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Monotonicity-Guided Bottom-Up Petri Net Discovery: The SPECpp Framework
Leah Tacke genannt Unterberg, Lisa L. Mannel, Wil M. P. van der Aalst
Process discovery is one of the central challenges in process mining. Petri nets are particularly attractive because simple local constructs can express complex behavior, including…
Hierarchical Decomposition of Separable Workflow-Nets
Humam Kourani, Gyunam Park, Wil M. P. van der Aalst
The Partially Ordered Workflow Language (POWL) has recently emerged as a process modeling notation, offering strong quality guarantees and high expressiveness. While early versions…
Revealing Inherent Concurrency in Event Data: A Partial Order Approach to Process Discovery
Humam Kourani, Gyunam Park, Wil M. P. van der Aalst
Process discovery algorithms traditionally linearize events, failing to capture the inherent concurrency of real-world processes. While some techniques can handle partially ordered…
OCPQ: Object-Centric Process Querying & Constraints
Aaron Küsters, Wil M. P. van der Aalst
Process querying is used to extract information and insights from process execution data. Similarly, process constraints can be checked against input data, yielding information on…
Computing Alignments for Partially-ordered Traces Through Petri Net Unfoldings
Ariba Siddiqui, Wil M. P. van der Aalst, Daniel Schuster
Conformance checking techniques aim to provide diagnostics on the conformity between process models and event data. Conventional methods, such as trace alignments, assume strict to…
CPN-Py: A Python-Based Tool for Modeling and Analyzing Colored Petri Nets
Alessandro Berti, Wil M. P. van der Aalst
Colored Petri Nets (CPNs) are an established formalism for modeling processes where tokens carry data. Although tools like CPN Tools and CPN IDE excel at CPN-based simulation, they…