IP Library Granted Patent US 10,402,249
Granted Patent B2
US 10,402,249 · App. 15/460,682 · Granted Sep 3, 2019

Method and apparatus for failure classification

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Quick Facts
Patent No.
US 10,402,249
App. No.
15/460,682
Granted
Sep 3, 2019
Kind
B2
Abstract

Embodiments of the present disclosure provide a method and apparatus for classifying a failure. The method comprises obtaining a log associated with a failure and identifying a key event in the log, and the key event indicates a predetermined situation. The method further comprises determining a similarity between the failure and each of a set of historical failures based on the key event, and the set of historical failures have been classified into at least one category. The method further comprises classifying the failure based at least partly on the similarity. Embodiments of the present disclosure enable classifying the failure fast and accurately by determining the similarity associated with key event between failures.

Claims (72)

1. A method for classifying a failure, comprising:

obtaining a log associated with a failure;

identifying a key event in the log, the key event indicating a predetermined situation;

determining a similarity between the failure and each of a set of historical failures based on the key event, the set of historical failures having been classified into at least one category; and

classifying the failure based at least partly on the similarity, the classifying of the failure including (i) determining a subset of the set of historical failures based on the similarity, (ii) determining another similarity associated with a predetermined failure characteristic between the failure and each of the subset of historical failures, the predetermined failure characteristic including at least one of a recency value, a state, a release number, a version number, and a duplication value, and (iii) classifying the failure based on the similarity and the other similarity.

2. The method according to claim 1 , wherein the identifying a key event in the log comprises:

determining whether at least one of the one or more predetermined key events exists in the log; and

in response to determining the at least one predetermined key event exists in the log, determining the at least one predetermined key event as the key event in the log.

3. The method according to claim 1 , wherein the determining a similarity between the failure and each of a set of historical failures comprises:

determining, based on an event status list indicating whether one or more predetermined key events occurs, the similarity between the failure and each of the set of historical failures.

4. The method according to claim 1 , wherein the determining a similarity between the failure and each of a set of historical failures comprises:

determining a first event status list of the failure according to one or more predetermined key events;

determining a second event status list of each of the set of historical failures according to the one or more predetermined key events; and

determining the similarity between the failure and each of the historical failures by comparing the first and second event status lists, the first and second event status lists indicating whether the one or more predetermined key event occurs.

5. The method according to claim 4 , wherein the determining a similarity between the failure and each of a set of historical failures further comprises:

setting respective weight for individual key event in the one or more predetermined key events; and

determining the similarity between the failure and each of the historical failures based at least partly on the respective weight.

6. The method according to claim 1 , wherein the classifying the failure comprises:

weighting the similarity and, the other similarity by a first weight and a second weight respectively;

determining a weighted similarity between the failure and each of the subset of historical failures based on the similarity, the other similarity and the first and second weights; and

classifying the failure based on the weighted similarity.

7. The method according to claim 1 , wherein the determining another similarity comprises at least one of the following:

determining a first similarity associated with the recency value by comparing timestamp information of the failure and each of the subset of historical failures;

determining a second similarity associated with the state by determining a current state of each of the subset of historical failures;

determining a third similarity associated with the release number by comparing release numbers associated with failed applications in which the failure and each of the subset of historical failures occur respectively;

determining a fourth similarity associated with the version number by comparing version numbers associated with failed applications in which the failure and each of the subset of historical failures occur respectively; and

determining a fifth similarity associated with the duplication value by determining a number of times that the failure repeats in the set of historical failures.

8. The method according to claim 6 , wherein the classifying the failure comprises:

selecting, from the subset of historical failures, a predetermined number of historical failures based on the weighted similarity;

analyzing statistically categories of the predetermined number of historical failures; and

selecting, from the categories, a category to which the failure is to be classified.

