Testing Requirements Have Changed
Almost everything about software has changed — how it’s architected, developed, and produced, what it does, and what users want from it. Yet product teams still use software testing approaches from 15+ years ago that don’t come close to meeting customer expectations.
Modern testing has to be about technology metrics and business metrics, such as user satisfaction, conversion, adoption, and retention. But existing software test automation solutions focus on the code — not how the user experiences the application. So, you can’t test UX or modern technologies and architectures. And in many cases, you don’t even own the code because you’ve built your app using cloud-based microservices.
Modern testing needs to handle complex architectures (including the edge of IoT), and ensure complex apps can scale and perform appropriately across platforms, devices, mobile front ends, and cloud or on-premises back ends.
It’s true that we’ve automated a critical aspect of test automation — test execution. But until we automate the whole process, we can’t keep up with the frequent release cycles associated with DevOps, continuous delivery, or agile. And we can’t cover the entire user journey to create an amazing digital experience.
Clearly, we need a new approach. One that puts the user at the center of software testing.
Testing Needs to Change
Nearly 1 in 4 people who download an app only use it once, and 51 percent of users don’t download any apps in a month. But at the same time, 86 percent of test teams say they’re meeting their test objectives. Why? Because organizations have made testing more about code-compliance checking rather than about delighting users. This results in low user adoption, engagement, and revenue, and creates a UX gap.
At the same time, trends within the software industry are making testing more challenging. DevOps, mobile and IoT, digital, and consumerization are massively increasing the scope of testing but shrinking time to delivery. Teams can’t keep up with the pace of DevOps, or deliver what the business wants, even with the budget they’ve been asking for — creating a productivity gap in both time to market and efficiency.
The internet of things (IoT), the proliferation and fragmentation of devices and technology, dynamic apps, and rich UIs are driving the need for test automation. But existing software testing solutions just can’t automate these new technologies that keep popping up, creating an automation gap.
Transform Testing From a Compliance Function to a Profit Center
At Eggplant, we’ve developed a new approach to software testing that empowers teams to quickly and continuously create amazing, user-centric digital experiences. We call it Digital Automation Intelligence, and it uses artificial intelligence, machine learning, and analytics to predict business and user impacts across different interfaces, platforms, and devices. So you can:
- Transform testing from a compliance function to a profit center.
- Shrink time to market by testing new versions, fast.
- Accelerate productivity by scaling test coverage without blowing your budget.
- Keep up with the pace and evolution of DevOps.
Intelligently Automate Your End-To-End Testing
Our approach involves five key elements.
1. Test through the eyes of the user.
The Eggplant Digital Automation Intelligence Suite can test any device or technology, and interact with apps just like a user would. Analyzing the actual screen — not the code. Using intelligent image and text recognition to test application logic and dynamic, modern UIs, and do real, end-to-end testing. This is the only way to understand the true UX. Citi is doing this in mobile banking. Walmart’s doing it in retail. It’s happening in the C2 Futures Lab at Northrop Grumman. And Konami is doing it in gaming.
2. Test all aspects of the UX.
Our solutions test functionality, performance, and usability — all critical product attributes associated with the UX. And by testing that experience through the eyes of the user, you have a much simpler, more intuitive way to test. Which means that even non-technical people — from manual testers to business analysts to product and user experts — can be effective testers.
3. Expand automation beyond test execution with artificial intelligence, machine learning, and analytics.
The Eggplant Digital Automation Intelligence Suite uses artificial intelligence and machine learning to auto-generate test cases and optimize test execution to find bugs and provide broad coverage of the UX. Analytics automate results analysis, root-cause analysis, and user impact to help teams boost productivity and time to market, and keep pace with DevOps.
4. Use predictive analytics to report quality status in terms of the UX.
Rather than reporting quality status purely in terms of metrics pass rate and defect density, our solutions reveal specifics on application quality in user terms. For example, shipping now will likely result in a 4 out of 5 app rating, users will see a 20-percent reduction in app freezes, page load times will move from 3 seconds to 2.4 seconds, and consumer conversion will increase by 15 percent. This data approach enables cross-functional collaboration and bridges the gap between product owners and QA.
5. Take a coherent approach to monitoring and testing.
Monitoring UX in production is especially important in a modern DevOps environment where products quickly move between the lab and production, and back again. Think about it this way: your traditional monitoring approach says that your app’s response time is two seconds but your users say it’s eight seconds. By emulating real network conditions, you can get a true, end-to-end view of performance in production.
Meet the Digital Automation Intelligence Suite — Integrated Solutions That Power Our User-Centric Approach
Eggplant Functional and Eggplant Performance enable testers to quickly and easily validate the full user experience. Including functional, performance, and usability testing — any app on any platform.
Eggplant AI automates the automation. It auto-generates test cases to massively increase testing productivity, speed, and coverage. It uses artificial intelligence and deep learning to literally hunt defects — predicting where quality issues are most likely to pop up, and correlating data to quickly identify and resolve them.
Eggplant Manager orchestrates test execution, initiated by Jenkins or another CI tool, via its REST API. Eggplant Manager determines which tests to run, communicates with Eggplant Automation Cloud to reserve the necessary test devices, connects with Eggplant Network — which emulates the appropriate network conditions — and executes the tests using Eggplant AI, Eggplant Functional, and Eggplant Performance.
The Eggplant Digital Automation Intelligence Suite fully integrates with JIRA, Microsoft TFS, HP ALM, CA Agile Central (Rally), and others.