Good estimates of the reliability of a system make use of test data and expert knowledge at all available levels. Furthermore, by\r\nintegrating all these information sources, one can determine how best to allocate scarce testing resources to reduce uncertainty.\r\nBoth of these goals are facilitated by modern Bayesian computational methods. We demonstrate these tools using examples that\r\nwere previously solvable only through the use of ingenious approximations, and employ genetic algorithms to guide resource\r\nallocation.
Loading....