Top 7 Latest Trends In Software Testing For 2022


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In this era of digitalization, the importance of the latest trends in software testing has expanded. An understanding of what is software testing is something that is important before we begin. Technological innovations and developments modify the functioning of the organizations and their development processes.

Thus, organizations need to refine their innovative techniques and find a solution to optimize their practices to develop quality software quickly. So, you should be aware of the latest software testing trends in the industry and why software testing is important. Let us have a glance at these trends.

Top 7 Latest Trend In Software Testing

Below are the latest trends in software testing in 2022:

Test automation

Test automation is a crucial part of different attributes that help us to create reliable software. These attributes entail agile development, CI/CD implementation, DevOps and continuous testing, which help us in facilitating code deployments. With the aid of test automation, we can reduce the dependency on manual testing.

According to a report, a growth from 12.6 billion in 2019 to 28.8 billion in 2024 is expected in the test automation market. A compound annual growth rate of 18% is expected during this period. The growth of the test automation market owes its importance to the usage of Agile and DevOps.

For example, many organizations use selenium test automation to procure their objectives. Selenium test automation is an economical method as compared to local test infrastructure and helps to enhance the test coverage.

Test automation has been used for more than a decade and will continue to do so in 2020. The usage of different technologies like AI, ML, etc. helps in the creation of test automation tools. Such technologies facilitate the process of DOM analysis and page object identification. Let us look at Software testing trends 2020.

Machine learning and artificial intelligence

The augmented usage of artificial intelligence shows that it is unequivocally, an important part of technology. A whisk of artificial intelligence and machine learning will help to make automation testing more efficient. It will bolster the process of test automation and cross-browser testing. Thus, artificial intelligence and machine learning will serve as a lubricant in facilitating the processes of the automation testing industry in 2020.

A report shows that the artificial intelligence and machine learning market is expected to touch the $190.6 billion mark by 2025. The same data for the year 2018 was 21.5 billion dollars. Hence, the compound annual growth rate of this industry is 36.6% in this period.

Due to the heightened importance of this industry, the QA tools should be revamped to align them with the AI/ML technologies. This will help to bolster the UI/ GUI testing of web applications and websites. Apart from the shift in the mindset, a shift in the skill set should be observed in the testing industry, to evolve the various tools and techniques of QA testing.

Multi-device testing

In this era of digitalization, people use different smartphones and IoT devices. Such usage has made multi-device testing more important than ever before. In today’s world, users can procure information from various devices like smartphones, IoT, connected devices, smart speakers, or other digital wearables.

So, in 2020, the automation testing teams will need to test umpteen devices, which can include Smart home appliances as well. Selenium automation testing will become prominent because multi-device testing is one of the software testing trends of 2020.

Internet of Things (IoT) Test automation

Due to the development of 5G and other innovative technologies, the Internet of Things (IoT) is gaining more importance. Different industries like the government sector, consumer electronics manufacturing industry and embedded systems make use of the Internet of Things.

The data generated with the help of the Internet of Things can help businesses to conduct critical analyses and run smoothly. IoT application testing has umpteen benefits like improving the test coverage, averting the defects in the early stages of development and reducing the time to promote the products.

Progressive web apps testing

The introduction of progressive web apps has facilitated the performing of functions in mobile phones. With the aid of PWA or progressive web apps, you do not need to install any app on your mobile phone. Instead, the web application makes use of the modern web facilities and helps to proffer a web-like experience.

A lot of researches show that with the help of PWA, companies like Twitter can facilitate new user conversions and better user engagement. But, since the Web apps bank on the features of the web browsers, it is crucial to ensure efficient functioning of the Web app on the older browsers. The online cross-browser testing cloud, like Lambda Test, can help you to test your PWA in more than 2000 real browsers on mobile or desktop. A report shows that the PWA is likely to replace approximately 50% of the consumer-facing apps in 2020. To test the attributes of the PWAs, the mobile testing tools and selenium automation testing frameworks should also be enriched.

Mobile test automation

Mobile test automation needs to be a part of DevOps Toolchains. But due to the lack of effective techniques and equipment, the utilization of mobile test automation is significantly low. To facilitate effective mobile automation testing, it is necessary to integrate the cloud-based mobile device labs with the test automation tools.

More complex tools and procedures for mobile test automation and shortening the time to market will help in the procedure of automated testing. With the emergence of new mobile apps, the process of mobile app development continues to grow.

Test environments and data the latest trends in software testing

The emergence of the Internet of Things (IoT) facilitates the operation of software systems in different environments. The testing teams need to assure the right level of test coverage. Hence, the appropriate test environments and data is the top challenge during any agile project. 

The problem of the lack of test data can be resolved by integrating the application of AI/ML in generating the test data. Additionally, the usage of cloud-based and containerized test environments will enhance in 2020. Research shows that software testing methodologies account for approximately 30% of the project efforts. Hence, the testing techniques and equipment of an organization should aim at creating quality software while keeping in mind the complex data and dynamic environment.

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