Mobile application performance prediction

US9635570B2 · US · B2

Patent metadata
FieldValue
Publication numberUS-9635570-B2
Application numberUS-201414243783-A
CountryUS
Kind codeB2
Filing dateApr 2, 2014
Priority dateApr 4, 2013
Publication dateApr 25, 2017
Grant dateApr 25, 2017

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  1. Title

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  2. Abstract

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  3. Assignees and inventors

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  4. Key dates

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  5. First independent claim

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  6. CPC / IPC classifications

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Abstract

Official abstract text for this publication.

The present invention provides methods of and systems for predicting performance of a mobile application. A first mobile application is installed on a first plurality of wireless mobile devices. Operational data resulting from operating the first mobile application on the first plurality of mobile devices is collected. A second mobile application is installed on a second plurality of mobile devices. Test data resulting from operating the second the mobile application on the second plurality of mobile devices is collected. The performance of the second mobile application is predicted using the operational data and the test data for combinations of mobile device configuration and wireless network connection type not represented by the second plurality of mobile devices.

First claim

Opening claim text (preview).

What is claimed is: 1. A method of predicting performance of a mobile application comprising: facilitating installation of a first mobile application on a first plurality of mobile device combinations comprising disparate combinations of mobile device configurations and wireless network connection types; collecting performance data resulting from operating the first mobile application on the first plurality of mobile device combinations, the performance data representing performance of the first mobile application for each respective disparate combination of the first plurality of mobile device combinations; facilitating installation of a second mobile application on a second plurality of mobile device combinations comprising disparate combinations of mobile device configurations and wireless network connection types, the second plurality of mobile device combinations being a smaller set of combinations than the first plurality of mobile device combinations; collecting test data resulting from operating the second mobile application on the second plurality of mobile device combinations, the test data representing performance of the second mobile application for each respective disparate combination of the second plurality of mobile device combinations; and predicting performance of the second mobile application on a first mobile device with a disparate combination of a mobile device configuration and a wireless network connection type that is not represented by the second plurality of mobile device combinations by: obtaining, from the test data, a subset of test data associated with operating the second mobile application on a second mobile device with a disparate combination of a mobile device configuration and wireless network connection type that is represented by the second plurality of mobile device combinations; obtaining a first set of performance data of the first mobile application operating on the second mobile device from the performance data; obtaining a second set of performance data of the first mobile application operating on the first mobile device from the performance data; generating a relative performance using the first set of performance data and the second set of performance data; and predicting performance of the second mobile application on the first mobile device by mathematically applying the relative performance to at least some of the subset of test data. 2. The method according to claim 1 , wherein the second mobile application is a modified version of the first mobile application. 3. The method according to claim 1 , wherein each of the mobile device configurations comprises a handset type and an operating system type. 4. The method according to claim 1 , wherein each of the wireless connection types comprise Wi-Fi networks and cellular networks. 5. The method according to claim 1 , wherein the first plurality of mobile device combinations further comprises disparate combinations of mobile device configurations, wireless network connection types, and geographical locations. 6. The method according to claim 1 , wherein the performance of the first mobile application represented by the performance data comprises one or more of: duration of network requests; battery drain; memory usage quantity; downloading latency; and runtime per function call. 7. The method according to claim 1 , wherein the performance of the first mobile application represented by the performance data comprises one or more of: low frame rate occurrences, network error occurrences and memory termination occurrences. 8. The method according to claim 1 , wherein said predicting performance comprises matching parameters of the collected performance data with parameters of the collected test data. 9. The method according to claim 8 , wherein said predicting performance further comprises predicting a value of a performance parameter for the second mobile application based on a value of a same performance parameter observed for the first mobile application. 10. The method according to claim 8 , wherein the matched parameters comprise mobile device configuration. 11. The method according to claim 8 wherein the matched parameters comprise wireless network connection type. 12. The method according to claim 8 , wherein the matched parameters comprise geographical location. 13. The method according to claim 8 , wherein the matched parameters comprise parameters other than available memory capacity and wherein said predicting performance comprises predicting performance for mobile device configurations having multiple different available memory capacities. 14. The method according to claim 8 , wherein said predicting performance further comprises determining a non-linear performance function from parameters of the performance test data and applying the non-linear performance function to a parameter of the collected test data. 15. The method according to claim 8 , wherein said predicting performance further comprises determining a distribution of outcomes for a parameter of the performance test data and using the distribution to predict outcomes for a parameter of the collected test data. 16. The method according to claim 15 , wherein the distribution of outcomes comprises a histogram. 17. The method according to claim 8 , wherein said predicting performance further comprises predicting a value of a first performance parameter for the second mobile application based on a value of a second performance parameter observed for the first mobile application, wherein the second performance parameter is different from the first performance parameter. 18. The method according to claim 17 , wherein the matched parameters comprise the second performance parameter. 19. The method according to claim 1 , further comprising distributing the second mobile application to a group of wireless mobile devices if the predicted performance of the second mobile application is satisfactory and, otherwise, developing a third mobile application by modifying the second mobile application. 20. The method according to claim 19 , further comprising: installing the third mobile application on a third plurality of mobile device combinations; collecting test data resulting from operating the third mobile application on the third plurality of mobile device combinations; and predicting performance of the third mobile application using the performance data resulting from operating the first mobile application on the first plurality of mobile device combinations, and the test data resulting from operating the third mobile application on the third plurality of mobile device combinations. 21. The method according to claim 1 , further comprising predicting a plurality of performance parameters; and assigning different statistical confidence levels to the predicted performance parameters of the plurality of performance parameters. 22. The method according to claim 1 , wherein the first and second mobile applications comprise a performance library that monitors performance of the application. 23. A system for predicting performance of a mobile application comprising a performance prediction server configured to: receive performance data resulting from operating a first mobile application on a first plurality of mobile device combinations comprising disparate combinations of mobile device configurations and wireless network connection types, the performance data representing performance of the first mobile

Assignees

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Classifications

  • Arrangements for maintaining operational condition · CPC title

  • H04W24/08Primary

    Testing, {supervising or monitoring} using real traffic · CPC title

  • Prevention of errors by analysis, debugging or testing of software · CPC title

  • Electricity · mapped topic

  • Monitoring arrangements for monitoring environmental properties or parameters of the computing system or of the computing system component, e.g. monitoring of power, currents, temperature, humidity, position, vibrations (thermal management in cooling arrangements of a computing system G06F1/206) · CPC title

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What does patent US9635570B2 cover?
The present invention provides methods of and systems for predicting performance of a mobile application. A first mobile application is installed on a first plurality of wireless mobile devices. Operational data resulting from operating the first mobile application on the first plurality of mobile devices is collected. A second mobile application is installed on a second plurality of mobile dev…
Who is the assignee on this patent?
Google Inc
What technology area does this patent fall under?
Primary CPC classification H04W24/08. Mapped technology areas include Electricity.
When was this patent published?
Publication date Tue Apr 25 2017 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 8 related publications on this page (citations in our corpus or others sharing the same primary CPC).