Execution flow shape compression for aggregate data reporting in an application manager

• US 20070169052A1
• Filed: 12/15/2005
• Published: 07/19/2007
• Est. Priority Date: 12/15/2005
• Status: Active Grant

• Current Assignee: CA, Inc. (d/b/a CA Technologies) (Broadcom, Inc.)
• Original Assignee: Wily Technology, Inc. (Broadcom, Inc.)
• Inventors: Puryear, Daryl, Vanrenen, Gabriel, Cobb, Jeffrey
• Granted Patent: US 8,316,354 B2
• Time in Patent Office: Days
• US Class Current: 717/154
• CPC Class Codes: G06F 11/28 by checking the correct order of processing G06F11/08 - G06F11/26 take precedence; monitoring patterns of pulse trains H03K5/19

Abstract

Data relating to execution flows at a computer system is compressed and aggregated across multiple execution flows by categorizing each execution flow into an execution flow shape. The execution flows may represent sequences of software components that are invoked. The execution flow shapes are developed by observing the execution flows at the computer system and applying lossy compression rules, such as representing multiple iterations of a loop as a single iteration, skipping certain types of software components, such as those having a specified call stack depth, treating some of the software components as being optional, and ignoring recursive calls by the software components. The aggregation and compression allow the information from all execution flows to be combined into a small enough data set that can be reported without consuming unduly large processing overhead while still preserving as many of the interesting aspects of the execution flows as possible.

Claims

1. A computer-implemented method for monitoring execution flows, comprising:

observing a plurality of execution flows at one or more computer systems;

compressing data representing at least one of the execution flows; and

defining a plurality of execution flow shapes based on the observing and the compressing.

2. The computer-implemented method of claim 1, wherein:

the defining comprises grouping different execution flows into a common execution flow shape.

3. The computer-implemented method of claim 1, wherein:

the compressing comprises representing multiple iterations of a loop as a single iteration.

4. The computer-implemented method of claim 1, wherein:

the observing comprises observing respective sequences of software components which are invoked for the respective execution flows.

5. The computer-implemented method of claim 4, wherein:

the compressing comprises skipping at least one type of the software components.

6. The computer-implemented method of claim 5, wherein:

the at least one type of the software components is a software component having a specified call stack depth.

7. The computer-implemented method of claim 4, wherein:

the compressing comprises treating at least one of the software components as being optional.

8. The computer-implemented method of claim 4, wherein:

the compressing comprises ignoring recursive calls by the software components.

9. The computer-implemented method of claim 1, wherein:

the observing comprises observing respective sequences in which resources are consumed by the respective execution flows.

10. The computer-implemented method of claim 1, further comprising:

aggregating data from the plurality of execution flows by categorizing each of the execution flows into a corresponding execution flow shape selected from the plurality of execution flow shapes.

11. The computer-implemented method of claim 10, further comprising:

communicating the aggregated data to a manager.

12. The computer-implemented method of claim 1, wherein:

the execution flow shapes correlate with e-commerce processes.

13. The computer-implemented method of claim 1, wherein:

at least one of the execution flows spans at least one of;

(a) one or more threads and (b) one or more processes.

14. The computer-implemented method of claim 1, wherein:

data representing a portion of the at least one of the execution flows is compressed before the at least one of the execution flows has completed executing.

15. The computer-implemented method of claim 1, wherein:

the at least one of the executions flows is compressed after it has completed executing.

16. A computer-implemented method for monitoring execution flows, comprising:

observing a sequence of software components which are invoked for an execution flow at a computer system;

choosing different ones of the software components as potential loop start components, and testing whether the chosen software components are actually loop start components, to identify loops in the sequence of software components; and

for each identified loop, collapsing multiple iterations to a single iteration.

17. The computer-implemented method of claim 16, further comprising:

defining an execution flow shape based on the sequence of software components and the collapsed loops.

