Using Free-Choice Nets for Process Mining and Business Process Management

Free-choice nets, a subclass of Petri have been studied for decades. They are interesting because they many desirable properties normal nets do not and can be analyzed efficiently. Although the majority process models used in practice inherently free-choice, most users (even modeling experts) aware free-choice net theory associated analysis techniques. This paper discusses context mining business management. For example, state-of-the-art discovery algorithms like inductive miner produce that free-choice. Also, hand-made using languages BPMN tend to choice synchronization separated different elements. Therefore, we introduce basic notions results this important class models. Moreover, also present new particularly relevant mining. elaborate on home clusters lucency as closely-related correctness notions. We discuss limitations management, suggest research directions extend with non-local dependencies.