Applitools research finds that AI increases testing efficiency 3X through Automated Validation and Maintenance

    Applitools, a Visual AI-Powered Testing Platform recently conducted research on millions of tests from customers which revealed that for every test step that was manually evaluated, two extra test steps were instantaneously fixed by the AI-powered automated maintenance, increasing engineering productivity by more than three times.

    “As engineering teams mature and scale their release and testing strategies, they face new challenges to keep pace with CI/CD environments,” said Moshe Milman, co-founder, and COO of Applitools. “Applitools’ Visual AI technology is the only solution in the market that offers AI-powered auto-analysis and auto-maintenance of tests and the test accuracy that is required to run at a rapid rate. Testing teams can now quickly and accurately assess test results across different environments and identify where bugs are happening so that they can improve their overall testing strategy and make a direct impact on the bottom line.”

    To evaluate the test outcomes of Applitools’ Visual AI with those of other tools that rely on pixel matching and less developed AI algorithms, the research team also performed a simulation. In the comparison, Applitools was subjected to millions of tests in contrast to the other tools, and it was discovered that on average, Applitools lowered the count of false positives by 3 times. It is practically unfeasible to measure the speed of modern CI/CD and run all over numerous environments because of these false positives that are detected by less sophisticated algorithms. Engineers invest innumerable hours debugging erroneous bugs brought on by inadequately accurate or developed algorithms.

    The implementation of automated testing approaches is supported by Applitools’ AI-powered test validation and maintenance capabilities, which relieve testing teams of the hardship of spending hours assessing and modifying hundreds or thousands of test outcomes.

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