公开(公告)号：US20210019142A1

公开(公告)日：2021-01-21

申请号：US16515135

申请日：2019-07-18

Applicant: Microsoft Technology Licensing, LLC

Inventor： Ranjita BHAGWAN ,  Chandra Sekhar MADDILA ,  Aditya KUMAR ,  Sumit ASTHANA ,  Rahul KUMAR ,  Sonu MEHTA ,  Chetan BANSAL ,  Balasubramanyan ASHOK ,  Christian Alma BIRD

IPC: G06F8/71 ,  G06N20/00 ,  G06F8/75 ,  G06F8/658 ,  G06F8/41

Abstract: Described herein is a system and method for detecting correlated changes (e.g., between code files and configuration files). For a plurality of code files and a plurality of configuration files, a correlated change model is trained to identify correlated changes across the code files and the configuration files using a machine learning algorithm that discovers change rules using a support parameter, and, a confidence parameter, and, a refinement algorithm that refines the discovered change rules. The correlated change model comprising the change rules is stored. The correlated change model can be used to identify potential issue(s) regarding a particular file (e.g., changed code or configuration file(s)). Information regarding the identified potential issue(s) can be provided to a user.