Method for automatic detection of build regressions

Details Method for automatic detection of build regressions Method for automatic detection of build regressions

2004-02-12

2009-02-24

Dam, Tuan Q. (Department: 2192)

Data processing: software development, installation, and managem

Software program development tool

Testing or debugging

C717S126000, C717S127000, C717S130000

Reexamination Certificate

active

07496900

ABSTRACT:
A method and apparatus for automatically performing regression processing on trace data are provided. With the apparatus and method, call tree data structures are generated for two or more executions of two or more builds of a computer program. The apparatus and method perform a “tree-minimization” operation on each set of call tree data structures for each of the builds to generate minimized call tree data structures for each build of the computer program. The minimized call tree data structures are then subtracted from one another to generate a subtracted minimized call tree data structure. From this subtracted minimized call tree data structure, the portions of the computer program that are different from build to build and which appreciably and consistently affect the difference in execution of the computer program from build to build may be identified. Thus, the analyst's attention is directed to these areas of the computer program code which may be optimized in order to obtain better execution of the computer program.

REFERENCES:
patent: 5950003 (1999-09-01), Kaneshiro et al.
patent: 5963739 (1999-10-01), Homeier
patent: 6011918 (2000-01-01), Cohen et al.
patent: 6055492 (2000-04-01), Alexander et al.
patent: 6247170 (2001-06-01), Giroux
patent: 6282701 (2001-08-01), Wygodny et al.
patent: 6338159 (2002-01-01), Alexander, III et al.
patent: 6349406 (2002-02-01), Levine et al.
patent: 6765990 (2004-07-01), Freedman et al.
patent: 6904594 (2005-06-01), Berry et al.
patent: 7103530 (2006-09-01), Bartz et al.
patent: 7246290 (2007-07-01), Green et al.
patent: 7260692 (2007-08-01), Zahavi et al.
patent: 2003/0051122 (2003-03-01), Sato
patent: 2003/0192034 (2003-10-01), Hayase
patent: 2004/0078789 (2004-04-01), Ghiya et al.
patent: 2005/0071818 (2005-03-01), Reissman et al.
patent: 2005/0183070 (2005-08-01), Alexander, III et al.
patent: 2005/0183074 (2005-08-01), Alexander, III et al.
patent: 2005/0183075 (2005-08-01), Alexander, III et al.
patent: 2005/0210452 (2005-09-01), Dimpsey et al.
Srivastava et al., “Effectively Prioritizing Tests in Development Environment”, Feb. 2002, Microsoft Research, pp. 97-106.
Young et al., “Better Global Scheduling Using Path Profiles”, Nov. 30, 1998, Preceedings. 31st Annual ACMIIEEE internation Symposium on Microarchitecture, 1998, pp. 115-123, IEEE.
Alexander et al., “A Unifying Approach to Performance Analysis in the Java Environment”, IBM Systems Journal, vol. 39, No. 1, 2000, pp. 118-134.
Kazi et al., “JaViz: A Client/Server Java Profiling Tool”, IBM Systems Journal 39, No. 1, 2000, pp. 96-117.
Bhargava et al., “Improving Dynamic Cluster Assignment for Clustered Trace Cache Processors”, Proceedings of the 30th Annual International Symposium on Computer Architecture, 2003, pp. 264-274, IEEE.
Zhang et al., “Whole Execution Traces”, 37th International Symposiumon on Microarchitecture, 2004, pp. 105-116, IEEE.
Srivastava et al., “Effectively Prioritizing Tests in Development Environment”, Feb. 2002, Microsoft Research, pp. 97-106, WA.
Young et al. “Better Global Scheduling Using Path Profiles”, Nov. 30, 1998, Proceedings. 31st Annual ACMIIEEE International Symposium on Microarchitecture, 1998, pp. 115-123, IEEE.

Affiliated with

Also associated with

Rating

Method for automatic detection of build regressions does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Method for automatic detection of build regressions, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Method for automatic detection of build regressions will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFUS-PAI-O-4133569