Kobiton preps AI-enabled testing tools for mobile apps

Mobile apps tester Kobiton announced plans to roll out an AI issue aggregation engine early next year. The AI-driven engine will allow users to group related errors and identify shared commonalities across test sessions, the company said.

Kobiton made the announcement September 26. Providing one example of how the engine would work, Kobiton said issues that seem to be distinct, such as button occlusion across different devices, can be identified as stemming from the same cause, such as a shared screen resolution. Kobiton’s AI issue aggregation engine can consolidate these errors into a single bug, eliminating manual steps and streamlining debugging for developers, the company said.

Currently, Kobiton allows customers and an ecosystem of third-party AI providers to integrate their own AI algorithms to analyze the mobile device “exhaust” that is captured during a test session. This exhaust includes critical data such as test steps, screen shots, full video capture at 30 frames per second, device logs, system metrics, network payloads, device health statistics, and XML for each test.

The exhaust data is collected in real time while the application is being testing and fed into Kobiton’s AI gateway. Kobiton has established partnerships with AI-centric companies such as Applitools. When these AI-powered tools detect app issues, results are ingested into the Kobiton Session Explorer, which allows users to inspect when and where an issue occurred along a timeline, offering greater visibility into the testing process, Kobiton said.