US 11,726,775 B2
Source code issue assignment using machine learning
Prabal Mahanta, Bangalore (IN); and Vipul Khullar, New Delhi (IN)
Assigned to SAP SE, Walldorf (DE)
Filed by SAP SE, Walldorf (DE)
Filed on Jun. 16, 2021, as Appl. No. 17/349,154.
Prior Publication US 2022/0405091 A1, Dec. 22, 2022
Int. Cl. G06F 8/71 (2018.01); G06F 8/20 (2018.01); G06F 11/36 (2006.01); G06N 20/00 (2019.01); G06F 18/2113 (2023.01); G06V 10/75 (2022.01)
CPC G06F 8/71 (2013.01) [G06F 8/24 (2013.01); G06F 11/362 (2013.01); G06F 11/3604 (2013.01); G06F 18/2113 (2023.01); G06N 20/00 (2019.01); G06V 10/751 (2022.01)] 19 Claims
OG exemplary drawing
 
1. A method, comprising:
generating a machine learning model using multiple versions of a source code object and identifiers of a plurality of developers associated with the multiple versions of the source code object, wherein the machine learning model is generated by generating feature sets for the multiple versions of the source code object, comparing the feature sets to one another, generating similarity scores for the multiple versions of the source code object based on the comparing, and incorporating the similarity scores into training of the machine learning model;
receiving an additional version of the source code object;
detecting a source code issue in the additional version of the source code object; and
using the machine learning model to identify a developer, of the plurality of developers, as a candidate to correct the source code issue in the additional version of the source code object.