The Infinite NHPP Software Reliability Model based on Monotonic Intensity Function

Software testing (debugging) in order to reduce costs in terms of changes in the software reliability and testing costs, need to know in advance is more efficient. In this paper, proposes the reliability model with monotonic intensity functions (Power-Law, Musa-Okumoto and Comperz model), which made out efficiency application for software reliability. Algorithm to estimate the parameters used to maximum likelihood estimation and bisection method, model selection based on mean square error and coefficient of determination, for the sake of efficient model, were employed. Analysis of failure using real data set for the sake of proposing monotonic intensity function was employed. This analysis of failure data compared with monotonic intensity function. In order to insurance for the reliability of data, Laplace trend test was employed. In this study, the proposed monotonic intensity function is more efficient in terms of reliability in this area. Thus, monotonic intensity function can also be used as an alternative model. From this paper, software developers have to consider the growth model by prior knowledge of the software to identify failure modes which can be able to help.