Abstract. In this paper we give an overview, how to apply region based methods for the synthesis of Petri nets from languages to process mining.The research domain of process mining aims at constructing a process model from an event log, such that the process model can reproduce the log, and does not allow for much more behaviour than shown in the log. We here consider Petri nets to represent process models. Event logs can be interpreted as finite languages. Region based synthesis methods can be used to construct a Petri net from a language generating the minimal net behaviour including the given language. Therefore, it seems natural to apply such methods in the process mining domain. There are several different region based methods in literature yielding different Petri nets. We adapt these methods to the process mining domain and compare them concerning efficiency and usefulness of the resulting Petri net.

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In this paper we present an algorithm to synthesize a finite unlabelled place/transition Petri net (p/t-net) from a possibly infinite partial language, which is given by a term over a finite set of labelled partial orders using operators for union, iteration, parallel composition and sequential composition. The synthesis algorithm is based on the theory of regions for partial languages presented in [17] and produces a p/t-net having minimal net behaviour including the given partial language. The algorithm uses linear programming techniques that were already successfully applied in [22] for the synthesis of p/t-nets from finite partial languages. Also, an equality test algorithm to check whether the behaviour of the synthesized p/t-net equals the given partial language is shown. Moreover, we present an implementation of the developed synthesis algorithm together with an example case study. Finally, a possible generalization of the presented term based representation of infinite partial languages is discussed.

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