Software Reliability Growth Model using Interval Domain Data
Rani Neppala Geetha, Prasad Dr.R.Satya · International Journal of Computer Applications · 2011
Software reliability is one of the most important characteristics of software quality. Its measurement and management technologies employed during the software life cycle are essential for producing and maintaining quality/reliable software systems. Over the last several decades, many Software Reliability Growth Models (SRGMs) have been developed to greatly facilitate engineers and managers in tracking and measuring the growth of reliability as software is being improved. In this paper we proposed Pareto type II based software reliability growth model with interval domain data. The maximum likelihood (ML) estimation approach is used to estimate the unknown parameters of the model. This paper presents estimation procedures to access reliability of a software system using Pareto type II distribution, which is based on Non Homogenous Poisson Process (NHPP). We also present an analysis of two software failure data sets. General Terms Software failure data, Distribution function, Mean value function