Bayesian recurrent model of reliability growth: A priori densities of polynomial type

This work is devoted to the Bayesian recurrent model of reliability growth of complex modifiable information systems. It is assumed that the key parameters of the system are unknown but the researcher obtains the information about their a priori distributions. The paper contains formulas for density and mean of marginal system's reliability when indexes of “defectiveness” and “efficiency” of the tool correcting the deficiencies in the system have a priori distributions with polynomial densities. For instance, uniform and parabolic distributions are considered. Likewise, the results for the case of degenerate distribution of one of the parameters are provided. The obtained formulas are illustrated with numerical results and plots.