Probabilistic assumptions of software reliability growth models

Abstract

The article describes research of probabilistic assumptions of software reliability growth models, that the time between two successive moments of defects detection is a random variable with a known distribution law. Experimental researches of the distribution law for time series of defect detection in 500 software systems has been performed. For increase the authenticity of the results, software systems written in 24 modern programming languages with different subject areas has been selected. The hypotheses that the series conform the normal, exponential, and uniform distribution laws, as well as the Poisson distribution, has been tested. The results of the experiment showed, that only 21% of tested software systems have one of the above listed time distributions between two consecutive time moments of detection of defects. Thus, the assumptions of the reliability models about a distribution law are not performs for 79% researched software systems. This fact can explain the absence of a single universal reliability mod-el, which with reasonable accuracy could describe the dynamics of defect detection in all software systems. The results of the research also testify about the necessity to revise the conceptual basis of the modern theory of software reliability.