Conformance Checking of Mixed-paradigm Process Models
This work provides the first conformance checking approach for mixed-paradigm process models, which is crucial for process mining practitioners working with complex process behaviors.
This paper addresses the lack of conformance checking techniques for mixed-paradigm process models, which combine procedural and declarative representations. The authors propose an alignment-based replay approach that explores the state space and computes trace fitness while respecting orthogonal Declare constraints, demonstrating its performance with real-world event logs.
Mixed-paradigm process models integrate strengths of procedural and declarative representations like Petri nets and Declare. They are specifically interesting for process mining because they allow capturing complex behaviour in a compact way. A key research challenge for the proliferation of mixed-paradigm models for process mining is the lack of corresponding conformance checking techniques. In this paper, we address this problem by devising the first approach that works with intertwined state spaces of mixed-paradigm models. More specifically, our approach uses an alignment-based replay to explore the state space and compute trace fitness in a procedural way. In every state, the declarative constraints are separately updated, such that violations disable the corresponding activities. Our technique provides for an efficient replay towards an optimal alignment by respecting all orthogonal Declare constraints. We have implemented our technique in ProM and demonstrate its performance in an evaluation with real-world event logs.