineering helps companies combine high software performance levels with UX design, security, business value, and rapid responses to market needs. All of these, with added market requirements, can be demanding and time-consuming. Here comes performance engineering. It helps ease this situation by providing customer-centric testing in the software development life cycle as early as possible. Performance engineering enables the development team to reduce and eliminate bugs and bottlenecks at the early stages of the development process. Performance engineering can be an early, big picture substitute for traditional performance testing, which focuses on the performance of finished apps or MVPs.

Where will we notice performance engineering’s influence in 2022? 

  • DevOps—DevOps takes advantage of performance engineering by using more responsive systems, creating performance engineering toolsets, meaning everything takes less time and carries less risk. 
  • Cloud-native tools—Blue-green deployment is a technique where a copy of the production environment is created in a cluster (the "green" line). The traffic is rerouted between green and blue lines until the next deployment. This technique enables the making of a production server copy for testing, with the duplicate being safe and separate. 
  • SaaS-based tools—Software as a service enables the tester to create and run tests on a large (cloud) scale with easy tool configuration that can be saved in the cloud for later use.


In order to achieve product-market fit, companies’ attention should be closely focused on Quality Assurance and QA experts in the coming years. Technological innovations and new techniques will ensure that the software will not only be much safer, it will be developed more quickly. 2022 promises to be very productive for Quality Assurance experts. Let’s see what changes it will bring!


Piotr Gilert

Project Manager