AIJun 11, 2020

Petri Nets with Parameterised Data: Modelling and Verification (Extended Version)

arXiv:2006.06630v137 citations
Originality Incremental advance
AI Analysis

This work addresses the need for flexible modeling of processes with multiple co-evolving cases in business process integration, representing an incremental extension of existing formalisms.

The authors tackled the problem of integrating business processes with data by introducing catalog-nets, an extension of coloured Petri nets that incorporate database queries and fresh data injection, and they systematically encoded these nets into a verification framework while analyzing the complexity of fresh-value injection.

During the last decade, various approaches have been put forward to integrate business processes with different types of data. Each of such approaches reflects specific demands in the whole process-data integration spectrum. One particular important point is the capability of these approaches to flexibly accommodate processes with multiple cases that need to co-evolve. In this work, we introduce and study an extension of coloured Petri nets, called catalog-nets, providing two key features to capture this type of processes. On the one hand, net transitions are equipped with guards that simultaneously inspect the content of tokens and query facts stored in a read-only, persistent database. On the other hand, such transitions can inject data into tokens by extracting relevant values from the database or by generating genuinely fresh ones. We systematically encode catalog-nets into one of the reference frameworks for the (parameterised) verification of data and processes. We show that fresh-value injection is a particularly complex feature to handle, and discuss strategies to tame it. Finally, we discuss how catalog nets relate to well-known formalisms in this area.

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