What do the software reliability growth model parameters represent?

Abstract

Here we investigate the underlying basis connecting the software reliability growth models to the software testing and debugging process. This is important for several reasons. First, if the parameters have an interpretation, then they constitute a metric for the software test process and the software under test. Secondly, it may be possible to estimate the parameters even before testing begins. These a priori values can serve as a check for the values computed at the beginning of testing, when the test-data is dominated by short term noise. They can also serve as initial estimates when iterative computations are used. Among the two-parameter models, the exponential model is characterized by its simplicity. Both its parameters have a simple interpretation. However, in some studies it has been found that the logarithmic Poisson model has superior predictive capability. Here we present a new interpretation for the logarithmic model parameters. The problem of a priori parameter estimation is considered using actual data available. Use of the results obtained is illustrated using examples. Variability of the parameters with the testing process is examined.