The software industry goes through a lot of research and modified methodologies that keep the software quality top-notch for the end-user. 2014 saw the trend of mobile app testing as they were becoming a multi-billion dollar business all over the world. 2015 saw the trend of scriptless testing and IoT focussed methodologies.
Again, this was shaped by the market trends and the increasing importance of both of this software. In 2016, Google made it clear that since mobile traffic is more than all else, mobile-friendly websites will be prioritised when a user searches on mobile. So the trend of mobile web testing came into the picture. The story has continued since then for each year.
With the end of 2021, we are here after careful analysis of the market trend and the latest prioritised technologies that we believe will be important in the future.
These technologies have started to pick up as trends in software testing and have the most potential of growing at a significant rate in 2022. Let’s see these trends and why they are important this year.
A couple of years back a new term QAOps started picking up in the software industry. In 2021 it went a bit more into consideration and implementation. Today, QAOps is projected to seep more into the software development life cycle and will play an important role in 2022.
QAOps is a term derived by combining the two processes – the DevOps and QA into one. QA is the final checkpoint that ensures that the software we are delivering is of high quality.
DevOps aims at developing software and combining IT operations with it. When we fuse QA into the DevOps process the newly integrated process is called QAOps. With QAOps we are incorporating the testing process into DevOps and let QA engineers work with developers while the software is in development.
QAOps is projected to create a new software process model and increase the overall quality of the process.
AI and Machine learning-based testing
Another software testing trend to watch out for in 2022 is artificial intelligence(AI) and machine learning(ML). AI and ML are no new words today. From mobile applications to chatbots to predictive systems, AI is growing its foot in every direction. This growth, as analyzed by GrandViewResearch has turned into a $62.3 billion industry in 2021 growing at a rate of 40%.
All this implementation of artificial intelligence has been primarily into the development field. AI is used to predict and present but not to verify the predicted data etc. In 2021, AI began being implemented in the testing department and we believe that it will be as crucial to testing as it has been to the development world.
So, what could be good use cases in software testing that can attract AI and shed off the tester’s load? Even though business logic is something that is quite far from AI, generating test cases can be a reasonable use case to bet on. Similarly, AI can help in generating test case data that is specific to the module with varying fields and validations.
AI can also be used in analyzing any leaks in testing, defaults, and predicting the test coverage even before running the test cases to save time. If you have something in mind, feel free to comment down below.
AI is coming to the deeper scenarios of software testing but one tool has been quick to pick up the trend and implement it in their DNA. Testsigma, a completely cloud-based test automation tool uses AI technology in software testing to save time, costs and smoothen out the learning curve of the testers.
With AI technology, the tester can write the test cases in the English language that can be translated into programming language by the tool. Testsigma also comes with self-healing technologies that can detect changes in the user interface and change the test script corresponding to that element automatically. Such artificial intelligence practices can improve the quality of processes and save time.
Take the 30 day free trial of Testsigma and see it for yourself.
IoT automation testing
IoT (Internet of things) devices have been on an increase for a long time now. In 2021, more than 23 billion IoT devices were active and connected to the internet. This number is projected to be around 50 billion by 2030.
Metova survey describes how people look forward to IoT devices and how 85% of them are interested to buy one for their daily use. With such growth comes a lot of responsibility for IoT developers, manufacturers, and testers.
IoT is used in sensitive data such as your video footages via CCTVs or your personal health data etc. Such sensitive data needs to be protected well before propagating it through the internet channels.
Hence, a special focus remains on the automation testing of the IoT devices using appropriate data. For example, if we are testing a voice assistant, a lot of human-like sentences need to be constructed. With such a boom in the IoT industry, in 2022, it will definitely be one thing to look forward to.
Robotic process automation (RPA)
Robotic process automation has already been involved in the software testing process and we believe that it will continue to be in the trend for 2022 with an increased acceptance.
Research and market survey projects the revenue from RPA to be around 3.4 billion US dollars by 2027. With 28.2% year-on-year growth, RPA is always preferred to be the first choice for performing the automation of mundane tasks.
RPA, also called robotic process automation, is a process of automating tasks that are repetitive and require no manual intervention as such. RPA takes down the actions of the tester for the first time to make note of what has to be done.
Using artificial intelligence and machine learning, RPA then executes multiple scenarios using the same actions on the screen. Since it is automatic, it saves time and costs for the company.
From the above definition, you might think it resembles test automation since it also talks about performing repetitive tasks as does test automation. It is a genuine confusion and therefore we have written a dedicated post on how RPA differs from test automation with various use cases and examples.
On October 13, 2021, Selenium released their fourth major version of the web driver tool which had been long waited for. It had been five long years since Selenium 3 debuted in the market and in these five years, the technology has gone through a major evolution.
This made the testers suggest and request improved functionalities of the software and since open-source works on people’s demands, Selenium 4 brought out commendable changes to itself.
The highlights of Selenium 4 were:
- Relative locators are now sorted by proximity.
- Selenium grid 4 has been introduced which is an optimized version of its predecessors.
- Testers can now work in multiple windows and tabs using the single test flow.
- Network interceptor is introduced for ChromeDevTools for the responses related to the network requests.
- Debugging is improved and optimized with better logging facilities.
Selenium 4 has been widely appreciated and accepted as an enhanced version of the previous versions. Needless to say, it will be one of the testing trends that we should watch out for in 2022 as companies take advantage of it.
In-sprint test automation
In-sprint test automation is a software testing methodology that picked up as a trend in 2021 and will still continue to do so in 2022. Agile methodology forces organizations to work speedily and release new versions quickly.
As a result, one sprint consists of 2 – 4 weeks of time after which there is no time left for testing the software. So testers are often found testing a previous version which has a major drawback. If your version is released with just regression and DDT methods, a few of the bugs might seep into the production which can cost even 100 times more.
In-sprint test automation changes this process by allowing the testers to work in the same sprint step by step. So a testing team need not wait till the complete development is over and can start during the development process. This keeps the quality of software on the better side while allowing testers to test the same version to be in sync.
What’s your personal trend?
Each year and each passing day sees advancement in various technologies. Be it development, management, or testing, we research, test, and improve in all the segments. With this, we welcome some of the top things that we believe will shine through this year and will continue to be a deeper part of our testing lives.
But this post highlights all the software testing trends that we believe (through research obviously) will shine all along the 2022 year. However, being a tester yourself, I am sure you must be aware and be using some technology that could not make it to the list here. If such is the case, we welcome all the comments with technologies and use cases to help everyone in the community learn more trends.