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Reducing irrelevant trace variations
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Automated Software Engineering archive
Proceedings of the twenty-second IEEE/ACM international conference on Automated software engineering table of contents
Atlanta, Georgia, USA
POSTER SESSION: Posters table of contents
Pages 477-480  
Year of Publication: 2007
ISBN:978-1-59593-882-4
Authors
Madeline Diep  University of Nebraska - Lincoln, Lincoln, NE
Sebastian Elbaum  University of Nebraska - Lincoln, Lincoln, NE
Matthew Dwyer  University of Nebraska - Lincoln, Lincoln, NE
Sponsors
ACM: Association for Computing Machinery
SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
SIGSOFT: ACM Special Interest Group on Software Engineering
Publisher
ACM  New York, NY, USA
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ABSTRACT

Identifying truly distinct traces is crucial for the performance and practicality of many dynamic analysis activities. For example, given a trace pool resulting from program failures, identifying the set of distinct traces can reduce the debugging effort by more quickly producing a smaller set of candidate fault locations. The process of discriminating valuable traces, however, is subject to the presence of irrelevant variations in the trace constitution, i.e., the sequence of events in a trace, that can make a trace appear unique when it is not, leading to the retention of a trace that adds no value. In this paper we present an approach to address inconsequential and potentially detrimental trace variations. The approach decomposes traces into segments on which irrelevant variations caused by event ordering or repetition can be detected and removed. The approach is illustrated on two well-known client dynamic analyses and is supported by an infrastructure to explore the approach


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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Dallmeier, V., Lindig, C., and Zeller, A., "Lightweight defect localization for Java," ECOOP - Object Oriented Programming, pp. 528--550, 2005.
 
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Collaborative Colleagues:
Madeline Diep: colleagues
Sebastian Elbaum: colleagues
Matthew Dwyer: colleagues