# Conformance Checking Based on Multi-Perspective Declarative Process Models

arXiv: https://arxiv.org/abs/1503.04957 · HTML: https://mlsanity.com/paper/1503.04957/

## Key facts

- Cited by 13 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 17 Mar 2015.

## Built on by (most cited first, 13 of 13)

- [Large Language Models can accomplish Business Process Management Tasks](https://mlsanity.com/paper/2307.09923/) (2023)
- [Outcome-Oriented Prescriptive Process Monitoring Based on Temporal Logic Patterns](https://mlsanity.com/paper/2211.04880/) (2022)
- [CoCoMoT: Conformance Checking of Multi-Perspective Processes via SMT (Extended Version)](https://mlsanity.com/paper/2103.10507/) (2021)
- [Monitoring Hybrid Process Specifications with Conflict Management: The Automata-theoretic Approach](https://mlsanity.com/paper/2111.13136/) (2021)
- [A Combined Approach of Process Mining and Rule-based AI for Study Planning and Monitoring in Higher Education](https://mlsanity.com/paper/2211.12190/) (2022)
- [DeclareAligner: A Leap Towards Efficient Optimal Alignments for Declarative Process Model Conformance Checking](https://mlsanity.com/paper/2503.10479/) (2025)
- [Online Soft Conformance Checking: Any Perspective Can Indicate Deviations](https://mlsanity.com/paper/2201.09222/) (2022)
- [ASP-Based Declarative Process Mining (Extended Abstract)](https://mlsanity.com/paper/2205.01979/) (2022)
- [A Monitoring and Discovery Approach for Declarative Processes Based on Streams](https://mlsanity.com/paper/2208.05364/) (2022)
- [Declarative Guideline Conformance Checking of Clinical Treatments: A Case Study](https://mlsanity.com/paper/2209.09535/) (2022)
- [Direct Encoding of Declare Constraints in ASP](https://mlsanity.com/paper/2412.10152/) (2024)
- [Efficient Conformance Checking of Rich Data-Aware Declare Specifications (Extended)](https://mlsanity.com/paper/2507.00094/) (2025)
- [Supporting Autonomous Process Execution within a Multi-Perspective Constraint Frame via Numeric Planning](https://mlsanity.com/paper/2607.16738/) (2026)

## Abstract (arXiv)

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.