Measurement of fairness in process models using entropy and stochastic Petri nets

Measurements of various properties of the process models in the last few years become relatively widely explored area. These are properties such as uncertainty, complexity, readability or cohesion of process models. Quantification of these properties can provide better insight in term of, for instance, user-friendliness, predictability, clarity, etc. of the process model. The aim of this work is to design a method for quantification of fairness in the process models which are modelled using stochastic Petri nets. The method is based on mapping the set of all reachable markings of Petri net into Markov chain and then quantification of entropy from stationary probabilities of the individual places (all places or a specific subset). The resulting value of fairness is from the interval <0, 1>.