Abstract
Conformance checking methods diagnose to which extent a real system, whose behavior is recorded in an event log, complies with its specification model, e.g., a Petri net. Nonetheless, the majority of these methods focus on checking isolated process instances, neglecting interaction between instances in a system. Addressing this limitation, a series of object-centric approaches have been proposed in the field of process mining. These approaches are based on the holistic analysis of the multiple process instances interacting in a system, where each instance is centered on the handling of an object. Inspired by the object-centric paradigm, this paper presents a replay-based conformance checking method which uses a class of colored Petri nets (CPNs) -- a Petri net extension where tokens in the model carry values of some types (colors). Particularly, we consider conservative workflow CPNs which allow to describe the expected behavior of a system whose components are centered on the end-to-end processing of distinguishable objects. For describing a system’s real behavior, we consider event logs whose events have sets of objects involved in the execution of activities. For replay, we consider a jump strategy where tokens absent from input places of a transition to fire move from their current place of the model to the requested places. Token jumps allow to identify desire lines, i.e., object paths unforeseen in the specification. Also, we introduce local diagnostics based on the proportion of jumps in specific model components. The metrics allow to inform the severity of deviations in precise system parts. Finally, we report experiments supported by a prototype of our method. To show the practical value of our method, we employ a case study on trading systems, where orders from users are matched to trade.
Highlights
Process mining is a discipline that focuses on the analysis of system processes on the basis of event logs and formal models [1]
Inspired by the object-centric paradigm, this paper presents a replay-based conformance checking method which uses a class of colored Petri nets (CPNs) – a Petri net extension where tokens in the model carry values of some types
The majority of process mining methods have hitherto consisted on the individual analysis of isolated process instances, thereby neglecting their interaction with other instances in the system. is assumption falls short, and may throw out a wrong analysis, especially when there is a strong dependency between the life-cycles of instances
Summary
Process mining is a discipline that focuses on the analysis of system processes on the basis of event logs and formal models [1]. As for conformance checking, certain methods have been proposed to validate multiple perspectives of a process beyond the control- ow, i.e., the correct ordering of activities [14, 15] These methods make use of Petri nets with data (DPNs) to detect deviations caused by data corruptions (e.g., “a loan approval was wrongly executed due to a requested amount higher than expected”). Tokens cannot disappear or duplicate, and they move through paths whose endpoints are speci c pairs of source and sink places In this way, the model allows to describe the expected behavior of systems with components centered on the end-to-end processing of distinct objects of a certain type.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have