Abstract:

The masked data are the system failure data when the exact cause of the failures might be unknown. That is, it is the subset of components that causes system failures. In general, the maximum likelihood estimation (MLE) of parameters are difficult to find when the masked data exist, because the superposition nonhomogenous Poisson process (NHPP) software reliability model cannot be decomposed into independent NHPP models. In this paper, the MLE of software reliability with masked data is studied based on superposition NHPP models. Finally, a numerical example based on simulation data is given to illustrate the good performance of MLE.