Abhay Chaturvedi
When automation is so adored by everyone, why not take a look at what 2021 has in store for it? This article brings to 10 predictions for automation for the year 2021. Go through them and be prepared to excel in whatever comes your way.
The increasing number of dev teams adopting automation indicates its dominance and spread. The App Developer Magazine’s report shows the two-year growth of test automation to be 85%. The organization’s not routing for automation may fall behind in the long run as classic testing schedules will delay the deployment along with doing a lousy bug-catching job.
Selenium, the openly accessible test automation framework, has come up with Selenium 4. With loads of added functionalities and a shift to WebSocket protocol, this version revamps the whole grid architecture. This will make automating unit tests way simpler and thus, the expectations for even better releases and updates are going to increase. Selenium 4 is blended with Opentelemetry.
This bestows the power of observability to Selenium 4 making it capable of implementing tracing and event logs.
Having a free-standing QA team delays the whole deployment process. Instead, development methodologies where the Dev Teams tests too and this creates a whole integrated production environment. Together the Dev Team and the QA teams will build a coherent system that will handle the bugs along the development process.
Java had its share of stardom for a long while. However, the changing times have found the successors of Java too. Now it’s time for Python and JavaScript. The GitHub Octoverse survey ranks Python on number 2 in the list of popular coding languages of 2020. As for JavaScript, it needs no evidence to say it is topping the charts.
The dependence on technology is increasing day by day. Hence making accessibility testing all the more important. Accessibility testing is the practice of analyzing whether the software under consideration is easily usable by people with visual impairment, hearing disabilities, and other physical or cognitive conditions. The upcoming times will see enterprises more eagerly investing in accessibility testing for developing an all-around user experience and enhancing brand recognition.
This mature automation trend is all about the mingling of automation platforms and vendors. It is based on the belief that every vendor has its own forte. Some platforms or vendors may be accustomed to handling low to medium complexity use cases, while others might be more suitable for the hyper-complex ones. That’s why it is best to resort to a multi-platform methodology wherein any vendor is allotted a particular use case depending upon its specialization.
Smart, AI-powered tech maximizes test coverage as it accelerates the whole testing procedure, systemises test setup detects test repetition, and highlights the code that’s been mistakenly left unscanned. Welcoming AI into your QA stratagem will upgrade the bug discovering algorithms. In addition, AI-driven automation will also replace plenty of manual testing tasks, resulting in better QA resource sharing.
Coined in 2019, the term hyperautomation refers to the process of utilising Artificial Intelligence (AI), Machine Learning (ML), and Robotic Process Automation (RPA), to free humans from repetitive and low-value tasks. Hyperautomation involves a high-powered assemblage of digital technologies to employ automation at speed. This “intelligent process automation” doesn’t depend on just one single tool, thus unlocking maximum potential.
Cloud-hosted, web and mobile app automated testing are not only going to stay the course in 2021 but there’s going to be a major rise in cloud spending as well. According to Gartner, the world’s leading research and advisory company, we can see a whopping 18% increment in cloud investment by organizations.
The more we rely on the cloud, the more it is going to grow which will, in turn, enable the agile culture. Utilizing the cloud flawlessly requires cloud based testing tools.
During the course of unit testing, including visual verification upgrades the user interface. Rather than just attending to unit tests when they alert about code failures, incorporating visual AI with conventional unit testing, work towards verifying visual components and simulations, validating the source code, and determining page checks. Experienced developers can themselves perceive and ponder upon the code while fabricating it.
