PAIS Lab seminar "Object-Centric Replay-Based Conformance Checking: Unveiling Desire Lines and Local Deviations"
17:00 (Moscow time)
Object-Centric Replay-Based Conformance Checking: Unveiling Desire Lines and Local Deviations
Julio Cesar Carrasquel Gamez, PAIS Lab Research Assistant
Join the seminar using Zoom: https://us02web.zoom.us/j/87055677095
Conformance checking methods diagnose whether a process, as observed in an event log, complies with its specification model, e.g., a Petri net. Most of these methods, however, check process instances (cases) individually, neglecting the interaction of such instances in a system. This limitation has been addressed in other areas of process mining by object-centric approaches. These approaches make use of Petri net extensions to model and analyze overlapping instances that are centered on the handling of objects. For instance, some of these approaches were recently presented at the PAIS Lab's seminar series "Wednesday Nights of Petri Nets and Their Extensions". Thus, for example, Fahland's synchronous proclets allow to describe the communication of multiple workflows, van der Aalst's object-centric nets can be discovered from logs where events have multiple case identifiers, whereas Rivkin and van der Werf propose formalisms to verify the interplay between processes and object-persistence models such as databases.
Inspired by the object-centric paradigm, we thus present in this talk a replay-based conformance method using conservative workflow colored nets. This model allows to describe the expected behavior of a system composed by end-to-end processes handling individual objects. Notably, when replaying an event log on top of our model, we consider a jump strategy where tokens representing objects move from their current location to input places of a transition to fire. Token jumps allow to unveil "desire lines", i.e., object paths unforeseen in the specification model. We introduce local conformance metrics based on the proportion of jumps in specific model components. The metrics allow to measure the magnitude of non-compliance in precise parts of a system. Supported by an implementation of our method, we present a practical example based on trading systems, where orders from users are matched to trade. Finally, we compare our approach with other well-known conformance methods.