Computer crash risk assessment

• US 10,331,508 B2
• Filed: 01/25/2017
• Issued: 06/25/2019
• Est. Priority Date: 06/23/2016
• Status: Active Grant

• Current Assignee: Vmware LLC (Broadcom, Inc.)
• Original Assignee: VMware, Inc. (Broadcom, Inc.)
• Inventors: Gadi, Sowgandh Sunil, Khan, Ayoob, Karajgaonkar, Vihang
• Primary Examiner(s): Contino, Paul
• Application Number:
  US15/415,235
• Publication Number:
  US 20170371736A1
• Time in Patent Office: 881 Days
• CPC Class Codes: G06F 11/0769 Readable error formats, e.g. cross-platform generic formats, human understandable formats
• CPC Class Codes: G06F 11/0778 Dumping, i.e. gathering error/state information after a fault for later diagnosis
• CPC Class Codes: G06F 11/079 Root cause analysis, i.e. error or fault diagnosis in a hardware test environment G06F11/22; in a software test environment G06F11/36
• CPC Class Codes: G06F 11/0793 Remedial or corrective actions recovery from an exception in an instruction pipeline G06F9/3861; by retry G06F11/1402; for recovering from a failure of a protocol instance or entity H04L69/40
• CPC Class Codes: G06F 11/366 using diagnostics G06F11/0703 takes precedence
• CPC Class Codes: G06F 11/3664 Environments for testing or debugging software

Abstract

A computer-implemented method assessing the risk of a future crash occurring on a computer system is disclosed. Crash results are received from a crash analysis system. The crash results are analyzed, at a processor, to determine the likelihood of the future crash occurring on the computer system. Information regarding the likelihood of the future crash occurring on the computer system is provided to a user of the computer system.

Claims

1. A computer-implemented method for assessing the risk of a future crash occurring on a computer system, said method comprising:

receiving crash results from a crash analysis system;

analyzing said crash results, at a processor, to determine the likelihood of said future crash occurring on said computer system, wherein said analyzing said crash results further comprises;

automatically determining a culprit module responsible for a crash of said computer system, said crash results corresponding to said crash; and

automatically generating a signature back trace, wherein said signature back trace pertains to a symptom of said crash of said computer system, and wherein said automatically determining a culprit module responsible for said crash of said computer system further comprises;

generating an essential stack of functions corresponding to said crash of said computer system;

determining a tag sequence and a tag depth corresponding to said essential stack of functions;

deriving a list of permissible tag permutations corresponding to said computer system; and

utilizing said tag sequence and said tag depth in combination with said list of permissible tag permutations to identify a culprit module responsible for said computer crash; and

providing information regarding said likelihood of said future crash occurring on said computer system to a user of said computer system.

2. The computer-implemented method of claim 1, wherein said analyzing said crash results further comprises:

analyzing said crash results to determine the likelihood of said future crash for a particular instance of software.

3. The computer-implemented method of claim 1, wherein said analyzing said crash results further comprises:

analyzing said crash results to determine the likelihood of said future crash for a particular instance of hardware.

4. The computer-implemented method of claim 1, wherein said analyzing said crash results further comprises:

analyzing said crash results to determine the likelihood of said future crash for a particular combination software and hardware.

5. The computer-implemented method of claim 1, wherein said analyzing said crash results further comprises:

analyzing said crash results to determine the likelihood of said future crash for a particular computational load.

6. The computer-implemented method of claim 1, wherein said analyzing said crash results further comprises:

analyzing said crash results to determine the likelihood of said future crash for a particular combination of two or more parameters, said parameters selected from the group consisting of;

instance of software, instance of hardware, and computational load.

7. The computer-implemented method of claim 1, wherein said analyzing said crash results further comprises:

assigning a ranking to said likelihood of said future crash occurring on said computer system.

8. The computer-implemented method of claim 1, wherein said providing information regarding said likelihood of said future crash occurring further comprises:

providing, on a portal accessible by said user of said computer system, said information regarding said likelihood of said future crash occurring on said computer system.

9. The computer-implemented method of claim 1, wherein said providing information regarding said likelihood of said future crash occurring further comprises:

sending a message to said user of said computer system, said message containing said information regarding said likelihood of said future crash occurring on said computer system.

10. A method for assessing the risk that a future crash will occur on a computer system, said method comprising:

receiving crash results which include a signature back trace, from said crash analysis system;

analyzing said crash results, at a processor, to determine the likelihood of

said future crash occurring on said computer system, said analyzing using at least one parameter selected from the group consisting of;

instance of software, instance of hardware, and computational load, wherein said analyzing said crash results further comprises;

automatically determining a culprit module responsible for a crash of said computer system, said crash results corresponding to said crash; and

automatically generating a signature back trace, wherein said signature back trace pertains to a symptom of said crash of said computer system, and wherein said automatically determining a culprit module responsible for said crash of said computer system further comprises;

generating an essential stack of functions corresponding to said crash of said computer system;

determining a tag sequence and a tag depth corresponding to said essential stack of functions;

deriving a list of permissible tag permutations corresponding to said computer system; and

utilizing said tag sequence and said tag depth in combination with said list of permissible tag permutations to identify a culprit module responsible for said computer crash; and

providing information regarding said likelihood of said future crash occurring on said computer system to a user of said computer system.

11. The method as recited in claim 10 wherein said analyzing said crash results further comprises:

comparing said results to a database of customers and their corresponding computer systems.

12. The method as recited in claim 10 wherein said analyzing said crash results further comprises:

assigning a ranking to said likelihood of said future crash occurring on said computer system.

13. The method as recited in claim 10, wherein said providing information regarding said likelihood of said future crash occurring on said computer system further comprises:

providing, on a portal accessible by said user of said computer system, said information regarding said likelihood of said future crash occurring on said computer system.

14. The method of claim 10, wherein said providing information regarding said likelihood of said future crash occurring further on said computer system comprises:

sending a message to said user of said computer system, said message containing said information regarding said likelihood of said future crash occurring on said computer system.