公开(公告)号：US20240319991A1

公开(公告)日：2024-09-26

申请号：US18186458

申请日：2023-03-20

Applicant: Adobe Inc.

Inventor： Charles Robert John Matthews ,  Thomas Stanley Dalton ,  Harinder Singh Sandhu ,  David Alexander Collie ,  Adrian John O'Lenskie

IPC: G06F8/71 ,  G06F8/41

CPC classification number: G06F8/71 ,  G06F8/41

Abstract: In implementations of systems for generating review likelihoods for sets of code, a computing device implements a review system to compile input data based on code data describing information associated with a set of new code to be incorporated into a set of existing code and reviewer data describing information associated with a potential reviewer of sets of code. The review system processes the input data using a machine learning model trained on training data to generate review likelihoods for potential reviewers of sets of code to be selected to review sets of new code. A review likelihood for the potential reviewer of sets of code to be selected to review the set of new code is generated using the machine learning model based on processing the input data. The review system generates an indication of the review likelihood for display in a user interface.

公开(公告)号：US12229552B2

公开(公告)日：2025-02-18

申请号：US18186458

申请日：2023-03-20

Applicant: Adobe Inc.

Inventor： Charles Robert John Matthews ,  Thomas Stanley Dalton ,  Harinder Singh Sandhu ,  David Alexander Collie ,  Adrian John O'Lenskie

IPC: G06F8/71 ,  G06F8/41

Abstract: In implementations of systems for generating review likelihoods for sets of code, a computing device implements a review system to compile input data based on code data describing information associated with a set of new code to be incorporated into a set of existing code and reviewer data describing information associated with a potential reviewer of sets of code. The review system processes the input data using a machine learning model trained on training data to generate review likelihoods for potential reviewers of sets of code to be selected to review sets of new code. A review likelihood for the potential reviewer of sets of code to be selected to review the set of new code is generated using the machine learning model based on processing the input data. The review system generates an indication of the review likelihood for display in a user interface.

公开(公告)号：US10834236B2

公开(公告)日：2020-11-10

申请号：US15340066

申请日：2016-11-01

Applicant: ADOBE INC.

Inventor： Neil Charles Armour Moore ,  Adrian John O'Lenskie

IPC: G06F3/00 ,  H04L29/06 ,  H04L29/08 ,  G06F3/0481

Abstract: Systems and methods provide for dynamic menu content for context menus for an object stored on a client device. Requests for context menu content are sent from the client device to a remote server associated with a type of object corresponding to the object stored on the client device. The remote server generates and sends menu content, including one or more custom menu items, to the client device. Upon a user's selection of a menu item, an indicator of the selected menu item is sent to the remote server and an action associated with the selected item is performed. Information relating to requests for menu content and selections of menu items are recorded and, in some embodiments, used as menu content usage data for determining menu content for subsequent requests. Menu content usage data may be used to increase selections of certain menu items and to optimize user experience.

公开(公告)号：US11113185B2

公开(公告)日：2021-09-07

申请号：US16679971

申请日：2019-11-11

Applicant: Adobe Inc.

Inventor： Harinder Singh Sandhu ,  Adrian John O'Lenskie

IPC: G06F8/60 ,  G06F11/36

Abstract: Software code is written using a multistage automated code deployment pipeline. A code change is provided to the pipeline and at each stage various checks or evaluations of the code change is performed. Additionally, a risk profile is generated for the code change that identifies a risk of making the code change based on the code change itself as well as a reputation of the individual providing the code change. In one or more stages of the pipeline, a determination is made whether the risk profile meets a verification criteria, and if so the code change does not progress to the next stage in the pipeline until additional verification (in addition to any testing typically performed at that stage) is performed.

公开(公告)号：US20210141718A1

公开(公告)日：2021-05-13

申请号：US16679971

申请日：2019-11-11

Applicant: Adobe Inc.

Inventor： Harinder Singh Sandhu ,  Adrian John O'Lenskie

IPC: G06F11/36 ,  G06F8/60

Abstract: Software code is written using a multistage automated code deployment pipeline. A code change is provided to the pipeline and at each stage various checks or evaluations of the code change is performed. Additionally, a risk profile is generated for the code change that identifies a risk of making the code change based on the code change itself as well as a reputation of the individual providing the code change. In one or more stages of the pipeline, a determination is made whether the risk profile meets a verification criteria, and if so the code change does not progress to the next stage in the pipeline until additional verification (in addition to any testing typically performed at that stage) is performed.