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  Software Reliability Models

 

Software modeling techniques can be divided into two subcategories: prediction modeling and estimation modeling. Both kinds of modeling techniques are based on observing and accumulating failure data and analyzing with statistical inference. The major difference of the two models is shown in Table 1.

ISSUES PREDICTION MODELS ESTIMATION MODELS
DATA REFERENCE Uses historical data

Uses data from the current software development effort

WHEN USED IN DEVELOPMENT CYCLE

Usually made prior to development or test phases; can be used as early as concept phase

Usually made later in life cycle(after some data have been collected); not typically used in concept or development phases

TIME FRAME

Predict reliability at some future time

Estimate reliability at either present or some future time

Table1: Difference between software reliability prediction models & software reliability estimation models
  The field has matured to the point that software models can be applied in practical situations and give meaningful results and, second, that there is no one model that is best in all situations. Because of the complexity of software, any model has to have extra assumptions. Only limited factors can be put into consideration. Most software reliability models ignore the software development process and focus on the results -- the observed faults and/or failures. By doing so, complexity is reduced and abstraction is achieved, however, the models tend to specialize to be applied to only a portion of the situations and a certain class of the problems. We have to carefully choose the right model that suits our specific case. Furthermore, the modeling results can not be blindly believed and applied.
 
   
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