18. The computer-implemented method of claim 16, wherein:

an innermost nested loop is first identified and collapsed, and successive higher level loops, if any, are sequentially identified and collapsed.

19. The computer-implemented method of claim 16, wherein:

the observing comprises observing respective sequences of software components which are invoked for the respective execution flows.

20. An apparatus for monitoring execution flows, comprising:

at least one storage device; and

at least one processor in communication with the at least one storage device, the at least one processor performing a method comprising;

observing a plurality of execution flows at one or more computer systems;

compressing data representing at least one of the execution flows; and

defining a plurality of execution flow shapes based on the observing and the compressing.

21. The apparatus of claim 20, wherein:

the defining comprises grouping different execution flows into a common execution flow shape.

22. The apparatus of claim 20, wherein:

the compressing comprises representing multiple iterations of a loop as a single iteration.

23. The apparatus of claim 20, wherein:

the observing comprises observing respective sequences of software components which are invoked for the respective execution flows.

24. The apparatus of claim 23, wherein:

the compressing comprises skipping at least one type of the software components.

25. The apparatus of claim 24, wherein:

the at least one type of the software components is a software component having a specified call stack depth.

26. The apparatus of claim 23, wherein:

the compressing comprises treating at least one of the software components as being optional.

27. The apparatus of claim 23, wherein:

the compressing comprises ignoring recursive calls by the software components.

28. The apparatus of claim 20, wherein:

the observing comprises observing respective sequences in which resources are consumed by the respective execution flows.

29. The apparatus of claim 20, wherein the method performed by the at least one processor further comprises:

aggregating data from the plurality of execution flows by categorizing each of the execution flows into a corresponding execution flow shape selected from the plurality of execution flow shapes.

30. The apparatus of claim 29, wherein the method performed by the at least one processor further comprises:

communicating the aggregated data to a manager.

31. The apparatus of claim 20, wherein:

the execution flow shapes correlate with e-commerce processes.

32. The apparatus of claim 20, wherein:

at least one of the execution flows spans at least one of;

(a) one or more threads and (b) one or more processes.

33. At least one processor readable storage device having processor readable code embodied thereon for programming at least one processor to perform a method for monitoring execution flows, the method comprising:

observing a plurality of execution flows at one or more computer systems;

compressing data representing at least one of the execution flows; and

defining a plurality of execution flow shapes based on the observing and the compressing.

34. The at least one processor readable storage device of claim 33, wherein:

the defining comprises grouping different execution flows into a common execution flow shape.

35. The at least one processor readable storage device of claim 33, wherein:

the compressing comprises representing multiple iterations of a loop as a single iteration.

36. The at least one processor readable storage device of claim 33, wherein:

the observing comprises observing respective sequences of software components which are invoked for the respective execution flows.

37. The at least one processor readable storage device of claim 36, wherein:

the compressing comprises skipping at least one type of the software components.

38. The at least one processor readable storage device of claim 37, wherein:

the at least one type of the software components is a software component having a specified call stack depth.

39. The at least one processor readable storage device of claim 36, wherein:

the compressing comprises treating at least one of the software components as being optional.

40. The at least one processor readable storage device of claim 36, wherein:

the compressing comprises ignoring recursive calls by the software components.

41. The at least one processor readable storage device of claim 33, wherein:

the observing comprises observing respective sequences in which resources are consumed by the respective execution flows.

42. The at least one processor readable storage device of claim 33, wherein the method performed further comprises:

aggregating data from the plurality of execution flows by categorizing each of the execution flows into a corresponding execution flow shape selected from the plurality of execution flow shapes.

43. The at least one processor readable storage device of claim 42, wherein the method performed further comprises:

communicating the aggregated data to a manager.

44. The at least one processor readable storage device of claim 33, wherein:

the execution flow shapes correlate with e-commerce processes.

45. The at least one processor readable storage device of claim 33, wherein:

at least one of the execution flows spans at least one of;

(a) one or more threads and (b) one or more processes.