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|Author(s):||David R. Kuhn; Raghu N. Kacker; Yu Lei;|
|Title:||Estimating Fault Detection Effectiveness|
|Published:||April 01, 2014|
|Abstract:||[Poster] A t-way covering array can detect t-way faults, however they generally include other combinations beyond t-way as well. For example, a particular test set of all 5-way combinations is shown capable of detecting all seeded faults in a test program, despite the fact that it contains up to 9-way faults. This poster gives an overview of methods for estimating fault detection effectiveness of a test set based on combinatorial coverage for a class of software. Detection effectiveness depends on the distribution of t-way faults, which is not known. However based on past experience one could say for example the fraction of 1-way faults is F(sub)1 = 60%, 2-way faults F(sub)2 = 25% F(sub)3 = 10% and F(sub)4 = 5%. Such information could be used in determining the required strength t. It is shown that the fault detection effectiveness of a test set may be affected significantly by the t-way fault distribution, overall, simple coverage at each level of t, number of values per variable, and minimum t-way coverage. Using these results, we develop practical guidance for testers.|
|Conference:||Third International Workshop on Combinatorial Testing|
|Proceedings:||Proceedings of the Seventh IEEE International Conference on Software, Testing, Verification and Validation (ICST 2014)|
|Pages:||pp. 154 - 154|
|Dates:||March 31-April 4, 2014|
|Keywords:||combinatorial testing, software testing, test coverage|
|Research Areas:||Information Technology, Math, Software Testing Metrics|
|DOI:||http://dx.doi.org/10.1109/ICSTW.2014.69 (Note: May link to a non-U.S. Government webpage)|
|PDF version:||Click here to retrieve PDF version of paper (34KB)|