System and methods for application activity capture, error identification, and error correction

• US 10,445,220 B2
• Filed: 01/25/2017
• Issued: 10/15/2019
• Est. Priority Date: 01/25/2017
• Status: Active Grant

• Current Assignee: Verizon Patent and Licensing Incorporated (Verizon Communications Inc.)
• Original Assignee: Verizon Patent and Licensing Incorporated (Verizon Communications Inc.)
• Inventors: Shanmugam, Sankar, Sundaraju, Sridhar, John, Suja, Sivaganesh, Sivagnanalingam
• Primary Examiner(s): Truong, Loan L. T.
• Application Number:
  US15/415,418
• Publication Number:
  US 20180210808A1
• Time in Patent Office: 993 Days
• CPC Class Codes: G06F 11/366 using diagnostics G06F11/0703 takes precedence
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: H04L 41/5067 Customer-centric QoS measurements

Abstract

A device may obtain data regarding application activity from a group of user devices. The application activity may relate to an application associated with network operator services provided by a network operator. The device may process the data regarding the application activity to generate a visualization of the application. The visualization of the application activity may include multiple tiers. The multiple tiers may correspond to at least a group of users, a user, and a session. The visualization may identify one or more errors associated with the application activity. The device may provide the visualization of the application activity for display. The visualization may be provided for display via a client device associated with the network operator. The device may automatically implement, without human intervention, a correction to the one or more errors.

Claims

1. A device, comprising:

one or more processors to;

obtain data regarding application activity from a group of user devices,

the application activity relating to an application associated with services provided by a network operator, and

the data regarding the application activity including logs of user interactions with the application,

the logs of user interactions mapping user experiences for sessions associated with utilization of the application;

process the data regarding the application activity to generate a visualization of the application activity,

the visualization including multiple tiers,

a first tier, of the multiple tiers, relating to the group of user devices,

 

the first tier being associated with a first flow diagram having first nodes representing first activity groups that indicate a first portion of the application activity associated with the group of user devices,

a second tier, of the multiple tiers, relating to a particular user device of the group of user devices,

 

the second tier being associated with a second flow diagram having second nodes representing second activity groups that indicate a second portion of the application activity associated with the particular user device, and

a third tier, of the multiple tiers, relating to a particular session of utilization of the application by the particular user device,

 

the third tier being associated with a third flow diagram having third nodes representing third activity groups that indicate a third portion of the application activity associated with the particular session;

the visualization identifying one or more errors associated with the application activity, and

the visualization providing at least one activity count specifying traversal of a respective application activity associated with at least one of the first activity groups, the second activity groups, or the third activity groups;

provide the visualization for display,

the visualization being provided for display via a client device associated with the network operator; and

automatically implement, without human intervention, a correction to the one or more errors.

2. The device of claim 1, where the one or more processors, when processing the data, are to:

process the data using a machine learning technique.

3. The device of claim 1, where the one or more processors, when processing the data, are to:

process the data to generate the first flow diagram, the second flow diagram, and the third flow diagram,

each of the first flow diagram, the second flow diagram, and the third flow diagram representing a respective path of user interactions with the application.

4. The device of claim 1, where the one or more processors, when obtaining the data, are to:

obtain the data using at least one of;

an NGINX server,

an MQ server,

an IBM stream,

a Kafka Q server, or

a Hadoop system.

5. The device of claim 1, where the one or more processors, when processing the data, are to:

group a subset of log entries based on timestamp information of the subset of log entries; and

generate the visualization based on the subset of log entries.

6. The device of claim 1, where the one or more processors are further to:

identify the one or more errors associated with the application activity based on processing the data;

generate a recommendation identifying the correction to the one or more errors; and

provide information identifying the recommendation for display.

7. The device of claim 1, where the one or more processors, when automatically implementing the correction, are to:

automatically alter the application to implement the correction to the one or more errors.

20. The device of claim 1, where the logs of user interactions with the application comprise a consolidated log file associated with multiple time periods or multiple user devices.

