Software testing

This invention aims to find the exact reason why an automated test for a web application fails. It does this by running a script that interacts with the app's user interface, then uses computer vision to compare how the interface looks at different points. By analyzing these visual differences and using smart probability calculations, it identifies which specific action in the test script most likely caused the failure.

Why it matters: Filed before the widespread availability of highly accurate, off-the-shelf computer vision and AI models. The core idea of visually comparing UI states and using probabilistic models for root cause analysis is now much more feasible and powerful due to advancements in AI/ML tools and cloud services since 2019.

Status: Not in forceListed as no longer active. The specific reason is not in the record we hold.
How hard to build: SpecializedSoftware logic, computer vision, probabilistic models

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