Effective Assessment of Software Reliability by Using Neuron-Fuzzy System

Abstract

Software reliability is defined as the probability of software to deliver correct service over a period of time under a specified environment. This is becoming more and more important in various software organizations to discover the faults that occur commonly during development process. As the demand of the software application programs increases the quality becomes higher and higher and the reliability of these software becomes more essential. Hence Software reliability is mentioned to be as the one of the important factor during development. Many analytical models were being proposed over the years for assessing the reliability of a software system and for modeling the growth trends of software reliability with different capabilities of prediction at different testing phases. A Neuro Fuzzy based software reliability (SR) model is presented to estimate and assess the quality. Multiple datasets containing software failures are applied to the proposed model. These datasets are obtained from several software projects. Then it is observed that the results obtained indicate a significant improvement in performance by using neural fuzzy model over conventional statistical models (Fuzzy Model) based on non homogeneous Poisson process.