Software reliability prediction based on design metrics

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dc.contributor.advisor Zage, Wayne M. en_US
dc.contributor.author Stineburg, Jeffrey en_US
dc.date.accessioned 2011-06-03T19:38:42Z
dc.date.available 2011-06-03T19:38:42Z
dc.date.created 1999 en_US
dc.date.issued 1999
dc.identifier LD2489.Z78 1999 .S75 en_US
dc.identifier.uri http://cardinalscholar.bsu.edu/handle/handle/186548
dc.description.abstract This study has presented a new model for predicting software reliability based on design metrics. An introduction to the problem of software reliability is followed by a brief overview of software reliability models. A description of the models is given, including a discussion of some of the issues associated with them. The intractability of validating life-critical software is presented. Such validation is shown to require extended periods of test time that are impractical in real world situations. This problem is also inherent in fault tolerant software systems of the type currently being implemented in critical applications today. The design metrics developed at Ball State University is proposed as the basis of a new model for predicting software reliability from information available during the design phase of development. The thesis investigates the proposition that a relationship exists between the design metric D(G) and the errors that are found in the field. A study, performed on a subset of a large defense software system, discovered evidence to support the proposition.
dc.description.sponsorship Department of Computer Science
dc.format.extent iv, 71 leaves : ill. ; 28 cm. en_US
dc.source Virtual Press en_US
dc.subject.lcsh Computer software -- Reliability. en_US
dc.subject.lcsh Computer software -- Quality control. en_US
dc.subject.lcsh Computer software -- Evaluation. en_US
dc.title Software reliability prediction based on design metrics en_US
dc.description.degree Thesis (M.S.)
dc.identifier.cardcat-url http://liblink.bsu.edu/catkey/1154775 en_US


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  • Master's Theses [5510]
    Master's theses submitted to the Graduate School by Ball State University master's degree candidates in partial fulfillment of degree requirements.

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