With the help of AI, digital twins can be applied in various environments to provide diagnostics and more efficient software development.
It’s only recently that digital twin technology has been implemented in software testing – and it’s offering some significant advantages.
The simplest definition of a digital twin is a virtual representation of an object or a system that uses real world data to create simulations, typically with the help of artificial intelligence and machine learning.
Compared to just a few years ago, software testing today is significantly more complicated. Developers face pressure to constantly release software in a complex ecosystem. That’s why digital twins are becoming more widely used in software. An example of this trend is Eggplant Software, which is a technology-agnostic test automation platform that aims to address some of the challenges developers face.
Eggplant, which was acquired by Keysight in 2020, allows companies to test any application, system, or device using a digital twin. To understand why digital twins are needed in software testing, I recently spoke with Jonathon Wright, Eggplant’s Chief Technology Evangelist. Highlights of the ZKast interview, done in conjunction with eWEEK eSPEAKS, are below.
- Software is not as easily measurable as hardware and it involves additional complexity. Software is continuously evolving, so it must be released faster. There are different types of testing, where millions of permutations can be simulated. Furthermore, implementing digital twins in software testing is a fairly novel concept and a recent offering in the Eggplant/Keysight portfolio.
- Eggplant provides AI-powered test automation and digital twin modeling using low-code tools. Through test automation, developers can predict – with accuracy – how software will behave under a variety of conditions. With the help of AI, digital twins can be applied in different environments. For example, instead of testing an autonomous car, the technology can be used to simulate automotive radar.
- AI-based systems require a large training set. The more data is fed into the systems – both good and bad – the more intelligent they become. Eggplant uses its proprietary AI algorithms for bug hunting and exploratory testing to determine whether software is ready to go live. It tests for software quality and how it’s increasing or decreasing over time, among other factors.
- During COVID-19, Eggplant worked with the Massachusetts Institute of Technology to create digital twin scenarios for a contact tracing program. They partnered with Apple and Google to collect exposure notifications from mobile phones using Bluetooth proximity. The scenarios took five hours to generate. More than 10,000 different permutations and scenarios were tested before actual adoption of Google’s and Apple’s exposure notifications took place.
- Digital twins can be used for variety of simulations, including creating a digital world that’s parallel to the physical world known as a metaverse. Eggplant is collaborating with companies like Microsoft on mixed reality (MR) use cases involving eye tracking, which emulates the movement of the eyes. As more devices move into MR, the metaverse will become a prominent technology that enables people to interact with each other in a virtual environment.
- We’re seeing the consumerization of MR, augmented reality (AR), and virtual reality (VR). The hardware and software is tested through the use of controllers, hand movements, cameras, and body tracking – all of which create a digital twin. It’s not just about testing the headset, but every single part of the experience.
- In the future, 6G technology (sixth generation wireless) will be a game-changer, with the network serving as a critical component for edge computing. Today, people struggle with having a flawless digital experience. That’s where digital twins, 6G, edge computing, and mobility are all coming together to break down the digital barriers and enable people to solve big problems.
