5 Software Testing Trends you Need to Look Out For in 2022.
In the world of software testing, change remains one of a constant thing. The software testing industry has already been through several changes over the years and there will still be more to come. This evolution will force software testers who want to be on top of their game to know the current and future state of this industry.
Not to also forget the relentless pressure on the development team to provide faster solutions without compromising the quality of the product. And the very important role software testing does in every stage of the development process. All these are the reasons why software testers should get acquainted with new trends that will shape the future of software testing.
As a software tester, leveraging new trends can help you up to your testing game and be ahead of your competitors. This article will help you understand some of the best software testing trends in 2022.
- Artificial Intelligence-Based Testing
Artificial Intelligence is the latest technology that is gaining ground across all industries and software development is not left out of this mix. Artificial intelligence-based testing is a software testing method that employs the use of Artificial Intelligence and Machine Learning algorithms to effectively test a software product. This form of testing is aimed with the goal to make the testing process smarter and more efficient. It will be able to predict application behaviour, build advanced testing scenarios and offer smart analytics of the test process.
The use of Artificial Intelligence in software testing is possible because AI algorithms can fully imitate human intelligence, while ML allows computers to learn without any form of human intervention. This way, unique and detailed algorithms can be developed to access data, learn from the extracted data and then make decisions and predictions that can be effectively used in software testing.
It has also been seen that businesses get many benefits from AI-based testing as it will enable faster and successive testing, complete automation without any human intervention, and also enables quicker ROI.
Some other benefits of using AI-based testing in software development:
- Enhanced Accuracy
Chances of human-caused errors are high in manual testing and although Automation testing helps to correct most of these errors, a more efficient result can be gotten with the introduction of AI in automation testing. The birth of Artificial intelligence in Automation testing helps in handling repetitive tasks more accurately and improves the accuracy of tests across-board.
- Visible Confirmation
With the ability of pattern and image recognition, visual bugs can be easily detected by performing visual testing on applications. This will help to ensure that all the visual elements can function effectively.
- Easy Bug Identification
Testing software with artificial intelligence also leads to fast bug identification, which in turn helps to reduce the defects and makes the product bug-free and reliable for customers or end-users.
- Products are released faster
The use of AI in software testing also ensures that products are released faster because AI-driven tests support continuous testing. This way, businesses go early to market.
- Testing at the Speed of Agile and DevOps
DevOps is known to be a practice that combines an organization’s strategies, techniques, tools, and teams to deliver new forms into production as quickly as possible. It is also famous for its association across departments while agile plays an important role in software development and testing. The combination of these two makes deployment and teamwork a lot better than ever before.
Agile and DevOps in software testing promise to increase performance. Leveraging this methodology in software development also promises faster results in software testing. Agile and DevOps aims at practices to close the gap of development through delivery activities in fulfilment of the business activities through a computerized continuous development, testing and delivery
This is why businesses are also trying to implement the DevOps principles into their software development process. The goal of DevOps is to unify software development and software operation. Automation and monitoring will be carried out at all steps of integration, software testing, deployment, and infrastructure management.
Testing software at DevOps speed also comes with absolutely no compromise on the quality. It is also noteworthy that the main aspect of everything related to DevOps uses continuity of each process in the application development cycle to get constant feedback.
- Cloud-Based Testing
Cloud testing is used to assess web applications and websites for performance, security, and reliability. As the name indicates, this form of testing is performed on a third-party cloud computing environment that houses the required infrastructure to perform tests. The various types of cloud testing processes allow you to test software and hardware without the usual constraints of a limited budget, geographical issues, multiple test cases, costs running high per test, etc.
This form of testing is also convenient for businesses to host solutions on the cloud due to the increasing storage capacity on the cloud. Cloud testing is used for simulating test environments over the cloud. And some of the top reasons why you should consider this testing form is:
- Cloud-based testing can be done virtually which helps in getting rid of plan delays that are environment-related. It eliminates the need to share an environment with team members and ensures that work is done rapidly and efficiently.
- This form of testing improves collaboration, accommodates a diverse team and easy monitoring of each other’s work.
- Cloud-based testing saves cost. This is an economically and technically viable option than setting up an in-house testing infrastructure. The total cost of ownership of cloud-based testing automation tools is significantly less than the in-house infrastructure. Most cloud-based testing providers use a ‘pay-as-you-go’ model, which means that you save costs when the tools are not in-use or plan to scale down testing activity due to business reasons.
- The hardware & software resources that provide access to cloud-based testing automation tools are accessible 24/7 (barring aside any scheduled downtime for maintenance on cloud testing provider’s front).
This improves the overall collaboration between geographically dispersed development & test teams as resources are available whenever they want.
- IoT Testing
The Internet of Things which has been on the rise over the past few years is now taking the world by storm. It gained its popularity through new technological advancements happening in the world. IoT is primarily based on machine learning and automation and is a mix of cloud computing, machine-to-machine interaction, advanced data processing, real-time analytics, and many more. This is the reason why software testers should integrate this trend into theirs.
The first step to take before you begin testing with IOTs is to test IoT devices to ensure that they work flawlessly and do not have any security risks. These devices need to meet specific standards before they are deployed. This form of testing is also used to ensure and safeguard the identity and integrity of an organization.
- Big Data Testing
Testing used to be all about verifying the quality of the software products being developed, but it has now moved way further and the scope has grown to include big data testing as well. Big Data Testing is a testing process of a big data application in order to ensure that all the functionalities of a big data application work as expected. It is a collection of large datasets that cannot be processed using traditional computing techniques.
Big data is, by nature, huge and highly complex. It is impossible to test these datasets manually and they require advanced analytical tools and testing frameworks that are still in the growth phase.
Today, big data has started to become more popular and in need than it has ever been in the past. Big data is getting used in almost every sector in the world. Mining this data, both structured and unstructured, requires end-to-end testing.
Big data testing will continue to be used by software testers. This is because businesses want to utilise data in developing practical market strategies and improving their targeting. Thus, the demand for big data testing will increase in 2022 and beyond. The goal of big data testing is to make sure that the big data system runs smoothly and error-free while maintaining performance and security. Performance and functional testing are the major keys to this form of testing.
The importance of software testing can’t be over-emphasized. Some of the importance are listed below:
- Saves Money
- Provides Security
- Defines the Quality of the Product
- Increases the odds of customer satisfaction
- Enhances the development process of the product
- Makes it easy while adding new features