During the last decade, various approaches have been put forward to integrate business processes with different types of data. Each of these approaches reflects specific demands in the whole process-data integration spectrum. One particularly 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.
Petri Nets with Parameterised Data / S. Ghilardi, A. Gianola, M. Montali, A. Rivkin (LECTURE NOTES IN ARTIFICIAL INTELLIGENCE). - In: Business Process Management[s.l] : Springer, 2020 Sep. - ISBN 978-3-030-58665-2. - pp. 55-74
|Titolo:||Petri Nets with Parameterised Data : Modelling and Verification|
|Settore Scientifico Disciplinare:||Settore INF/01 - Informatica|
|Data di pubblicazione:||2020|
|Digital Object Identifier (DOI):||http://dx.doi.org/10.1007/978-3-030-58666-9_4|
|Tipologia:||Book Part (author)|
|Appare nelle tipologie:||03 - Contributo in volume|