We train the model based on user sessions to learn how to use an app. The model learns how to execute specific flows, but also how to interact with components in the more general sense. Since most developers use compostable components, patterns of usage are repeated across the same app.

Then, during test generation, we bias the model to explore edge cases (in a few ways), and the model is still able to complete those even with low sample.

In other words, we direct the model toward certain goals, and flows and also add chaos to the process which result in the model executing unexpected flows.