9. A system, comprising:

a data storage system; and

computer-executable program logic encoded in memory of one or more computers enabled for classifying a failure, wherein the computer-executable program logic is configured for the execution of:

obtaining a log associated with a failure;

identifying a key event in the log, the key event indicating a predetermined situation;

determining a similarity between the failure and each of a set of historical failures based on the key event, the set of historical failures having been classified into at least one category; and

classifying the failure based at least partly on the similarity, the classifying of the failure including (i) determining a subset of the set of historical failures based on the similarity, (ii) determining another similarity associated with a predetermined failure characteristic between the failure and each of the subset of historical failures, the predetermined failure characteristic including at least one of a recency value, a state, a release number, a version number, and a duplication value, and (iii) classifying the failure based on the similarity and the other similarity.

10. The system of claim 9 , wherein the identifying a key event in the log comprises:

determining whether at least one of the one or more predetermined key events exists in the log; and

in response to determining the at least one predetermined key event exists in the log, determining the at least one predetermined key event as the key event in the log.

11. The system of claim 9 , wherein the determining a similarity between the failure and each of a set of historical failures comprises:

determining, based on an event status list indicating whether one or more predetermined key events occurs, the similarity between the failure and each of the set of historical failures.

12. The system of claim 9 , wherein the determining a similarity between the failure and each of a set of historical failures comprises:

determining a first event status list of the failure according to one or more predetermined key events;

determining a second event status list of each of the set of historical failures according to the one or more predetermined key events; and

determining the similarity between the failure and each of the historical failures by comparing the first and second event status lists, the first and second event status lists indicating whether the one or more predetermined key event occurs.

13. The system of claim 12 , wherein the determining a similarity between the failure and each of a set of historical failures further comprises:

setting respective weight for individual key event in the one or more predetermined key events; and

determining the similarity between the failure and each of the historical failures based, at least partly on the respective weight.

14. The system of claim 9 , wherein the classifying the failure comprises:

weighting the similarity and the other similarity by a first weight and a second weight respectively;

determining a weighted similarity between the failure and each of the subset of historical failures based on the similarity, the other similarity and the first and second weights; and

classifying the failure based on the weighted similarity.

15. The system of claim 9 , wherein the determining another similarity comprises at least one of the following:

determining a first similarity associated with the recency value by comparing timestamp information of the failure and each of the subset of historical failures;

determining a second similarity associated with the state by determining a current state of each of the subset of historical failures;

determining a third similarity associated with the release number by comparing release numbers associated with failed applications in which the failure and each of the subset of historical failures occur respectively;

determining a fourth similarity associated with the version number by comparing version numbers associated with failed applications in which the failure and each of the subset of historical failures occur respectively; and

determining a fifth similarity associated with the duplication value by determining a number of times that the failure repeats in the set of historical failures.

16. The system of claim 14 , wherein the classifying the failure comprises:

selecting, from the subset of historical failures, a predetermined number of historical failures based on the weighted similarity;

analyzing statistically categories of the predetermined number of historical failures; and

selecting, from the categories, a category to which the failure is to be classified.

17. A computer program product for classifying a failure, the computer program product comprising:

a non-transitory computer readable medium encoded with computer-executable code, the code configured to enable the execution of:

obtaining a log associated with a failure;

identifying a key event in the log, the key event indicating a predetermined situation determining a similarity between the failure and each of a set of historical failures based on the key event, the set of historical failures having been classified into at least one category; and

classifying the failure based at least partly on the similarity, the classifying of the failure including (i) determining a subset of the set of historical failures based on the similarity, (ii) determining another similarity associated with a predetermined failure characteristic between the failure and each of the subset of historical failures, the predetermined failure characteristic including at least one of a recency value, a state, a release number, a version number, and a duplication value, and (iii) classifying the failure based on the similarity and the other similarity.

18. The computer program product of claim 17 , wherein the identifying a key event in the log comprises:

determining whether at least one of the one or more predetermined key events exists in the log; and

in response to determining the at least one predetermined key event exists in the log, determining the at least one predetermined key event as the key event in the log.

