A Non-Parametric Order Statistics Software Reliability Model

This paper addresses a family of probability models for the failure time process known as order statistic models. Conventional order statistics models make rather strong distributional assumptions about the detection times: typically they assume that these come from some parametric family of distributions. In this paper a new model is presented that relaxes these distributional assumptions, and in the tradition of non-parametric statistics generally ‘allows the data to speak for themselves’. The accuracy of the new model is compared on some real data sets with the predictions that come from several of the better parametric reliability growth models. key words: Software reliability growth, non-parametric estimation, kernel density estimation