Predicting software reliability growth using bootstrap nonparametric fixed-width confidence intervals

In this paper, we use fixed-width bootstrap confidence intervals based on nonparametric kernal regression estimators (Nadaraya-Watson (N-W) and the Local Linear (LL)) to predict the growth of software reliability. The sample size for a preset confidence interval is optimized using a two-stage sequential sampling procedure.