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Automated path generation for software fault localization
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Proceedings of the 20th IEEE/ACM international Conference on Automated software engineering table of contents
Long Beach, CA, USA
SESSION: Short papers 1 table of contents
Pages: 347 - 351  
Year of Publication: 2005
ISBN:1-59593-993-4
Authors
Tao Wang  National University of Singapore
Abhik Roychoudhury  National University of Singapore
Sponsors
ACM: Association for Computing Machinery
SIGART: ACM Special Interest Group on Artificial Intelligence
SIGSOFT: ACM Special Interest Group on Software Engineering
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 7,   Downloads (12 Months): 47,   Citation Count: 3
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ABSTRACT

Localizing the cause(s) of an observable error lies at the heart of program debugging. Fault localization often proceeds by comparing the failing program run with some "successful" run (a run which does not demonstrate the error). An issue here is to generate or choose a "suitable" successful run; this task is often left to the programmer. In this paper, we present an efficient technique where the construction of the successful run as well its comparison with the failing run is automated. Our method constructs a successful program run by toggling the outcomes of some conditional branch instances in the failing run. If such a successful run exists, program statements for these branches are returned as bug report. In our experiments with the Siemens benchmark suite, we found that the quality of our bug report compares well with those produced by existing fault localization approaches where the programmer manually provides or chooses a successful run.


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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B. Pytlik, M. Renieris, S. Krishnamurthi, and S. P. Reiss. Automated fault localization using potential invariants. CoRR, cs.SE/0310040, Oct, 2003.
 
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M. Renieris and S. P. Reiss. Fault localization with nearest neighbor queries. In Automated Software Engineering (ASE), pages 30--39, 2003.
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Collaborative Colleagues:
Tao Wang: colleagues
Abhik Roychoudhury: colleagues