Nonparametric analysis of software reliability: Revealing the nature of software failure dataseries

Abstract

Software reliability is directly related to the number and time of occurrence of software failures. Thus, if we were able to reveal and characterize the behavior of the evolution of actual software failures over time then we could possibly build more accurate models for estimating and predicting software reliability. This paper focuses on the study of the nature of empirical software failure data via a nonparametric statistical framework. Six different time-series data expressing times between successive software failures were investigated and a random behavior was detected with evidences favoring a pink noise explanation.