公开(公告)号：US20220035605A1

公开(公告)日：2022-02-03

申请号：US17499749

申请日：2021-10-12

Applicant: Intel Corporation

Inventor： Alejandro IBARRA VON BORSTEL ,  Fernando AMBRIZ MEZA ,  David Israel GONZALEZ AGUIRRE ,  Walter Alejandro MAYORGA MACIAS ,  Rocio HERNANDEZ FABIAN

IPC: G06F8/35 ,  G06F8/41 ,  G06N20/00

Abstract: Methods, apparatus, and software for implementing dual Bayesian encoding-decoding for text-to-code transformations. In one aspect, a multi-model probabilistic source code model employing dual Bayesian encoder-decoder models is used to convert natural language (NL) inputs (aka requests) into source code. An NL input is processed to generate a Probabilistic Distribution (PD) of Source code (SC) tokens in an SC token sequence and a PD of Abstract Syntax Tree (AST) tokens in an AST token sequence, wherein each SC token is associated with a respective AST token, and each of the SC and AST tokens have a respective PD. One or more fixing rules are applied to one or more tokens SC tokens that are identified as needing fixing, wherein the fixing rule are selected in consideration of the PDs of the SC tokens and the PDs of their associated AST tokens.