公开(公告)号：US20220382613A1

公开(公告)日：2022-12-01

申请号：US17333480

申请日：2021-05-28

Applicant: BUSINESS OBJECTS SOFTWARE LTD.

Inventor： Arta Alavi

IPC: G06F11/07 ,  G06N5/02

Abstract: A method, a system, and a computer program product for analyzing error messages. A first error log generated as a result of an execution of at least one task of a computing system at a first instance is received. The first error log include a plurality of first error messages. A first association rules model is generated using the first error messages. The first association rules model includes a plurality of association rules defining one or more relationships. A second error log, including a plurality of second error messages, generated as a result of an execution of the task at a second instance is received and a second association rules model is generated using the second error messages. Based on the first and second association rules models, at least one error message pattern associated with execution of the at least one task is determined.

公开(公告)号：US20220382776A1

公开(公告)日：2022-12-01

申请号：US17333392

申请日：2021-05-28

Applicant: BUSINESS OBJECTS SOFTWARE LTD.

Inventor： Arta Alavi

IPC: G06F16/25

Abstract: A method, a system, and a computer program product for templatizing error messages in computing systems. An error log generated as a result of an execution of at least one task of a computing system is monitored. The error log includes a plurality of error messages. Each error message includes a first portion and a second portion. Each error message is extracted from the generated error log. One or more error message processing rules for converting each error message into a corresponding template format error message is determined. The error message processing rules are associated with at least one task. The determined error message processing rules are executed to convert each extracted error message into the corresponding template format error message. The converted error message includes the first portion, where the second portion is removed from the converted error message. A converted error log is generated.

公开(公告)号：US11734299B2

公开(公告)日：2023-08-22

申请号：US17333392

申请日：2021-05-28

Applicant: BUSINESS OBJECTS SOFTWARE LTD.

Inventor： Arta Alavi

IPC: G06F16/25

CPC classification number: G06F16/258

Abstract: A method, a system, and a computer program product for templatizing error messages in computing systems. An error log generated as a result of an execution of at least one task of a computing system is monitored. The error log includes a plurality of error messages. Each error message includes a first portion and a second portion. Each error message is extracted from the generated error log. One or more error message processing rules for converting each error message into a corresponding template format error message is determined. The error message processing rules are associated with at least one task. The determined error message processing rules are executed to convert each extracted error message into the corresponding template format error message. The converted error message includes the first portion, where the second portion is removed from the converted error message. A converted error log is generated.

公开(公告)号：US11709726B2

公开(公告)日：2023-07-25

申请号：US17333480

申请日：2021-05-28

Applicant: BUSINESS OBJECTS SOFTWARE LTD.

Inventor： Arta Alavi

IPC: G06F11/00 ,  G06F11/07 ,  G06N5/025

CPC classification number: G06F11/079 ,  G06F11/0772 ,  G06F11/0775 ,  G06N5/025

Abstract: A method, a system, and a computer program product for analyzing error messages. A first error log generated as a result of an execution of at least one task of a computing system at a first instance is received. The first error log include a plurality of first error messages. A first association rules model is generated using the first error messages. The first association rules model includes a plurality of association rules defining one or more relationships. A second error log, including a plurality of second error messages, generated as a result of an execution of the task at a second instance is received and a second association rules model is generated using the second error messages. Based on the first and second association rules models, at least one error message pattern associated with execution of the at least one task is determined.