TABLE OF CONTENTS


What is ACE?

ACE (Application Confidence Engine) attempts to crowdsource opinions on whether an application should be accepted or rejected. This results in a suggested status and a confidence percent based on how many others have either accepted or rejected the specific application.


How to Use

ACE Recommendations are available from the main grid and application DMR context menu. 



Tool Bar

  • Rationisation Show/Hide
    • Show/Hide the App Rationisation group of columns on the grid
  • Normalisation Show/Hide
    • Show/Hide the App Normalisation group of columns on the grid
  • w/ Recommends 
    • Filter the applications to only applications with either a rationalisation or normalisation recommendation. 



App Rationalisation

The grid view will so the current application’s Status and its ACE Recommendation and Confidence percent. If the recommendation is to rationalise to another version of the same application, then that application AppId and Name will also be shown.

Suggestions can be accepted by either clicking the switch next to the specific recommendation or selecting a group of applications and right clicking to bulk approve multiple rationalisation recommendations.



App Normalisation

Normalisation is the process of cleaning up Applications names and making them more consistent across multiple products from the same vendor.

  • Vendor:  Adobe Inc. Adobe Incorporated, Adobe Ltd. would all normalise to simply Adobe.
  • App Name: The vendor and versions are removed from the app name to avoid Apps being named “Adobe Adobe Reader 11 11.2”.
  • Version: The version is cleaned up into the standard version format of Major.Minor.Build.Revision e.g. 10.1.2.3. This allows for clearer versions and better comparisons in rules later.


The grid view will show the current App Vendor, Name, and Version next to the Norm. Vendor, Name Version. Suggestions can be accepted by either clicking the switch next to the specific recommendation or selecting a group of applications and right-clicking to bulk approve multiple normalisation recommendations.