Granted Patent B2

US 11,886,296 · App. 17/186,648 · Granted Jan 30, 2024

Inventors: Wei-Ta Chen (Pflugerville, TX); Landon Martin Chambers (Round Rock, TX); John Li (Austin, TX)

Assignee: Dell Products L.P.

G06F11/1433G06F8/61G06F11/366G06F2201/865

Abstract

Claims (73)

1. An apparatus comprising at least one processing device comprising a processor coupled to memory, the at least one processing device being configured:

to obtain information about driver installations of a given driver on a plurality of computing devices from the plurality of computing devices;

to obtain information about system failures from the plurality of computing devices;

to determine a correlation between the driver installations of the given driver on the plurality of computing devices and the system failures;

to determine that the given driver is likely to cause at least one of the system failures based at least in part on the determined correlation between the driver installations of the given driver on the plurality of computing devices and the system failures; and

to provide an indication that the given driver is likely to cause at least one of the system failures to a given computing device, the indication being configured to cause the given computing device to inhibit a presentation of a recommendation to install the given driver to a user of the given computing device;

wherein the at least one processing device is further configured to determine a failure rate cutoff value; and

determining that the given driver is likely to cause at least one of the system failures based at least in part on the determined correlation between the driver installations of the given driver on the plurality of computing devices and the system failures comprises determining that a rate of the system failures is greater than the failure rate cutoff value.

2. The apparatus of claim 1 wherein determining the correlation between the driver installations of the given driver on the plurality of computing devices and the system failures comprises filtering the information about the system failures to a pre-determined amount of time subsequent to the driver installations of the given driver on each of the plurality of computing devices.

3. The apparatus of claim 1 wherein:

a first sub-set of the plurality of computing devices comprises a first configuration type and a second sub-set of the plurality of computing devices comprises a second configuration type that is different than the first configuration type; and

determining the correlation between the driver installations of the given driver on the plurality of computing devices and the system failures comprises determining a correlation between the driver installations of the given driver on computing devices having the first configuration type and the system failures for computing devices having the first configuration type based at least in part on the driver installations of the given driver on the first sub-set of the plurality of computing devices and system failures of the first sub-set of the plurality of computing devices.

4. The apparatus of claim 3 wherein the given computing device is different than the plurality of computing devices and comprises the first configuration type.

5. The apparatus of claim 1 wherein:

the at least one processing device is further configured:

to determine a minimum sample size of the driver installations of the given driver on the plurality of computing devices; and

to determine that the minimum sample size has been met based at least in part on the obtained information about the driver installations of the given driver on the plurality of computing devices; and

determining the correlation comprises determining the correlation based at least in part on the determination that the minimum sample size has been met.

6. The apparatus of claim 1 wherein:

the at least one processing device is further configured:

to wait a predetermined period of time between determining that the given driver is likely to cause at least one of the system failures and providing the indication that the given driver is likely to cause at least one of the system failures to the given computing device; and

based at least in part on an expiration of the predetermined period of time, to determine that the given driver is still likely to cause at least one of the system failures; and

providing the indication that the given driver is likely to cause at least one of the system failures to the given computing device comprises providing the indication that the given driver is likely to cause at least one of the system failures to the given computing device based at least in part on the determination that the given driver is still likely to cause at least one of the system failures.

7. The apparatus of claim 1 wherein the failure rate cutoff value is determined at least in part utilizing a machine learning technique.

8. A method comprising:

obtaining information about driver installations of a given driver on a plurality of computing devices from the plurality of computing devices;

obtaining information about system failures from the plurality of computing devices;

determining a correlation between the driver installations of the given driver on the plurality of computing devices and the system failures;

determining that the given driver is likely to cause at least one of the system failures based at least in part on the determined correlation between the driver installations of the given driver on the plurality of computing devices and the system failures; and

providing an indication that the given driver is likely to cause at least one of the system failures to a given computing device, the indication being configured to cause the given computing device to inhibit a presentation of a recommendation to install the given driver to a user of the given computing device;

wherein the method further comprises determining a failure rate cutoff value; and

determining that the given driver is likely to cause at least one of the system failures based at least in part on the determined correlation between the driver installations of the given driver on the plurality of computing devices and the system failures comprises determining that a rate of the system failures is greater than the failure rate cutoff value;

wherein the method is implemented by at least one processing device comprising a processor coupled to memory.

9. The method of claim 8 wherein determining the correlation between the driver installations of the given driver on the plurality of computing devices and the system failures comprises filtering the information about the system failures to a pre-determined amount of time subsequent to the driver installations of the given driver on each of the plurality of computing devices.

