公开(公告)号：US12190081B1

公开(公告)日：2025-01-07

申请号：US17933461

申请日：2022-09-19

Applicant: Amazon Technologies, Inc.

Inventor： Willem Conradie Visser ,  Sengamedu Hanumantha Rao Srinivasan

IPC: G06F8/41 ,  G06F8/33 ,  G06N20/00 ,  G06F8/36 ,  G06F8/38 ,  G06F8/70 ,  G06F8/72 ,  G06F8/73

Abstract: Session-specific edit recommendations may be made for editing a code file. After a code editing session is started, code file edits may be captured. A machine learning technique may be applied to learn the code edits and recommend alternative code portions for portions of the code file during the code editing session. The recommendations may be provided and accepted, or not, via an interface of a code editor application.

公开(公告)号：US12189506B1

公开(公告)日：2025-01-07

申请号：US18082521

申请日：2022-12-15

Applicant: Amazon Technologies, Inc.

Inventor： Xiao Wang ,  Jasmeet Chhabra ,  Yuyang Wang ,  Willem Conradie Visser

IPC: G06F11/30 ,  G06F11/07

Abstract: Systems and methods are described relating to aggregating log anomalies. In some examples, a plurality of log anomaly instances may be obtained, from a log anomaly detector, where individual instances are associated with a first log anomaly type and a first anomalous log event. Log anomaly instances associated with the first log anomaly type and the first anomalous log event may be combined into a first log anomaly class. The first log anomaly class may be combined with a second log anomaly class, including log anomaly instances associated with the first anomalous log event and a second log anomaly type, into a log anomaly group, which may correlate the occurrences of the first and second anomaly types to the same first anomalous log event over a period of time. An indication of the log anomaly group may then be output.

公开(公告)号：US20250094136A1

公开(公告)日：2025-03-20

申请号：US18970668

申请日：2024-12-05

Applicant: Amazon Technologies, Inc.

Inventor： Willem Conradie Visser ,  Sengamedu Hanumantha Rao Srinivasan

IPC: G06F8/33 ,  G06F8/36 ,  G06F8/38 ,  G06F8/41 ,  G06F8/70 ,  G06F8/72 ,  G06F8/73 ,  G06N20/00

Abstract: Session-specific edit recommendations may be made for editing a code file. After a code editing session is started, code file edits may be captured. A machine learning technique may be applied to learn the code edits and recommend alternative code portions for portions of the code file during the code editing session. The recommendations may be provided and accepted, or not, via an interface of a code editor application.

公开(公告)号：US11736525B1

公开(公告)日：2023-08-22

申请号：US16904467

申请日：2020-06-17

Applicant: Amazon Technologies, Inc.

Inventor： Neha Rungta ,  Willem Conradie Visser ,  Daniel George Peebles

IPC: H04L9/40 ,  G06F21/57 ,  G06F21/62 ,  H04L41/0893

CPC classification number: H04L63/20 ,  G06F21/577 ,  G06F21/6218 ,  H04L41/0893 ,  H04L63/10

Abstract: Methods, systems, and computer-readable media for generating access control policies using static analysis are disclosed. An access control policy generator performs static analysis of program code of a software product. The static analysis identifies one or more calls to one or more external components in the program code. The access control policy generator determines a mapping of the one or more calls to one or more actions. The one or more actions are selected from a plurality of known actions supported by an access control policy manager. The access control policy generator generates an access control policy associated with the software product. The access control policy comprises one or more permissions with respect to the one or more external components. The access control policy permits the software product to access the plurality of external components using the access control policy manager during execution of the software product.

公开(公告)号：US11675584B1

公开(公告)日：2023-06-13

申请号：US17217327

申请日：2021-03-30

Applicant: Amazon Technologies, Inc.

Inventor： Aritra Sengupta ,  Lee Pike ,  Martin Schaef ,  Nicolas Leandro Rosner ,  Willem Conradie Visser

IPC: G06F9/44 ,  G06F8/75 ,  G06F16/901 ,  G06F8/10

CPC classification number: G06F8/75 ,  G06F8/10 ,  G06F16/9027

Abstract: Techniques for visualizing dependent relationships in computer program analysis trace elements are described. A code analysis service analyzes computer code associated with a software application for at least one of errors or policy violations. The service outputs a trace log identifying a path within the computer code that results in an error or policy violation. The trace log includes a set of trace elements each corresponding to a line of the computer code. The output is displayed as a tree data structure including nodes. The nodes may include indentations indicating dependent relationships between and among variables initialized at lines in the computer code corresponding to the nodes. Alternatively, the nodes may be arranged as a hierarchy with edges connecting adjacent nodes, and nodes at different levels indicating dependent relationships. The tree data structure may include annotations providing additional contextual information about the actions performed at each node.