Invention Grant
- Patent Title: Automated detection of code regressions from time-series data
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Application No.: US16351384Application Date: 2019-03-12
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Publication No.: US11720461B2Publication Date: 2023-08-08
- Inventor: Rahul Nigam , Andrei Nicolae , Mark Raymond Gilbert , Vinod Mukundan Menon
- Applicant: Microsoft Technology Licensing, LLC
- Applicant Address: US WA Redmond
- Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC
- Current Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC
- Current Assignee Address: US WA Redmond
- Main IPC: G06N3/04
- IPC: G06N3/04 ; G06F11/30 ; G06N3/088 ; G06F18/21 ; G06F18/2431 ; G06N20/20 ; G06N20/10

Abstract:
In non-limiting examples of the present disclosure, systems, methods and devices for detecting and classifying service issues associated with a cloud-based service are presented. Operational event data for a plurality of operations associated with the cloud-based application service may be monitored. A statistical-based unsupervised machine learning model may be applied to the operational event data. A subset of the operational event data may be tagged as potentially being associated with a code regression, wherein the subset comprises a time series of operational event data. A neural network may be applied to the time series of operational event data, and the time series of operational event data may be flagged for follow-up if the neural network classifies the time series as relating to a positive code regression category.
Public/Granted literature
- US20200293900A1 AUTOMATED DETECTION OF CODE REGRESSIONS FROM TIME-SERIES DATA Public/Granted day:2020-09-17
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