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