Conformance Checking Based on Multi-Perspective Declarative Process Models

TL;DR

This paper introduces a framework for conformance checking using multi-perspective declarative process models, specifically MP-Declare, to better handle high variability in business processes, implemented in ProM and validated through case studies.

Contribution

The paper presents a novel conformance checking framework based on MP-Declare, supporting multi-perspective specifications in declarative process models, addressing a gap in existing methods.

Findings

Framework supports multi-perspective conformance checking

Implemented in ProM tool for practical use

Validated through three real-life case studies

Abstract

Process mining is a family of techniques that aim at analyzing business process execution data recorded in event logs. Conformance checking is a branch of this discipline embracing approaches for verifying whether the behavior of a process, as recorded in a log, is in line with some expected behaviors provided in the form of a process model. The majority of these approaches require the input process model to be procedural (e.g., a Petri net). However, in turbulent environments, characterized by high variability, the process behavior is less stable and predictable. In these environments, procedural process models are less suitable to describe a business process. Declarative specifications, working in an open world assumption, allow the modeler to express several possible execution paths as a compact set of constraints. Any process execution that does not contradict these constraints is allowed. One of the open challenges in the context of conformance checking with declarative models is the capability of supporting multi-perspective specifications. In this paper, we close this gap by providing a framework for conformance checking based on MP-Declare, a multi-perspective version of the declarative process modeling language Declare. The approach has been implemented in the process mining tool ProM and has been experimented in three real life case studies.