UTILIZING PRIOR USAGE DATA FOR SOFTWARE BUILD OPTIMIZATION

• US 20080028378A1
• Filed: 07/27/2006
• Published: 01/31/2008
• Est. Priority Date: 07/27/2006
• Status: Abandoned Application

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Liu, Jiyang, de Halleux, Jonathan P., Gershony, Ori, Biswas, Surupa, Sullivan, Brian F.
• Application Number:
  US11/460,577
• Publication Number:
  US 20080028378A1
• Time in Patent Office: Days
• US Class Current: 717/151
• CPC Class Codes: G06F 8/36 Software reuse

Abstract

In one embodiment, a computer system packages a first set of data objects into a first software build. The computer system evaluates at least a portion of the usage of the first software build in accordance with usage training scenarios. The computer system monitors the evaluation of the first software build in accordance with a first software build usage detection process to detect the use of data objects within the first software build. The computer system generates profile data for the data objects and the generated profile data includes an indication of usage for each data object. The computer system packages a second set of data objects into a second software build in accordance with the generated profile data from the first software build, wherein the second set of data objects is different from but includes one or more data objects from the first set of data objects.

Claims

1. At a computer system that is configured to process data objects, a method for utilizing prior usage data for software build optimization, the method comprising the acts of:

packaging a first set of data objects into a first software build;

evaluating at least a portion of the usage of the first software build in accordance with usage training scenarios;

monitoring the evaluation of the first software build in accordance with a software build usage detection process to detect the use of data objects within the first software build;

generating profile data for the data objects, wherein the generated profile data includes an indication of usage for each data object; and

packaging a second set of data objects into a second software build in accordance with the generated profile data from the first software build, wherein the second set of data objects is different from but includes one or more data objects from the first set of data objects.

2. The method of claim 1, wherein the profile data includes block weights indicating the number of times a block of code was executed during the software build usage dection process.

3. The method of claim 2, wherein block weights are mapped from the first software build to the second software build by analyzing basic block graphs for the first and the second builds and transferring block weights from one graph to the other.

4. The method of claim 1, wherein the profile data comprises metadata tokens which are capable of identifying functions or data structures within software source code.

5. The method of claim 4, wherein the act of packaging a second set of data objects in accordance with the generated profile data comprises mapping the metadata tokens from a first version of the software build to a second version of the software build.

6. The method of claim 1, wherein the profile data comprises blobs which are capable of identifying generic methods used in a software build.

7. The method of claim 1, wherein the usage training scenarios comprise one or more software build tests that the computer system uses to evaluate at least a portion of the functionality of the first software build by running application commands, calling functions, executing code paths, loading and unloading processes, or using other means of activating software build functionality.

8. The method of claim 1, further comprising evaluating at least a portion of the functionality of any data objects in the second software build using profile data generated from the first software build.

9. The method of claim 1, wherein profile data includes information indicating which Common Language Runtime (CLR) data structures were referenced during the software build usage dection process.

10. A computer program product for use at a computer system, the computer program product of implementing a method for utilizing prior usage data for software build optimization, the computer program product comprising one or more computer-readable storage media having stored thereon computer-executable instructions that, when executed by one or more processors of the computer system, cause the computer system to perform the following:

package a first set of data objects into a first software build;

evaluate at least a portion of the usage of the first software build in accordance with usage training scenarios;

monitor the evaluation of the first software build in accordance with a software build usage detection process to detect the degree of use of data objects within the first software build;

generate profile data for the data objects, wherein the generated profile data includes an indication of usage for each data object; and

package a second set of data objects into a second software build in accordance with the generated profile data from the first software build, wherein the second set of data objects is different from but includes one or more data objects from the first set of data objects.

11. The method of claim 10, wherein the profile data includes block weights indicating the number of times a block of code was executed during the software build usage detection process.

12. The method of claim 11, wherein block weights are mapped from the first software build to the second software build by analyzing basic block graphs for the first and the second builds and transferring block weights from one graph to the other.

13. The method of claim 10, wherein the profile data comprises metadata tokens which are capable of identifying functions or data structures within software source code.

14. The method of claim 13, wherein the act of packaging a second set of data objects in accordance with the generated profile data comprises mapping the metadata tokens from a first version of the software build to a second version of the software build.

15. The method of claim 10, wherein the profile data comprises blobs which are capable of identifying generic methods used in a software build.

16. The method of claim 10, wherein the usage training scenarios comprise one or more software build tests that the computer system uses to evaluate at least a portion of the functionality of the first software build by running application commands, calling functions, executing code paths, loading and unloading processes, or using other means of activating software build functionality.

17. The method of claim 10, further comprising evaluating at least a portion of the functionality of any data objects in the second software build using profile data generated from the first software build.

18. The method of claim 10, wherein profile data includes information indicating which Common Language Runtime (CLR) data structures were referenced during the software build usage detection process.

19. At a computer system configured to process data objects, a method for optimizing the processing of a set of data objects by incorporating profile data from software build training scenarios from a first version of a software build to a second version the software build, the method comprising the acts of:

monitoring which data objects were referenced or executed during the software build training scenarios and which data objects were neither referenced nor executed;

monitoring information that includes which data objects were referenced or executed during the software build training scenarios and which data objects were neither referenced nor executed; and

generating profile data for the data objects within the software build, wherein the generated profile data includes an indication of usage for each data object.

20. The method of claim 19, wherein the indication of usage includes at least one of block weights indicating the number of times a block of code was executed during the software build training scenarios, metadata tokens which are capable of identifying functions or data structures within software source code, or blobs which are capable of identifying generic methods used in a software build.