10. The method of claim 8 wherein:

a first sub-set of the plurality of computing devices comprises a first configuration type and a second sub-set of the plurality of computing devices comprises a second configuration type that is different than the first configuration type; and

determining the correlation between the driver installations of the given driver on the plurality of computing devices and the system failures comprises determining a correlation between the driver installations of the given driver on computing devices having the first configuration type and the system failures for computing devices having the first configuration type based at least in part on the driver installations of the given driver on the first sub-set of the plurality of computing devices and system failures of the first sub-set of the plurality of computing devices.

11. The method of claim 10 wherein the given computing device is different than the plurality of computing devices and comprises the first configuration type.

12. The method of claim 8 wherein:

the method further comprises:

determining a minimum sample size of the driver installations of the given driver on the plurality of computing devices; and

determining that the minimum sample size has been met based at least in part on the obtained information about the driver installations of the given driver on the plurality of computing devices; and

determining the correlation comprises determining the correlation based at least in part on the determination that the minimum sample size has been met.

13. The method of claim 8 wherein:

the method further comprises:

waiting a predetermined period of time between determining that the given driver is likely to cause at least one of the system failures and providing the indication that the given driver is likely to cause at least one of the system failures to the given computing device; and

based at least in part on an expiration of the predetermined period of time, determining that the given driver is still likely to cause at least one of the system failures; and

providing the indication that the given driver is likely to cause at least one of the system failures to the given computing device comprises providing the indication that the given driver is likely to cause at least one of the system failures to the given computing device based at least in part on the determination that the given driver is still likely to cause at least one of the system failures.

14. The method of claim 8 wherein the failure rate cutoff value is determined at least in part utilizing a machine learning technique.

15. A computer program product comprising a non-transitory processor-readable storage medium having stored therein program code of one or more software programs, wherein the program code when executed by at least one processing device, the at least one processing device comprising a processor coupled to memory, causes the at least one processing device:

to obtain information about driver installations of a given driver on a plurality of computing devices from the plurality of computing devices;

to obtain information about system failures from the plurality of computing devices;

to determine a correlation between the driver installations of the given driver on the plurality of computing devices and the system failures;

to determine that the given driver is likely to cause at least one of the system failures based at least in part on the determined correlation between the driver installations of the given driver on the plurality of computing devices and the system failures; and

to provide an indication that the given driver is likely to cause at least one of the system failures to a given computing device, the indication being configured to cause the given computing device to inhibit a presentation of a recommendation to install the given driver to a user of the given computing device;

wherein the program code when executed further causes the at least one processing device to determine a failure rate cutoff value; and

determining that the given driver is likely to cause at least one of the system failures based at least in part on the determined correlation between the driver installations of the given driver on the plurality of computing devices and the system failures comprises determining that a rate of the system failures is greater than the failure rate cutoff value.

16. The computer program product of claim 15 wherein determining the correlation between the driver installations of the given driver on the plurality of computing devices and the system failures comprises filtering the information about the system failures to a pre-determined amount of time subsequent to the driver installations of the given driver on each of the plurality of computing devices.

17. The computer program product of claim 15 wherein:

a first sub-set of the plurality of computing devices comprises a first configuration type and a second sub-set of the plurality of computing devices comprises a second configuration type that is different than the first configuration type;

determining the correlation between the driver installations of the given driver on the plurality of computing devices and the system failures comprises determining a correlation between the driver installations of the given driver on computing devices having the first configuration type and the system failures for computing devices having the first configuration type based at least in part on the driver installations of the given driver on the first sub-set of the plurality of computing devices and system failures of the first sub-set of the plurality of computing devices; and

the given computing device is different than the plurality of computing devices and comprises the first configuration type.

18. The computer program product of claim 15 wherein:

the program code further causes the at least one processing device:

to determine a minimum sample size of the driver installations of the given driver on the plurality of computing devices; and

to determine that the minimum sample size has been met based at least in part on the obtained information about the driver installations of the given driver on the plurality of computing devices; and

determining the correlation comprises determining the correlation based at least in part on the determination that the minimum sample size has been met.

19. The computer program product of claim 15 wherein:

the program code further causes the at least one processing device:

to wait a predetermined period of time between determining that the given driver is likely to cause at least one of the system failures and providing the indication that the given driver is likely to cause at least one of the system failures to the given computing device; and

based at least in part on an expiration of the predetermined period of time, to determine that the given driver is still likely to cause at least one of the system failures; and

providing the indication that the given driver is likely to cause at least one of the system failures to the given computing device comprises providing the indication that the given driver is likely to cause at least one of the system failures to the given computing device based at least in part on the determination that the given driver is still likely to cause at least one of the system failures.

20. The computer program product of claim 15 wherein the failure rate cutoff value is determined at least in part utilizing a machine learning technique.

Assignments (10)

Continuity (1)

Cited By (1)

US 12,541,352