On Kolmogorov-Smirnov Test for Software Reliability Models with Grouped Data

Abstract

Software reliability models (SRMs) are the stochastic processes of the number of faults detected in the development phase, and are utilized to estimate the quantitative reliability measures of software. In the reliability evaluation with SRM, after estimating model parameters from the observed the number of detected faults, we should test the estimated SRM is fitted to the observed data statistically, i.e., we perform the goodness-of-fit test for the estimated SRM. In the past literature, Kolmogorov-Smirnov (KS) test has been used as the goodness-of-fit test for SRM. In this paper, we revisit the KS test for SRM in the case where the model parameters of SRM are estimated from grouped data of the number of detected faults.