7 Latest Trends In Software Testing To Revolutionize 2022


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The exponential and unusual change in technology can affect how organizations develop, validate, deliver and operate the software. Hence, these organizations must consistently innovate and renew themselves by finding solutions for optimizing practices and tools to develop and deliver high-quality software quickly. Accounting for around 30% of the total project effort, software testing trends are essential for changes and improvements. Testing practices and tools should address the challenges of achieving quality at speed between the growing complexity of systems, environment, and data.

Below are some of the latest trends in software testing, and many of them have already developed over the past few years. You may have observed that agile and DevOps, test automation, artificial intelligence for testing and API test automation are some of the most prominent trends in 2021. Along with these trends, there are solutions like selenium, Katalon, TestComplete, and Kobiton to address the challenges in software testing.

Latest trends in software testing in 2022

Here are the latest trends in software testing :

Agile and DevOps

Organizations have embraced agile to respond to rapidly changing requirements and DevOps to respond to speed demands. DevOps involves practices, rules, processes, and tools that help integrate development and operation activities to reduce the time from development to operations. DevOps has grown to be a widely accepted solution for companies who look for ways to shorten the software life cycle from development to delivery and operation. The adoption of agile and DevOps helps teams develop and deliver quality software faster which is also known as quality of speed. It has gained very much interest over the past years and proceeds to strengthen in the coming years.

Test automation

For implementing DevOps practices effectively, software teams cannot ignore test automation as it is a crucial element of the DevOps process. Companies are required to find opportunities for replacing manual testing with automated testing. As test automation is supposed to be an important bottleneck of DevOps and organizations should automate most regression testing at a minimum.

Given the demand for DevOps and the fact that test automation is underutilized, with less than 20% of testing automated, there is a lot of room for increasing test automation in organizations. More venerable methods and tools should begin allowing better utilization of test automation in projects. Some existing popular tools such as Selenium, Katalon, and TestComplete develop with new features that will make automation much easier and more effective.

API and services test automation

Decoupling the consumer and server is a modern trend in designing both mobile and web applications. API and services are being used in more than one application or component. These changes need the teams to test API and services autonomously from the applications using them. When API and services are utilized across client applications, the testing team’s components are more powerful and efficient than testing the client. 

The main trend is that the requirement of API and services test automation remains to increase, perhaps outpacing that of the functionality used by the end-users on user interfaces. Owning the right processes, tools, and solutions for API automation tests is more essential than ever. Therefore it is worth the effort to know the best API testing tools for testing projects.

Artificial intelligence for testing

Implementing artificial intelligence and machine learning proposes to address the difficulties in software testing trends is not new in the software research communities as recent advancements in AI and ML with a large amount of data available provide new opportunities for applying artificial intelligence and machine learning in testing.

Nevertheless, the application of AI and ml in testing is still in the initial stages as organizations are finding ways to optimize the testing practices in AI and ML. The algorithms of AI and ml have been developed for generating better test cases, test scripts, test data, and reports. Auspicious models will help in making decisions about where what, and when to test. Smart analytics and visualization encourage teens to detect flaws for understanding test coverage in areas of high risk.

Mobile test automation

The trend of mobile app development is continuing to grow as mobile devices are becoming increasingly more capable. For fully supporting DevOps, mobile test automation should be a part of the DevOps tool change. Notwithstanding, the current use of mobile test automation is very low because of the lack of methods and tools. The trend of automated testing for mobile apps is continuing to increase. The requirement drives this trend for shortening time to market and more advanced methods and tools for mobile test automation. The integration between cloud-based mobile device labs like Kobiton and test automation tools like Katalon will bring mobile automation to the next level.

Test environment and data

The accelerated growth of the internet of things indicates more software systems will be operating in numerous environments. It sets a challenge for testing teams to ensure the right level of test coverage. Certainly, lack of a test environment and data is the top challenge while applying to tests in agile projects.

Organizations will see growth by offering and using cloud-based and containerized test environments. The application of artificial intelligence and machine learning for generating data and the growth of data projects are some solutions for the lack of test data.

Integration of tools and activities

It isn’t easy to use any testing tool that is not integrated with other tools for application lifecycle management, for top software teams should integrate the tools used for development phases and activities to get the multi-source data for applying AI/ML approaches effectively.

For instance, using artificial intelligence and machine learning for detecting where testing should be focused requires data from the testing phase and the requirements, design, and implementation phases. Simultaneously trends of increasing transformation towards DevOps, test automation, and AI/ML organizations will see testing tools that will allow integration with other tools and activities in ALM.


These were some of the current trends in software testing that should be watched out for in 2022 as we live in a world of unique exponential changes driven by technology and digital transformation. Organizations and individuals should remain aware of developments in the industry by keeping up with these trends. Keeping up with these trends will provide test professionals, organizations, and teams the opportunity to stay ahead of the curve.

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