8. A system, comprising:

one or more computing resources to implement;

a web server to provide an interface to obtain application activity data regarding application activity of a group of user devices,

the application activity data including logs of user interactions with an application, and

the logs of user interactions mapping user experiences for sessions associated with utilization of the application;

a message queuing server to obtain the application activity data from the web server and queue the application activity data for processing;

an analytics server to process the application activity data; and

a front-end server to generate a visualization based on processing the application activity data and provide the visualization for display via a client device,

the visualization including multiple tiers,

a first tier, of the multiple tiers, relating to the group of user devices,

 

the first tier being associated with a first flow diagram having first nodes representing first activity groups that indicate a first portion of the application activity associated with the group of user devices;

a second tier, of the multiple tiers, relating to a particular user device of the group of user devices,

 

the second tier being associated with a second flow diagram having second nodes representing second activity groups that indicate a second portion of the application activity associated with the particular user device; and

a third tier, of the multiple tiers, relating to a particular session of utilization of the application by the particular user device,

 

the third tier being associated with a third flow diagram having third nodes representing third activity groups that indicate a third portion of the application activity associated with the particular session; and

the visualization providing at least one activity count specifying traversal of a respective application activity associated with at least one of the first activity groups, the second activity groups, or the third activity groups.

9. The system of claim 8, where the analytics server further comprises:

a recommendation server to generate a recommendation to correct an error with the application based on the application activity data.

10. The system of claim 8, where each of the first flow diagram, the second flow diagram, and the third flow diagram depict functionalities of the application.

11. The system of claim 10, where each of the first flow diagram, the second flow diagram, and the third flow diagram represent a transfer of the application activity from a first functionality of the functionalities to a second functionality of the functionalities.

12. The system of claim 8, further comprising:

an error identification computing resource to identify an error in the application based on the application activity data.

13. The system of claim 8, further comprising:

a data acquisition computing resource to acquire data from one or more point of sale devices and provide the data to the analytics server to process with the application activity data.

14. A non-transitory computer-readable medium storing instructions, the instructions comprising:

one or more instructions that, when executed by one or more processors, cause the one or more processors to;

obtain data regarding application activity from a group of user devices,

the application activity relating to an application associated with network operator services provided by a network operator, and

the data regarding the application activity including logs of user interactions with the application,

the logs of user interactions mapping user experiences for sessions associated with utilization of the application;

process the data regarding the application activity to generate a visualization of the application activity,

the visualization including multiple tiers,

a first tier, of the multiple tiers, relating to the group of user devices,

 

the first tier being associated with a first flow diagram having first nodes representing first activity groups that indicate a first portion of the application activity associated with the group of user devices,

a second tier, of the multiple tiers, relating to a particular user device of the group of user devices,

 

the second tier being associated with a second flow diagram having second nodes representing second activity groups that indicate a second portion of the application activity associated with the particular user device, and

a third tier, of the multiple tiers, relating to a particular session of utilization of the application by the particular user device,

 

the third tier being associated with a third flow diagram having third nodes representing third activity groups that indicate a third portion of the application activity associated with the particular session;

the visualization identifying one or more errors associated with the application activity, and

the visualization providing at least one activity count specifying traversal of a respective application activity associated with at least one of the first activity groups, the second activity groups, or the third activity groups;

provide the visualization for display,

the visualization being provided for display via a client device associated with the network operator; and

implement a recommendation to remediate the one or more errors associated with the application activity.

15. The non-transitory computer-readable medium of claim 14, where the one or more instructions, when executed by the one or more processors, further cause the one or more processors to:

receive a selection of the recommendation based on providing the visualization; and

where the one or more instructions, that cause the one or more processors to implement the recommendation, cause the one or more processors to;

implement the recommendation based on receiving the selection of the recommendation.

16. The non-transitory computer-readable medium of claim 14, where the one or more instructions, when executed by the one or more processors, further cause the one or more processors to:

generate the recommendation based on processing the data.

17. The non-transitory computer-readable medium of claim 16, where the one or more instructions, that cause the one or more processors to generate the recommendation, cause the one or more processors to:

generate the recommendation using at least one of;

a machine learning technique,

a heuristic technique, or

a pattern recognition technique.

18. The non-transitory computer-readable medium of claim 14, where the one or more instructions, when executed by the one or more processors, further cause the one or more processors to:

obtain the data regarding the application activity in near real-time relative to one or more events associated with the application.

19. The non-transitory computer-readable medium of claim 14, where the application activity relates to at least one of:

a set-up activity,

a billing activity,

a purchasing activity,

an upgrading activity, or

a usage review activity.