|18.104.22.168 Statistic Models|
Statistic Models are based on an estimation of values based on available information about software errors.
Statistic Models can be differentiated in models based on the time between the detection of two errors, and in models based on the number of errors (/Goel, 1985/).
Models based on the time between the detection of two errors are, e. g.:
Models based on the number of errors might be:
Since the models are probability models, they are based on a number of assumptions. The most important assumption certainly is that the errors occur independent of each other. Also, it is usually assumed that the error correction will be successful. The disadvantage of the statistic models is that reasonable, probability-theoretical information can only be obtained after a certain application period. These statistic models cannot be used to define the reliability of software prior to its application.
In /Musa, 83/, the following criteria are suggested for the selection of statistic reliability models:
"Usefulness" refers to the ability of the model to estimate values. Such values are, e. g.:
The "simplicity" can refer to several aspects. First, it should be simple to collect the data required for the model. Furthermore, the model concept should be simple enough for the user to understand this model without a comprehensive knowledge of the mathematical background.
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