Abstract
Software Reliability Growth Model (SRGM) is used to assess software reliability quantitatively for tracking and measuring the growth of reliability. The potentiality of SRGM is judged by its capability to fit the software failure data. In this paper we propose Burr type III software reliability growth model based on Non Homogeneous Poisson Process (NHPP) with time domain data. The Maximum Likelihood (ML) estimation method is used for finding unknown parameters in the model on ungrouped data. How good does a mathematical model fit to the data is also being calculated. To assess the performance of the considered SRGM, we have carried out the parameter estimation on real software failure data sets. We also present an analysis of goodness of fit and reliability for given failure data sets. Keywords: Burr type III, Goodness of fit, NHPP, ML estimation, Software Reliability, Time domain data.
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