Assignments (8)
RELEASE OF SECURITY INTEREST IN PATENTS PREVIOUSLY RECORDED AT REEL/FRAME (053546/0001) Recorded Jun 23, 2022
From: THE BANK OF NEW YORK MELLON TRUST COMPANY, N.A., AS NOTES COLLATERAL AGENT
To: DELL MARKETING L.P. (ON BEHALF OF ITSELF AND AS SUCCESSOR-IN-INTEREST TO CREDANT TECHNOLOGIES, INC.); DELL INTERNATIONAL L.L.C.; DELL PRODUCTS L.P.; DELL USA L.P.; EMC CORPORATION; DELL MARKETING CORPORATION (SUCCESSOR-IN-INTEREST TO FORCE10 NETWORKS, INC. AND WYSE TECHNOLOGY L.L.C.); EMC IP HOLDING COMPANY LLC
Reel/Frame 071642/0001 →
RELEASE OF SECURITY INTEREST IN PATENTS PREVIOUSLY RECORDED AT REEL/FRAME (042769/0001) Recorded Apr 26, 2022
From: THE BANK OF NEW YORK MELLON TRUST COMPANY, N.A., AS NOTES COLLATERAL AGENT
To: DELL PRODUCTS L.P.; EMC CORPORATION; EMC IP HOLDING COMPANY LLC (ON BEHALF OF ITSELF AND AS SUCCESSOR-IN-INTEREST TO MOZY, INC.); DELL MARKETING CORPORATION (SUCCESSOR-IN-INTEREST TO WYSE TECHNOLOGY L.L.C.)
Reel/Frame 059803/0802 →
RELEASE OF SECURITY INTEREST AT REEL 042768 FRAME 0585 Recorded Nov 2, 2021
From: CREDIT SUISSE AG, CAYMAN ISLANDS BRANCH
To: DELL PRODUCTS L.P.; EMC CORPORATION; EMC IP HOLDING COMPANY LLC; MOZY, INC.; WYSE TECHNOLOGY L.L.C.
Reel/Frame 058297/0536 →
SECURITY AGREEMENT Recorded Apr 22, 2020
From: CREDANT TECHNOLOGIES INC.; DELL INTERNATIONAL L.L.C.; DELL MARKETING L.P.; DELL PRODUCTS L.P.; DELL USA L.P.; EMC CORPORATION; FORCE10 NETWORKS, INC.; WYSE TECHNOLOGY L.L.C.; EMC IP HOLDING COMPANY LLC
To: THE BANK OF NEW YORK MELLON TRUST COMPANY, N.A.
Reel/Frame 053546/0001 →
SECURITY AGREEMENT Recorded Mar 21, 2019
From: CREDANT TECHNOLOGIES, INC.; DELL INTERNATIONAL L.L.C.; DELL MARKETING L.P.; DELL PRODUCTS L.P.; DELL USA L.P.; EMC CORPORATION; FORCE10 NETWORKS, INC.; WYSE TECHNOLOGY L.L.C.; EMC IP HOLDING COMPANY LLC
To: THE BANK OF NEW YORK MELLON TRUST COMPANY, N.A.
Reel/Frame 049452/0223 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 21, 2017
From: XIAO, HUIBING; GAO, JIAN; GAO, HONGPO; HAN, GENG; DONG, JIBING; GONG, SHAOQIN
To: EMC IP HOLDING COMPANY, LLC
Reel/Frame 044935/0134 →
PATENT SECURITY INTEREST (CREDIT) Recorded Jun 12, 2017
From: DELL PRODUCTS L.P.; EMC CORPORATION; EMC IP HOLDING COMPANY LLC; MOZY, INC.; WYSE TECHNOLOGY L.L.C.
To: CREDIT SUISSE AG, CAYMAN ISLANDS BRANCH, AS COLLATERAL AGENT
Reel/Frame 042768/0585 →
PATENT SECURITY INTEREST (NOTES) Recorded Jun 12, 2017
From: DELL PRODUCTS L.P.; EMC CORPORATION; EMC IP HOLDING COMPANY LLC; MOZY, INC.; WYSE TECHNOLOGY L.L.C.
To: THE BANK OF NEW YORK MELLON TRUST COMPANY, N.A., AS COLLATERAL AGENT
Reel/Frame 042769/0001 →