Stochastic models for software science
Abstract The current development of software measures is the result of treating software construction as a deterministic process. In this article, stochastic models for the software construction process are developed. The models are based on absorbing Markov chains and can be used to estimate standard software measures and their variability. The focus is on the length measure. The predictive properties of the models are investigated in an empirical study based on data from PASCAL and C language software.