A New Dynamic Algorithm for Petri Nets Slicing

Petri Nets are a mathematical and graphical tool that is used to model and analyze discrete event systems. The integration of different concurrent processes leads to more complex Petri Nets models. Verifying these models is a nontrivial challenge, as the huge models result in huge state space. Therefore, slicing algorithms are used to reduce the size of the models. These algorithms aim to extract parts from the model that affect the slicing criteria. In this paper, a new slicing algorithm is proposed, which aims to minimize the size of the model while preserving the behaviors of the system. The retained slice is formed by extracting the backward executions starting from the slicing criteria. Simultaneously, it generates all possible lower boundaries of the initial marking that can influence the places of slicing criteria. The paper also presents a case study. The case study compares the performance of the proposed algorithm against some of the existing dynamic Petri Nets slicing algorithms.