Considering Residual Faults of Burr Type XII Software Reliability Growth Model

Software Reliability Growth model (SRGM) is a mathematical model of how the software reliability improves as faults are detected and repaired. A large number of software reliability growth models have been proposed to analyze the reliability of software application during the testing phase, with the increasing demand to deliver high-quality software, more accurate software reliability models are required to estimate the optimal software release time and the cost of testing efforts. This paper proposes Burr type XII based Software Reliability growth model with Interval domain data. The unknown parameters of the model are estimated using the maximum likelihood (ML) estimation method. Reliability of a software system using Burr type XII distribution, which is based on Non-Homogenous Poisson process (NHPP), is presented through estimation procedures. The performance of the SRGM is judged by its ability to fit the software failure data. How good does a mathematical model fit to the data is also being calculated. To access the performance of the considered SRGM, we have carried out the parameter estimation on the real software failure datasets.