AI-augmented software testing accelerates digital transformation
Is digital transformation top of mind at your company? You’re not alone. New methods of developing software are driving fast change across all industries.
With today’s pressure on enterprises to digitally transform, continuously delivering quality software has never been more critical. Internal and external digital products, which are built by millions of lines of code, are vital for success.
“AI-augmented and ML-powered software engineering is changing the way software is being created, tested and operated," according to the 2023 Gartner® Hype Cycle™ for Software Engineering.
However, every enterprise application is built differently. User workflows, business-critical rules, and third-party systems are just some of the many customizations that make enterprise applications unique and testing their software challenging.
The increasing demand for faster software deployment is making the testing process more complex and harder to scale. Continuously delivering new features and functionalities merely adds to these complications. Particularly when these enhancements must be implemented and tested to keep pace with changing market forces, competitor activity, and customer expectations.
Trying to do this manually is labor-intensive, costly, and it dramatically slows down release cycles.
What is AI-Augmented Software Testing?
AI-augmented testing comprises AI- and machine learning (ML)-based technologies and practices to make software testing activities more independent from human intervention.
According to Gartner, AI-augmented testing “continuously improves testing outcomes by learning from the data collected from performed activities. It extends traditional test automation beyond the automated execution of test cases to include fully automated planning, creation, maintenance and analysis of tests."
Software test automation has become a business-critical asset in our digital-first world, as companies strive to deliver unbeatable user experiences at DevOps speed. According to Gartner, “AI-augmented testing enables the automation of a broad set of testing activities related to requirement quality, design quality, code quality, release quality and operational resilience. This increases the degree of autonomy of those activities.”
Benefits of Investing in AI-Augmented Software Testing Tools:
- AI can identify patterns and defects that a human tester would not be able to find.
- Testers can use AI to generate test data, which will help them cover more ground in their testing efforts.
- With the help of AI, testers can get feedback on the effectiveness of their tests in real time, so they can make changes quickly and improve the quality of their software.
- By using AI-augmented software-testing tools, companies can reduce the time and cost it takes to release high-quality software.
Discover AI-Driven Model-Based Testing
Keysight’s Eggplant uses AI-driven model-based testing to deliver the coverage you need to optimize the user experience, speed up release cycles, and improve your quality assurance process across the software testing lifecycle. Eggplant provides a fast, secure, and easy-to-use solution that tests any kind of software on any platform or device.