US 12,190,081 B1
Learning session-specific code recommendations for editing code files
Willem Conradie Visser, Los Gatos, CA (US); and Sengamedu Hanumantha Rao Srinivasan, Seattle, WA (US)
Assigned to Amazon Technologies, Inc., Seattle, WA (US)
Filed by Amazon Technologies, Inc., Seattle, WA (US)
Filed on Sep. 19, 2022, as Appl. No. 17/933,461.
Int. Cl. G06F 8/41 (2018.01); G06F 8/33 (2018.01); G06N 20/00 (2019.01); G06F 8/36 (2018.01); G06F 8/38 (2018.01); G06F 8/70 (2018.01); G06F 8/72 (2018.01); G06F 8/73 (2018.01)
CPC G06F 8/33 (2013.01) [G06N 20/00 (2019.01); G06F 8/36 (2013.01); G06F 8/38 (2013.01); G06F 8/41 (2013.01); G06F 8/42 (2013.01); G06F 8/443 (2013.01); G06F 8/447 (2013.01); G06F 8/70 (2013.01); G06F 8/72 (2013.01); G06F 8/73 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A system, comprising:
at least one processor; and
a memory, storing program instructions that when executed by the at least one processor, cause the at least one processor to implement an integrated development environment, the integrated development environment configured to:
capture one or more edits to a code file received via an interface of the integrated development environment during an editing session;
update an artifact used by a machine learning technique to include the captured one or more edits;
after the update to the artifact:
apply, during the editing session, the machine learning technique to identify one or more portions of the code file to replace with respective alternative code portions that makes a same edit as one of the captured one or more edits to the code file, wherein the application of the machine learning technique:
recognizes the one or more portions of the code file according to the captured one or more edits; and
determines corresponding ones of the captured one or more edits as providing the respective alternative code portions; and
display, via the interface, the respective alternative code portions as recommendations to replace the one or more portions of the code file.