公开(公告)号：US20240231765A1

公开(公告)日：2024-07-11

申请号：US18618371

申请日：2024-03-27

Applicant: Google LLC

Inventor： Daniel Dun-ning Woo Johnson ,  Daniel Stefan Tarlow ,  Maxim Tabachnyk ,  Marc Hatcher Rasi ,  Jacob Austin ,  Hassan Abolhassani ,  Jacob Hanson Hegna

IPC: G06F8/33

CPC classification number: G06F8/33

Abstract: Systems and methods of the present disclosure are directed to a method for machine- learned code segment prediction for optimizing software development. The method includes obtaining an incomplete segment of code. The method includes processing the incomplete segment of code with a machine-learned code prediction model to obtain a sampled set of segment completion predictions that include code that completes the incomplete segment of code. The method includes determining an aggregated segment completion prediction from the sampled set of segment completion predictions. The method includes replacing a portion of the aggregated segment completion prediction with an input field, wherein the portion of the aggregated segment completion prediction is associated with a degree of certainty less than a threshold degree of certainty.

公开(公告)号：US20230393817A1

公开(公告)日：2023-12-07

申请号：US17832199

申请日：2022-06-03

Applicant: Google LLC

Inventor： Daniel Dun-ning Woo Johnson ,  Daniel Stefan Tarlow ,  Maxim Tabachnyk ,  Marc Hatcher Rasi ,  Jacob Austin ,  Hassan Abolhassani ,  Jacob Hanson Hegna

IPC: G06F8/33

CPC classification number: G06F8/33

Abstract: Systems and methods of the present disclosure are directed to a method for machine-learned code segment prediction for optimizing software development. The method includes obtaining an incomplete segment of code. The method includes processing the incomplete segment of code with a machine-learned code prediction model to obtain a sampled set of segment completion predictions that include code that completes the incomplete segment of code. The method includes determining an aggregated segment completion prediction from the sampled set of segment completion predictions. The method includes replacing a portion of the aggregated segment completion prediction with an input field, wherein the portion of the aggregated segment completion prediction is associated with a degree of certainty less than a threshold degree of certainty.

公开(公告)号：US20240111497A1

公开(公告)日：2024-04-04

申请号：US18535473

申请日：2023-12-11

Applicant: Google LLC

Inventor： Maxim Tabachnyk ,  Yurun Shen ,  Stoyan Stefanov Nikolov ,  Stanislav Pyatykh ,  Ksenia Korovina ,  Evgeny Gryaznov ,  Erik Grabljevec

IPC: G06F8/33

CPC classification number: G06F8/33

Abstract: A method for providing autofill suggestions in a development environment includes obtaining, from a user interface executing on a user device, a user input representing source code generated within a development environment. The source code is created using a particular programming language and a programming code base. The method further includes determining, using a machine learning model, at least one autofill suggestion based on the user input, the autofill suggestion continuing the source code represented by the user input. The method further includes determining, using a rule-based semantic checker configured for the particular programming language, whether the autofill suggestion is semantically correct based on the development environment and the programming code base. The method also includes, when the autofill suggestion is semantically correct, transmitting the autofill suggestion for display on the user interface of the user device.

公开(公告)号：US11861333B2

公开(公告)日：2024-01-02

申请号：US17657113

申请日：2022-03-29

Applicant: Google LLC

Inventor： Maxim Tabachnyk ,  Yurun Shen ,  Stoyan Stefanov Nikolov ,  Stanislav Pyatykh ,  Ksenia Korovina ,  Evgeny Gryaznov ,  Erik Grabljevec

IPC: G06F8/33

CPC classification number: G06F8/33

Abstract: A method for providing autofill suggestions in a development environment includes obtaining, from a user interface executing on a user device, a user input representing source code generated within a development environment. The source code created using a particular programming language and a programming code base. The method further includes determining, using a machine learning model, at least one autofill suggestion based on the user input, the autofill suggestion continuing the source code represented by the user input. The method further includes determining, using a rule-based semantic checker configured for the particular programming language, whether the autofill suggestion is semantically correct based on the development environment and the programming code base. The method also includes, when the autofill suggestion is semantically correct, transmitting the autofill suggestion for display on the user interface of the user device.

公开(公告)号：US11972234B2

公开(公告)日：2024-04-30

申请号：US17832199

申请日：2022-06-03

Applicant: Google LLC

Inventor： Daniel Dun-Ning Woo Johnson ,  Daniel Stefan Tarlow ,  Maxim Tabachnyk ,  Marc Hatcher Rasi ,  Jacob Austin ,  Hassan Abolhassani ,  Jacob Hanson Hegna

IPC: G06F8/33

CPC classification number: G06F8/33

Abstract: Systems and methods of the present disclosure are directed to a method for machine-learned code segment prediction for optimizing software development. The method includes obtaining an incomplete segment of code. The method includes processing the incomplete segment of code with a machine-learned code prediction model to obtain a sampled set of segment completion predictions that include code that completes the incomplete segment of code. The method includes determining an aggregated segment completion prediction from the sampled set of segment completion predictions. The method includes replacing a portion of the aggregated segment completion prediction with an input field, wherein the portion of the aggregated segment completion prediction is associated with a degree of certainty less than a threshold degree of certainty.

公开(公告)号：US20230315400A1

公开(公告)日：2023-10-05

申请号：US17657113

申请日：2022-03-29

Applicant: Google LLC

Inventor： Maxim Tabachnyk ,  Yurun Shen ,  Stoyan Stefanov Nikolov ,  Stanislav Pyatykh ,  Ksenia Korovina ,  Evgeny Gryaznov ,  Erik Grabljevec

IPC: G06F8/33

CPC classification number: G06F8/33

Abstract: A method for providing autofill suggestions in a development environment includes obtaining, from a user interface executing on a user device, a user input representing source code generated within a development environment. The source code created using a particular programming language and a programming code base. The method further includes determining, using a machine learning model, at least one autofill suggestion based on the user input, the autofill suggestion continuing the source code represented by the user input. The method further includes determining, using a rule-based semantic checker configured for the particular programming language, whether the autofill suggestion is semantically correct based on the development environment and the programming code base. The method also includes, when the autofill suggestion is semantically correct, transmitting the autofill suggestion for display on the user interface of the user device.