Tool-Assisted Conformance Checking to Reference Process Models

• URL: http://arxiv.org/abs/2508.00738v2
• Date: Mon, 04 Aug 2025 12:03:24 GMT
• Title: Tool-Assisted Conformance Checking to Reference Process Models
• Authors: Bernhard Rumpe, Max Stachon, Sebastian Stüber, Valdes Voufo,
• Abstract summary: Conformity checks are crucial to maintain quality and consistency in various processes.<n>This paper explores automated conformance checks for concrete process models against reference models.
• Score: 0.9117519504551699
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Reference models convey best practices and standards. The reference frameworks necessitate conformance checks to ensure adherence to established guidelines and principles, which is crucial for maintaining quality and consistency in various processes. This paper explores automated conformance checks for concrete process models against reference models using causal dependency analysis of tasks and events. Existing notions of conformance checking for process models focus on verifying process execution traces and lack the expressiveness and automation needed for semantic model comparison, leaving this question unresolved. We integrate our approach into a broader semantic framework for defining reference model conformance. We outline an algorithm for reference process model conformance checking, evaluate it through a case study, and discuss its strengths and limitations. Our research provides a tool-assisted solution enhancing accuracy and flexibility in process model conformance verification.

Related papers

• Consistency Verification in Ontology-Based Process Models with Parameter Interdependencies [40.539768677361735]
  Formalization of process knowledge enables consistent modeling of parameter interdependencies in manufacturing.<n>To support cross-context application and knowledge reuse, such expressions are defined in a generic form and applied across multiple process contexts.<n>This paper presents a set of verification mechanisms for a previously developed process semantics-based model.
  arXiv  Detail & Related papers  (2025-06-19T07:21:16Z)
• Formal Analysis of the Contract Automata Runtime Environment with Uppaal: Modelling, Verification and Testing [0.3807314298073301]
  A distributed runtime application called tt CARE has been introduced to realise service applications specified using a dialect of finite-state automata.<n>We detail the formal modelling, verification and testing of tt CARE.
  arXiv  Detail & Related papers  (2025-01-22T15:03:25Z)
• Mining Constraints from Reference Process Models for Detecting Best-Practice Violations in Event Log [1.389948527681755]
  We propose a framework for mining declarative best-practice constraints from a reference model collection. We demonstrate the capability of our framework to detect best-practice violations through an evaluation based on real-world process model collections and event logs.
  arXiv  Detail & Related papers  (2024-07-02T15:05:37Z)
• OSM: Leveraging Model Checking for Observing Dynamic 1 behaviors in Aspect-Oriented Applications [0.0]
  observe-based statistical model-checking (OSM) framework devised to craft executable formal models directly from foundational system code. This ensures the unyielding performance of electronic health record systems amidst shifting preconditions.
  arXiv  Detail & Related papers  (2024-03-03T00:03:34Z)
• QualEval: Qualitative Evaluation for Model Improvement [82.73561470966658]
  We propose QualEval, which augments quantitative scalar metrics with automated qualitative evaluation as a vehicle for model improvement. QualEval uses a powerful LLM reasoner and our novel flexible linear programming solver to generate human-readable insights. We demonstrate that leveraging its insights, for example, improves the absolute performance of the Llama 2 model by up to 15% points relative.
  arXiv  Detail & Related papers  (2023-11-06T00:21:44Z)
• Variable Importance Matching for Causal Inference [73.25504313552516]
  We describe a general framework called Model-to-Match that achieves these goals. Model-to-Match uses variable importance measurements to construct a distance metric. We operationalize the Model-to-Match framework with LASSO.
  arXiv  Detail & Related papers  (2023-02-23T00:43:03Z)
• Extending Process Discovery with Model Complexity Optimization and Cyclic States Identification: Application to Healthcare Processes [62.997667081978825]
  The paper presents an approach to process mining providing semi-automatic support to model optimization. A model simplification approach is proposed, which essentially abstracts the raw model at the desired granularity. We aim to demonstrate the capabilities of the technological solution using three datasets from different applications in the healthcare domain.
  arXiv  Detail & Related papers  (2022-06-10T16:20:59Z)
• Lifted Model Checking for Relational MDPs [12.574454799055026]
  pCTL-REBEL is a lifted model checking approach for verifying pCTL properties on relational MDPs. We show that the pCTL model checking approach is decidable for relational MDPs even for possibly infinite domains.
  arXiv  Detail & Related papers  (2021-06-22T13:12:36Z)
• CoCoMoT: Conformance Checking of Multi-Perspective Processes via SMT (Extended Version) [62.96267257163426]
  We introduce the CoCoMoT (Computing Conformance Modulo Theories) framework. First, we show how SAT-based encodings studied in the pure control-flow setting can be lifted to our data-aware case. Second, we introduce a novel preprocessing technique based on a notion of property-preserving clustering.
  arXiv  Detail & Related papers  (2021-03-18T20:22:50Z)
• Evaluating the Safety of Deep Reinforcement Learning Models using Semi-Formal Verification [81.32981236437395]
  We present a semi-formal verification approach for decision-making tasks based on interval analysis. Our method obtains comparable results over standard benchmarks with respect to formal verifiers. Our approach allows to efficiently evaluate safety properties for decision-making models in practical applications.
  arXiv  Detail & Related papers  (2020-10-19T11:18:06Z)
• Control as Hybrid Inference [62.997667081978825]
  We present an implementation of CHI which naturally mediates the balance between iterative and amortised inference. We verify the scalability of our algorithm on a continuous control benchmark, demonstrating that it outperforms strong model-free and model-based baselines.
  arXiv  Detail & Related papers  (2020-07-11T19:44:09Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.