US 12,032,936 B2
Code adaptation through deep learning
Miltiadis Allamanis, Cambridge (GB); Shengyu Fu, Redmond, WA (US); Xiaoyu Liu, Sammamish, WA (US); Neelakantan Sundaresan, Bellevue, WA (US); and Alexey Svyatkovskiy, Bellevue, WA (US)
Assigned to MICROSOFT TECHNOLOGY LICENSING, LLC., Redmond, WA (US)
Filed by MICROSOFT TECHNOLOGY LICENSING, LLC., Redmond, WA (US)
Filed on Mar. 24, 2022, as Appl. No. 17/703,169.
Prior Publication US 2023/0305824 A1, Sep. 28, 2023
Int. Cl. G06F 8/51 (2018.01); G06F 8/41 (2018.01); G06F 8/53 (2018.01); G06N 3/08 (2023.01); G06F 16/901 (2019.01); G06F 40/279 (2020.01); G06F 40/284 (2020.01); G06F 40/30 (2020.01); G06N 3/0455 (2023.01); G06N 20/00 (2019.01)
CPC G06F 8/51 (2013.01) [G06N 3/08 (2013.01); G06F 8/41 (2013.01); G06F 8/433 (2013.01); G06F 16/9027 (2019.01); G06F 40/279 (2020.01); G06F 40/284 (2020.01); G06F 40/30 (2020.01); G06N 3/0455 (2023.01); G06N 20/00 (2019.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method, comprising:
detecting insertion of a pasted source code snippet into a pre-existing partial source code program, wherein the pasted source code snippet includes a variable name undefined in the pasted source code snippet and in the pre-existing partial source code program, wherein the pasted source code snippet comes from a source external to the pre-existing partial source code program;
predicting a defined variable name from the pre-existing partial source code program to replace the undefined variable name from a probability distribution output from a deep learning model given a context of the pre-existing partial source code program; and
altering the undefined variable name with the predicted defined variable name in the pre-existing partial source code program.