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Efficient Software Verification: Statistical Testing Using Automated Search

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Publication details

JournalIEEE Transactions on Software Engineering
DatePublished - 1 Nov 2010
Issue number6
Number of pages15
Pages (from-to)763-777
Original languageEnglish


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.

Bibliographical note

Query date: 14/01/2011

    Research areas

  • automated search, dynamic testing, near-optimal probability distribution, random testing, software fault detection, software verification, statistical testing, structural testing, test data, program testing, program verification, statistical distributions


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