Application performance measurement and reporting

• US 9,311,211 B2
• Filed: 02/28/2012
• Issued: 04/12/2016
• Est. Priority Date: 07/28/2011
• Status: Active Grant

• Current Assignee: TATA Consultancy Services Limited (Tata Sons Pvt Ltd.)
• Original Assignee: TATA Consultancy Services Limited (Tata Sons Pvt Ltd.)
• Inventors: Chatterjee, Swarup, Chowdhury, Kallol Saha, Sengupta, Somnath
• Primary Examiner(s): Breene, John
• Assistant Examiner(s): Dinh, Lynda
• Application Number:
  US13/407,572
• Publication Number:
  US 20130030764A1
• Time in Patent Office: 1,505 Days
• Field of Search: 702/182
• US Class Current: 1/1
• CPC Class Codes: G06F 11/3409 for performance assessment
• CPC Class Codes: G06F 11/3414 Workload generation, e.g. scripts, playback
• CPC Class Codes: G06F 11/3452 Performance evaluation by statistical analysis
• CPC Class Codes: G06F 15/02 manually operated with input through keyboard and computation using a built-in program, e.g. pocket calculators
• CPC Class Codes: G06F 15/0216 Constructional details or arrangements

Abstract

Systems and methods related to performance measurement and reporting are described. In one method, a first application is profiled in a first profiling session to generate a first parameter dataset related to performance of segments of the first application. A session report is created based on the first parameter dataset. Further, based in part on the session report, comments for one or more of the segments of the application are received. A consolidated report is then generated based on the first parameter dataset and the comments.

Claims

1. A computer implemented method for application performance measurement and reporting, the method comprising a processor executing instructions stored in a memory to perform:

generating, in a first profiling session, a first parameter dataset related to performance of an application, wherein generating the first parameter dataset comprises executing the segments in the first profiling session and measuring performance parameters to obtain the first parameter dataset, wherein the performance parameters comprise at least one of processor utilization, memory utilization, network utilization, input-output utilization, database queries statistics, response time related statistics, session related statistics, throughput statistics, process thread statistics, and queue related statistics;

creating a session report based on the first parameter dataset;

receiving comments for one or more of the segments of the application, based in part on the session report;

providing a consolidated report based on the first parameter dataset and the comments;

receiving a second parameter dataset corresponding to a second application profiled in a second profiling session;

identifying common segments between a first application and a second application; and

generating a comparison report for at least one of the common segments, based on the first parameter dataset and the second parameter dataset, wherein the comments relate to at least one of a hardware setup, runtime conditions, a part of the first application, a session timing and a duration of the session.

2. The computer implemented method as claimed in claim 1, further comprising:

determining whether a performance parameter in the first parameter dataset lies outside a pre-specified range; and

prompting one or more users to provide the comments based on a positive determination.

3. The computer implemented method as claimed in claim 2, wherein the comments received from the one or more users are visually differentiated based on at least one of a user name and a network ID.

4. The computer implemented method as claimed in claim 1, wherein the second application is at least one of the first application and a modified version of the first application.

5. The computer implemented method as claimed in claim 1, wherein the second profiling session differs from the first profiling session in at least one of a hardware setup, runtime conditions, a session timing and a duration of the session.

6. The computer implemented method as claimed in claim 1, wherein the comparison report includes at least one comment received based in part on the session report.

7. A system for performance measurement and reporting, the system comprising:

a processor;

a user interface;

a network interface; and

a memory coupled to the processor, the memory comprising;

a profiling module configured to profile performance of a first application and generate a first parameter dataset related to segments executed in the first application, wherein the first parameter dataset is generated by executing the segments in the first profiling session and measuring performance parameters to obtain the first parameter dataset, wherein the performance parameters comprise at least one of processor utilization, memory utilization, network utilization, input-output utilization, database queries statistics, response time related statistics, session related statistics, throughput statistics, process thread statistics, and queue related statistics;

a reporting module configured to,

receive comments for altering performance of one or more of the segments; and

generate reports based on at least one of the first parameter dataset and the comments;

a comparison module configured to identify common segments between two or more applications, wherein the reporting module is further configured to generate a comparison report for comparing performance of one or more of the common segments, and wherein the comments relate to at least one of a hardware setup, runtime conditions, a part of the first application, a session timing and a duration of the session.

8. The system as claimed in claim 7, wherein the reporting module is further configured to:

determine whether at least one data point in the first parameter dataset deviates from a pre-specified range; and

indicate the deviation in a session report based on a positive determination.

9. The system as claimed in claim 7, wherein the reporting module is further configured to:

determine whether the performance of one or more of the common segments has changed across the two or more applications; and

indicate a change in the performance, in a comparison report, based on a positive determination.

10. A non-transitory computer-readable medium having embodied thereon a computer program for processor readable code stored thereon, the processor executing a method comprising:

generating a first parameter dataset related to performance of an application in a first profiling session, wherein the generating the first parameter dataset comprises executing the segments in the first profiling session and measuring performance parameters to obtain the first parameter dataset, wherein the performance parameters comprise at least one of processor utilization, memory utilization, network utilization, input-output utilization, database queries statistics, response time related statistics, session related statistics, throughput statistics, process thread statistics, and queue related statistics;

obtaining a second parameter dataset corresponding to a second profiling session, wherein said second parameter dataset relates to a second application; and

providing a comparison report based on the first parameter dataset and the second parameter dataset, wherein the comparison report further includes comments associated with an application profiled in at least one of the first profiling session and the second profiling session, wherein the comments relate to at least one of a hardware setup, runtime conditions, a part of the application, a session timing and a duration of the session.

11. The non-transitory computer-readable medium as claimed in claim 10, wherein the method further comprises:

creating a session report based on the first parameter dataset;

receiving the comments for one or more segments of the application, based in part on the session report; and

providing a consolidated report based on the user comments and the session report.

12. The non-transitory computer-readable medium as claimed in claim 10, wherein the second profiling session differs from the first profiling session in at least one of a hardware setup, runtime conditions, a session timing and a duration of the session.

13. The non-transitory computer-readable medium as claimed in claim 10, wherein the method further comprises:

identifying common segments between applications profiled in the first profiling session and the second profiling session; and

generating the comparison report for one or more of the common segments, based on the first parameter dataset and the second parameter dataset.

14. The non-transitory computer-readable medium as claimed in claim 13, wherein the generating the comparison report comprises indicating changes in performance parameters of the one or more of the common segments.