US 11,972,254 B2
Utilizing a machine learning model to transform a legacy application to a low-code/no-code application
Rajesh Pappu, Bangalore (IN); Surender Subramanian, Bangalore (IN); Jeevak Balasubramaniam, Bangalore (IN); and Vijay Baskaran, Chennai (IN)
Assigned to Accenture Global Solutions Limited, Dublin (IE)
Filed by Accenture Global Solutions Limited, Dublin (IE)
Filed on Jul. 12, 2022, as Appl. No. 17/812,025.
Prior Publication US 2024/0020113 A1, Jan. 18, 2024
Int. Cl. G06F 8/40 (2018.01); G06F 8/38 (2018.01); G06F 8/41 (2018.01); G06F 8/71 (2018.01); G06N 20/00 (2019.01)
CPC G06F 8/71 (2013.01) [G06F 8/38 (2013.01); G06F 8/433 (2013.01); G06N 20/00 (2019.01)] 20 Claims
OG exemplary drawing
 
1. A method, comprising:
receiving, by a device, an application for transforming legacy applications into low-code/no-code applications to be managed by a low-code/no-code platform;
executing, by the device, the application for a legacy application of the legacy applications;
processing, by the device, the legacy application, with a machine learning model, to identify one or more components of the legacy application to be managed by the low-code/no-code platform;
transforming, by the device, the one or more components into one or more transformed components to be managed by the low-code/no-code platform;
implementing, by the device, the one or more transformed components in the legacy application to generate a transformed legacy application; and
performing, by the device, one or more actions based on the transformed legacy application.