Measuring the Complexity of User Processes using Shannon Entropy and Stochastic Petri Nets

Abstract

Measuring complexity of processes or systems is currently a very popular topic. There is a wide range of defined complexity measures that quantify features such as legibility, modifiability, uncertainty, comprehensibility, easiness of implementation, user-friendliness and many others. The content of this work is a presentation of a method for quantification of complexity using Shannon entropy and stochastic Petri nets. Shannon entropy and Petri nets are an appropriate combination because they allow analysing the complexity of processes not only in terms of their structure but also in terms of their dynamic development under tension. On a simple example are outlined possible analyses and the correlation analysis examines the comparability with other selected complexity measures.