Functionize collects test case data during test creation and execution for the purposes of self healing. Machine Learning (ML) Engine is a self healing selection engine. This is the root of ML Deep Analysis.
In Architect settings, ML Deep Analysis is on by default for all users in Architect version 1.1.71+. (See below)
- In Architect, toggle ADV to ON.
- Click on Settings gear icon.
- ML Deep Analysis = ON
(A complete user guide to all Architect Settings can be found HERE!)
If, when using Architect to create a test case on a complex site, the user notices significant performance issues where the site running slowly, we offer a set of diagnosis tips.
Best Practices for Performance Management
- Close all other open tabs. If the browser is low on memory, that can affect Architect.
- Restart the active browser keeping only one tab open.
- Debug tabs. To do this go to Windows>>Task Manager. See what tabs are using up extensive amounts of memory and end those applications. Sometimes extensions can interfere with Architect performance.
- Turn off ML Deep Analysis in Architect settings. *NOTE: ML Deep Analysis setting = ON is preferred. This is not an ideal scenario because the initial execution of the test will be using an older ML self-heal engine. Although the engine is good, it is not as good! However, when the test is executed for the first time, and as long as the execution is successful, the Functionize ML engine pulls all the same data as if you had the setting on in Architect. Having this additional data allows our self-healing to be extremely robust when the site changes structure, when your elements change names, and so on.
If all other recommended trouble shooting options have been exhausted including turning off ML Deep Analysis setting, please submit a support ticket to us.