Identifying relationships between applications

• US 9,454,565 B1
• Filed: 06/25/2013
• Issued: 09/27/2016
• Est. Priority Date: 06/25/2013
• Status: Active Grant

• Current Assignee: Amazon Technologies, Inc. (Amazon.com, Inc.)
• Original Assignee: Amazon Technologies, Inc. (Amazon.com, Inc.)
• Inventors: Evans, Ethan Zane, Markley, David Allen
• Primary Examiner(s): Stevens, Robert
• Application Number:
  US13/926,215
• Time in Patent Office: 1,190 Days
• Field of Search: 707/758, 707/736
• US Class Current: 1/1
• CPC Class Codes: G06F 16/24 Querying

Abstract

In various embodiments, static, dynamic, and behavioral analysis may be performed on an application. A set of software libraries or code fragments employed by the application may be determined. A set of device resources employed by the application may be determined. An application fingerprint is generated for the application. The application fingerprint encodes identifiers for the set of software libraries or code fragments and identifiers for the set of device resources.

Claims

1. A non-transitory computer-readable medium having a computer-executable program stored thereon that, when executed by at least one computing device, configures the at least one computing device to perform operations comprising:

identifying an application in an application marketplace;

identifying a plurality of other applications within a category in which the application is associated;

executing an instance of the application;

performing, in response to executing the instance, an analysis of a set of code fragments employed by the instance and an analysis of a set of device resources employed by the instance;

determining a resource consumption profile employed by the application based at least in part on the analysis of the set of code fragments and the analysis of the set of device resources;

performing an analysis of usage data associated with the instance that is executed;

generating an application fingerprint of the application based at least in part upon the analysis of the set of code fragments, the analysis of the set of device resources, and the analysis of the usage data, the application fingerprint comprising unique identifiers corresponding to the set of code fragments, the set of device resources, the resource consumption profile, and the usage data;

identifying, based at least in part upon the application fingerprint and respective fingerprints of the plurality of other applications within the category, a subset of the plurality of applications within the category employing at least one of a threshold number of common code fragments or a threshold number of common device resources relative to the application; and

identifying at least one difference between each of the subset of the plurality of applications and the application based at least in part upon the application fingerprint of the application.

2. The non-transitory computer-readable medium of claim 1, wherein the common device resource comprises use of at least one of:

a device orientation detection capability, a location detection capability, a display capability, or an audio capability.

3. The non-transitory computer-readable medium of claim 1, wherein the operations further comprise identifying a performance metric associated with the application and the subset of the plurality of other applications.

4. The non-transitory computer-readable medium of claim 3, wherein the operations further comprise ranking the subset of the plurality of other applications according to a similarity to the application.

5. The non-transitory computer-readable medium of claim 1, wherein the usage data further comprises an amount of network traffic originating from the application.

6. The non-transitory computer-readable medium of claim 1, wherein the subset of the plurality of other applications is further identified based at least in part upon the respective fingerprints of the plurality of other applications indicating a respective frame rate associated with content rendered by each of the subset of the plurality of other applications that is within a threshold percentage of a frame rate associated with content rendered on a display device by the application.

7. A system, comprising:

at least one computing device; and

at least one service executable in the at least one computing device, the at least one service configured to cause the at least one computing device to;

execute an instance of an application;

perform, in response to executing the instance, an analysis of a set of code fragments employed by the instance and an analysis of a set of device resources employed by the instance;

obtain an application fingerprint for the application, the application fingerprint based at least in part on the analysis of the set of code fragments employed by the instance, the analysis of the set of device resources employed by the instance, a resource consumption profile, and usage data associated with the instance;

identify a plurality of other applications within a common category of the application in an application marketplace; and

identify a refined set of applications from the common category, the refined set of applications being a subset of the plurality of other applications within the common category and being identified based at least in part upon an analysis of the application fingerprint and an analysis of a respective plurality of application fingerprints of the refined set of applications, wherein the refined set of applications employs at least one of a threshold number of common code fragments or a threshold number of common device resources relative to the application.

8. The system of claim 7, wherein the at least one service that causes the at least one computing device to identify the refined set of applications further causes the at least one computing device to rank the plurality of other applications according to a binary data similarity metric.

9. The system of claim 7, wherein the at least one service that causes the at least one computing device to identify the refined set of applications further causes the at least one computing device to identify at least one application from the plurality of other applications having a respective application fingerprint indicating a respective frame rate associated with content rendered by the at least one application that is within a threshold percentage of a frame rate associated with content rendered on a display device by the application.

10. The system of claim 7, wherein the at least one service that causes the at least one computing device to identify the refined set of applications further causes the at least one computing device to identify at least one application from the plurality of other applications having a respective application fingerprint indicating a threshold percentage of downloads of the at least one application being performed by a set of users sharing an attribute with another set of users who have downloaded the application as indicated by the application fingerprint.

11. The system of claim 7, wherein the at least one service that causes the at least one computing device to identify the refined set of applications further causes the at least one computing device to identify applications within the application marketplace having a respective application fingerprint indicating that the applications are added to the application marketplace within a predefined period of time.

12. The system of claim 7, wherein the at least one service further causes the at least one computing device to identify another refined set of applications from the common category, the another refined set of applications differing from the application based at least in part upon the analysis of the application fingerprint and a respective plurality of application fingerprints of the another refined set of applications.

13. The system of claim 12, wherein each of the other refined set of applications differs from the application by employing at least one code fragment that the application does not employ.

14. The system of claim 12, wherein each of the other refined set of applications differs from the application by employing at least one device resource that the application does not employ.

15. The system of claim 7, wherein the at least one service further causes the at least one computing device to rank the refined set of applications based at least in part upon a number common code fragments employed relative to the application.

16. The system of claim 7, wherein the at least one service further causes the at least one computing device to rank the refined set of applications based at least in part upon a number common device resources employed relative to the application.

17. A method, comprising:

identifying, by at least one computing device, an application in an application marketplace;

executing, by the at least one computing device, an instance of the application;

obtaining, by the at least one computing device, an application fingerprint for the application, the application fingerprint based at least in part upon a static analysis of the application, a dynamic analysis of the instance, and a behavioral analysis of usage of the application by a plurality of users of the application marketplace;

extracting, by the at least one computing device, usage data associated with the behavioral analysis of usage from the application fingerprint, the usage data associated with the plurality of users of the application marketplace;

identifying, by the at least one computing device, usage of the application with respect to a plurality of aspects of the application from the usage data; and

generating, by the at least one computing device, a recommendation with respect to modifying the plurality of aspects based at least in part upon the usage of the application with respect to the plurality of aspects by identifying an aspect among the plurality of aspects of the application at which usage of the application according to the usage data decreases by a threshold percentage.

18. The method of claim 17, wherein the plurality of aspects of the application comprise at least one of:

a level within a game application, a map within the game application, a difficulty setting within the game application, a screen within the application, a feature provided by the application, or a portion of the application.

19. The method of claim 17, wherein generating the recommendation with respect to modifying the plurality of aspects comprises identifying an aspect of the application associated with a population of users for whom usage of the application according to the usage data decreases by the threshold percentage.

20. The method of claim 19, further comprising identifying the population of users, wherein the population of users comprises a subset of the plurality of users of the application marketplace, the subset being identified according to a demographic attribute.

21. The method of claim 17, wherein generating the recommendation with respect to modifying the plurality of aspects comprises generating reporting data identifying a number of users according to usage of the application associated with a plurality of aspects of the application.

22. The method of claim 17, wherein the aspect among the plurality of aspects corresponds to a particular level within the application and the recommendation comprises adjusting the particular level of the application.