Emerging Trends & Technologies in Software Testing

Image source: https://www.ml-labs.ie/ethics-in-practice-a-priority-for-ai/

This is where proper software testing comes into play.

This is where new technologies of software testing come to play & these emerging technologies can reshape the future of software testing.

Let’s look into the overview of the below-emerging trends & technologies in software testing.

Artificial Intelligence (AI) and Machine Learning (ML)

Image source : https://etfdb.com/themes/artificial-intelligence-etfs/

The outcomes of AI & ML testing of testers can be used to refine the product by developers & it will result in making a smarter and more productive software for the end-user.

Big Data Testing

Image source: https://www.msystechnologies.com/blog/8-steps-to-foolproof-your-big-data-testing-cycle/

Gartner defines Big Data as, “Big data is high-volume, high-velocity and/or high-variety information assets that demand cost-effective, innovative forms of information processing that enable enhanced insight, decision making, and process automation”.

According to Evans Data Corporation, “19.2% of big data app developers say quality of data is the biggest problem they consistently face”.

Insights of big data testing can be used to improve the quality of products and services, hence the organizations can deliver a better customer experience.

Robotic Process Automation (RPA)

Image source: https://www.imt-soft.com/Blogs/All/Robotic-Process-Automation---RPA-what-is-it-

Throughout the software testing activities, we can use RPA to optimize the repetitive testing activities to automate large and complex data sets through an easy-to-use interface. RPA has the capability to perform all types of testing that use automation testing tools, thereby eliminating the need to write test scripts.

RPA enables work to go on 24/7 without any break and with precision. This, in return, guarantees a superior customer experience.

QAOps or DevTestOps

Image source: https://www.softwaretestingmaterial.com/qaops/

And the combination of these two methodologies, i.e. QA and DevOps brings a new practice called QAOps or DevTestOps.

QAOps is a useful set of practices/framework that automates the processes among software development, operations and QA to deliver a software faster and more reliably by identifying bugs at an earlier stages.

Internet of Thing (IoT)

Source: https://performancelabus.com/iot-testing-importance/

Any physical object can be transformed into an IoT device if it can be connected to the internet to be controlled or communicate information.

A typical IoT platform has four basic components: application, sensors, backend database (data center), and network communication.
Each component of the IoT needs different testing procedures. Testers need to consider these elements to formulate a comprehensive test strategy.

As of 2021, there are 21.7 billion active connected devices in the world today, out of which more than 11.7 billion (54 percent) are IoT devices. This means that there are more IoT devices in the world than there are non-IoT devices.





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