Optimization analysis using similar frequencies

• US 9,658,936 B2
• Filed: 12/24/2014
• Issued: 05/23/2017
• Est. Priority Date: 02/12/2013
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Inventors: Li, Ying, Krajec, Russell S.
• Primary Examiner(s): Sough, H S
• Assistant Examiner(s): Duncan, Timothy
• Application Number:
  US14/582,973
• Publication Number:
  US 20150301920A1
• Time in Patent Office: 881 Days
• Field of Search: None
• CPC Class Codes: G06F 11/3466 Performance evaluation by tracing or monitoring
• CPC Class Codes: G06F 11/3476 Data logging G06F11/14, G06F11/2205 take precedence
• CPC Class Codes: G06F 11/3604 Software analysis for verifying properties of programs byte-code verification G06F9/44589
• CPC Class Codes: G06F 11/3636 by tracing the execution of the program
• CPC Class Codes: G06F 11/3644 by instrumenting at runtime
• CPC Class Codes: G06F 2201/865 Monitoring of software

Abstract

Periodicity similarity between two different tracer objectives may be used to identify additional input parameters to sample. The tracer objectives may be individual portions of a large tracer operation, and each of the tracer objectives may have separate set of input objects for which data may be collected. After collecting data for a tracer objective, other tracer objectives with similar periodicities may be identified. The input objects from the other tracer objectives may be added to a tracer objective and the tracer objective may be executed to determine a statistical significance of the newly added objective. An iterative process may traverse multiple input objects until exhausting possible input objects and a statistically significant set of input objects are identified.

Claims

1. A method performed in a computing environment for optimizing analysis of a computer application by optimizing a tracer objective in order to enable improved operation of the application when operated in a computer system, said method comprising:

identifying a plurality of tracer objectives of an application;

identifying a frequency profile for each of the plurality of tracer objectives;

for a given tracer objective, identifying an input parameter of at least one other tracer objective;

scoring the input parameter at least in part based on similarity between the frequency profile of the at least one other tracer objective and the frequency profile of the given tracer objective;

comparing the scored input parameter to a relevance threshold; and

based at least in part on the input parameter scoring above the relevance threshold, selectively adding the input parameter to the given tracer objective.

2. The method of claim 1, further comprising, for the given tracer objective, sorting a plurality of other tracer objectives according to similarity of frequency profiles of the other tracer objectives to the frequency profile of the given tracer objective.

3. The method of claim 1, further comprising iterating by identifying additional input parameters of the at least one other tracer objective, scoring the additional input parameters at least in part based on similarity between the frequency profile of the at least one other tracer objective and the frequency profile of the given tracer objective, comparing the scored input parameters to a relevance threshold, and adding the additional input parameters to the given tracer objective when the additional input parameters score above the relevance threshold.

4. The method of claim 1, further comprising executing the plurality of tracer objectives in the application in order to perform a periodicity analysis to generate the frequency profiles of the plurality of tracer objectives.

5. The method of claim 1, wherein scoring the input parameter further includes determining an influence factor of the input parameter with respect to the at least one other tracer objective.

6. The method of claim 5, wherein scoring the input parameter includes multiplying the influence factor with a similarity score, the similarity score being based on the similarity between the frequency profile of the at least one other tracer objective and the frequency profile of the given tracer objective.

7. The method of claim 1, wherein the relevance threshold represents a score indicating statistical relevance of the input parameter to a set of results generated when the given tracer objective is executed.

8. The method of claim 1, wherein at least one of the frequency profiles includes multiple frequencies and the intensity and/or strength of the multiple frequencies.

9. The method of claim 1, further comprising identifying an input parameter of the given tracer objective, scoring the input parameter of the given tracer objective and comparing the scored input parameter of the given tracer objective to the relevance threshold, and based on the input parameter of the given tracer objective scoring below the relevance threshold, removing the input parameter from the given tracer objective.

10. A computing system configured to optimize analysis of a computer application by optimizing a tracer objective in order to enable improved operation of the application, the system comprising:

one or more processors; and

one or more computer readable media having stored thereon instructions that are executable by the one or more processors, including instructions that are executable to configure the computer system to perform at least;

identify a plurality of tracer objectives of an application;

identify a frequency profile for each of the plurality of tracer objectives;

for a given tracer obj ective, identify an input parameter of at least one other tracer obj ective;

score the input parameter at least in part based on similarity between the frequency profile of the at least one other tracer obj ective and the frequency profile of the given tracer objective;

compare the scored input parameter to a relevance threshold; and

based at least in part on the input parameter scoring above the relevance threshold, selectively adding the input parameter to the given tracer objective.

11. The computing system of claim 10, wherein the computer-executable instructions also include instructions that are executable to configure the computer system to, for the given tracer objective, sort a plurality of other tracer objectives according to similarity of frequency profiles of the other tracer objectives to the frequency profile of the given tracer objective.

12. The computing system of claim 10, wherein the computer-executable instructions also include instructions that are executable to configure the computer system to iterate by identifying additional input parameters of the at least one other tracer obj ective, scoring the additional input parameters at least in part based on similarity between the frequency profile of the at least one other tracer objective and the frequency profile of the given tracer objective, comparing the scored input parameters to a relevance threshold, and adding the additional input parameters to the given tracer objective when the additional input parameters score above the relevance threshold.

13. The computing system of claim 10, wherein the computer-executable instructions also include instructions that are executable to configure the computer system to execute the plurality of tracer objectives in the application in order to perform a periodicity analysis to generate the frequency profiles of the plurality of tracer objectives.

14. The computing system of claim 10, wherein scoring the input parameter further includes determining an influence factor of the input parameter with respect to the at least one other tracer objective, and multiplying the influence factor with a similarity score, the similarity score being based on the similarity between the frequency profile of the at least one other tracer objective and the frequency profile of the given tracer objective.

15. The computing system of claim 10, wherein at least one of the frequency profiles includes multiple frequencies and the intensity and/or strength of the multiple frequencies.

16. The computing system of claim 10, wherein the computer-executable instructions also include instructions that are executable to configure the computer system to identify an input parameter of the given tracer objective, score the input parameter of the given tracer objective and compare the scored input parameter of the given tracer objective to the relevance threshold, and based on the input parameter of the given tracer objective scoring below the relevance threshold, remove the input parameter from the given tracer objective.

17. A storage device comprising stored computer-executable instructions which are executable by one or more processors of a computing system to cause the computing system to perform a method that includes the computing system:

receiving an application to instrument;

identifying a plurality of trace objectives for said application, said trace objectives comprising trace objects and input parameters;

causing said plurality of trace objectives to be executed with said application to generate a plurality of results sets;

selecting a first results set generated from a first tracer objective;

analyzing said first results set to identify a first frequency;

identifying a second trace objective having a second results set comprising said first frequency;

identifying a second input parameter in said second trace objective;

creating a third trace objective comprising said first trace object and said second input parameter; and

causing said third trace objective to be executed.