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- W192548637 abstract "Statistical testing involves exercising a piece of software by supplying it with input values that are randomly selected according to a defined probability distribution over its input domain. This paper focuses on functional statistical testing, that is, when an input distribution and a number of random inputs are determined according to criteria relating to software functionality. The criteria based on models of behavior deduced from specification, i.e., finite-state machines and decision tables, are defined. The modeling approach involves a hierarchical decomposition of software functionality. It is applied to a module from the nuclear field. Functional statistical test sets are designed and applied to two versions of the module: the real version, and that developed by a student. Twelve residual faults are revealed, eleven of which affect the student’s version. The other fault is quite subtle, since it resides in the driver that we have developed for the real version in our experimental test harness. Two other input distributions are experimented with: the uniform distribution over the input domain and a structural distribution determined so as to rapidly exercise all the instructions of the student’s version. The results show that the functional statistical test sets have the highest fault revealing power and are the most cost-effective.KeywordsTest SizeRandom InputInput DistributionHierarchical DecompositionInput DomainThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves." @default.
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- W192548637 date "1993-01-01" @default.
- W192548637 modified "2023-09-27" @default.
- W192548637 title "On Functional Statistical Testing Designed from Software Behavior Models" @default.
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- W192548637 doi "https://doi.org/10.1007/978-3-7091-4009-3_1" @default.
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