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Improving test suites for efficient fault localization
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Proceedings of the 28th international conference on Software engineering table of contents
Shanghai, China
SESSION: Research papers: test & analysis I table of contents
Pages: 82 - 91  
Year of Publication: 2006
ISBN:1-59593-375-1
Authors
Benoit Baudry  IRISA, Cedex, France
Franck Fleurey  IRISA, Cedex, France
Yves Le Traon  France Télécom R&D, Cedex, France
Sponsors
ACM: Association for Computing Machinery
SIGSOFT: ACM Special Interest Group on Software Engineering
Publisher
ACM  New York, NY, USA
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ABSTRACT

The need for testing-for-diagnosis strategies has been identified for a long time, but the explicit link from testing to diagnosis (fault localization) is rare. Analyzing the type of information needed for efficient fault localization, we identify the attribute (called Dynamic Basic Block) that restricts the accuracy of a diagnosis algorithm. Based on this attribute, a test-for-diagnosis criterion is proposed and validated through rigorous case studies: it shows that a test suite can be improved to reach a high level of diagnosis accuracy. So, the dilemma between a reduced testing effort (with as few test cases as possible) and the diagnosis accuracy (that needs as much test cases as possible to get more information) is partly solved by selecting test cases that are dedicated to diagnosis.


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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H. Agrawal, J. Horgan, S. London, and W. Wong. Fault Localization using Execution Slices and Dataflow Tests. Proceedings of ISSRE'95 (Int. Symposium on Software Reliability Engineering), Toulouse, France, October 1995.
 
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V. Dallmeier, C. Lindig, and A. Zeller. Lightweight Defect Localization for Java. Proceedings of ECOOP'05 (European Conference on Object-Oriented Programming), Glasgow, Scotland, July 2005.
 
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R. DeMillo, R. Lipton, and F. Sayward. Hints on Test Data Selection: Help For The Practicing Programmer. IEEE Computer, 1978. 11(4): 34--41.
 
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F. Fleurey, B. Baudry, and Y. Le Traon. Improving Test Cases for Accurate Diagnosis. Accessed on: May 2005.http://www.irisa.fr/triskell/results/Diagnosis/index.htm
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B. Korel. Dynamic method for software test data generation. Software Testing, Verification and Reliability, 1992. 2(4): 203--213.
 
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M.L. Rosenzweig. Species Diversity In Space and Time. Cambridge University Press, 1995.
 
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J. Wegener, A. Baresel, and H. Stahmer. Evolutionary Test Environment for Automatic Structural Testing. Information and Software Technology, 2001. 43(14): 841--854.
 
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Collaborative Colleagues:
Benoit Baudry: colleagues
Franck Fleurey: colleagues
Yves Le Traon: colleagues