US 11,941,393 B2
Systems and methods for managing a software repository
Brian Burgess, Richmond, VA (US); Benjamin Cabell Glancy, Richmond, VA (US); Narender Pashikant, Ashburn, VA (US); and Guganathan Sellamuthu, Glen Allen, VA (US)
Assigned to CAPITAL ONE SERVICES, LLC, McLean, VA (US)
Filed by Capital One Services, LLC, McLean, VA (US)
Filed on Nov. 1, 2021, as Appl. No. 17/515,746.
Prior Publication US 2023/0133407 A1, May 4, 2023
Int. Cl. G06F 9/44 (2018.01); G06F 8/73 (2018.01); G06F 16/903 (2019.01); G06F 16/9032 (2019.01); G06N 3/08 (2023.01)
CPC G06F 8/73 (2013.01) [G06F 16/90332 (2019.01); G06F 16/90335 (2019.01); G06N 3/08 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method of managing a software repository, the method comprising:
receiving, at a computing device, a dataset comprising a set of computer instructions;
parsing, by a machine learning model executing on the computing device, through feature-related data from the dataset, the feature-related data comprising data indicative of a feature of the set of computer instructions;
training the machine learning model using the feature-related data from the dataset to generate a synopsis of the dataset by:
determining, by the machine learning model executing on the computing device, a function of the set of computer instructions based on the feature-related data;
generating, by the machine learning model, the synopsis comprising a description of the function of the set of computer instructions;
transmitting the synopsis to a user interface;
receiving, from the user interface, feedback from a user indicative of whether the synopsis accurately describes the function of the set of computer instructions;
in response to determining that the feedback indicates that the synopsis accurately describes the function of the set of computer instructions, storing the synopsis in a memory of the computing device; and
in response to determining the feedback indicates that the synopsis inaccurately describes the function of the set of computer instructions, generating, by the machine learning model executing on the computing device, a revised synopsis of the function of the set of computer instructions based on the feedback from the user.