Log-logistic software reliability growth model

Abstract

The finite-failure non-homogeneous Poisson process (NHPP) models proposed in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault, and are inadequate to describe the failure processes underlying certain failure data sets. In this paper, we propose the log-logistic reliability growth model, which can capture the increasing/decreasing nature of the failure occurrence rate per fault. Equations are developed to estimate the parameters of the existing finite-failure NHPP models, as well as the log-logistic model, based on failure data collected in the form of inter-failure times. We also present an analysis of two data sets, where the underlying failure process could not be adequately described by the existing models, which motivated the development of the log-logistic model.