The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Dec. 23, 2025

Filed:

Apr. 21, 2021
Applicant:

Emc Ip Holding Company Llc, Hopkinton, MA (US);

Inventors:

Tuan Anh Nguyen, San Jose, CA (US);

Shashikanth Lakshmikantha, San Jose, CA (US);

Philip Shilane, Newtown, PA (US);

Assignee:

EMC IP HOLDING COMPANY LLC, Hopkinton, MA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 3/09 (2023.01); G06F 11/3604 (2025.01); G06F 16/17 (2019.01); G06N 20/00 (2019.01);
U.S. Cl.
CPC ...
G06N 20/00 (2019.01); G06F 11/3612 (2013.01); G06F 16/1734 (2019.01); G06N 3/09 (2023.01);
Abstract

Embodiments of the present disclosure relate to a method, a system, and a non-transitory machine-readable medium for assigning performance defects to software processing components. Provided is a method that receives performance data of a set of performance runs of a software application across a set of software processing components of a file software system, where the performance data comprises multiple labeled performance features that are associated with the set of software processing components; receives, from a software processing component expert, a user-selection of a subset of labeled performance features of the several labeled performance features; and trains a machine learning (ML) model to determine whether one or more of the set of software processing components is associated with performance regressions of the software application, using the subset of labeled performance features of the performance data as training data.


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