Articlegreen2013

Business Process Model Merging

Marcello La Rosa · Marlon Dumas · Reina Uba · Remco Dijkman

206 citations0/0 files storedACM Transactions on Software Engineering and Methodology

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Business Process Modeling and Analysis Advanced Software Engineering Methodologies Model-Driven Software Engineering Techniques

Abstract

This article addresses the problem of constructing consolidated business process models out of collections of process models that share common fragments. The article considers the construction of unions of multiple models (called merged models ) as well as intersections (called digests ). Merged models are intended for analysts who wish to create a model that subsumes a collection of process models -- typically representing variants of the same underlying process -- with the aim of replacing the variants with the merged model. Digests, on the other hand, are intended for analysts who wish to identify the most recurring fragments across a collection of process models, so that they can focus their efforts on optimizing these fragments. The article presents an algorithm for computing merged models and an algorithm for extracting digests from a merged model. The merging and digest extraction algorithms have been implemented and tested against collections of process models taken from multiple application domains. The tests show that the merging algorithm produces compact models and scales up to process models containing hundreds of nodes. Furthermore, a case study conducted in a large insurance company has demonstrated the usefulness of the merging and digest extraction operators in a practical setting.

Citations in this library

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References

2009Seven process modeling guidelines (7PMG)2010Similarity of business process models: Metrics and evaluation 2005A configurable reference modelling language 2009Graph Matching Algorithms for Business Process Model Similarity Search 2007What Makes Process Models Understandable?2008Metrics for Process Models : Empirical Foundations of Verification, Error Prediction, and Guidelines for Correctness 2008Measuring Similarity between Business Process Models 2010APROMORE: An advanced process model repository

Cited by

2012Managing large collections of business process models—Current techniques and challenges 2013Process Cubes: Slicing, Dicing, Rolling Up and Drilling Down Event Data for Process Mining 2014Dealing with change in process choreographies: Design and implementation of propagation algorithms 2017Similarity of Business Process Models—A State-of-the-Art Analysis 2013Mining Configurable Process Models from Collections of Event Logs 2017Challenges of smart business process management: An introduction to the special issue

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