| Analyses of Software Failure Data (2007) | |||||||||||||||
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| In this paper we present and analyse a new set of software failure data which shows the failure behaviour, over a period of four years, of a single-user work station which was installed at the City University in March 1985. The details recorded in this data collection exercise allow us to subdivide the data into various subsets of inter-failure times. A sub-collection of these are chosen for more detailed analysis. Experience of applying reliability models in the past has shown that the relative predictive performance of the models depends entirely on the context. It has been found that there is no one model that performs well over all data sets. It has also been found that for some data sets all models applied are in error. In such cases two techniques for improving predictive accuracy have been shown to be beneficial: i) recalibrating the raw model predictions and ii) using the results of trend tests to apply the models. These two techniques may be used separately or in combination. ... | |||||||||||||||
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