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Issue No.06 - November/December (2010 vol.36)
pp: 763-777
Simon Poulding , University of York, York
John A. Clark , University of York, York
Statistical testing has been shown to be more efficient at detecting faults in software than other methods of dynamic testing such as random and structural testing. Test data are generated by sampling from a probability distribution chosen so that each element of the software's structure is exercised with a high probability. However, deriving a suitable distribution is difficult for all but the simplest of programs. This paper demonstrates that automated search is a practical method of finding near-optimal probability distributions for real-world programs, and that test sets generated from these distributions continue to show superior efficiency in detecting faults in the software.
Software/program verification, testing strategies, test coverage of code, optimization.
Simon Poulding, John A. Clark, "Efficient Software Verification: Statistical Testing Using Automated Search", IEEE Transactions on Software Engineering, vol.36, no. 6, pp. 763-777, November/December 2010, doi:10.1109/TSE.2010.24
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