Detecting inconsistencies between process models and textual descriptions

J.H. van der Aa, H. Leopold, H.A. Reijers

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

32 Citations (Scopus)

Abstract

Text-based and model-based process descriptions have their own particular strengths and, as such, appeal to different stakeholders. For this reason, it is not unusual to find within an organization descriptions of the same business processes in both modes. When considering that hundreds of such descriptions may be in use in a particular organization by dozens of people, using a variety of editors, there is a clear risk that such models become misaligned. To reduce the time and effort needed to repair such situations, this paper presents the first approach to automatically identify inconsistencies between a process model and a corresponding textual description. Our approach leverages natural language processing techniques to identify cases where the two process representations describe activities in different orders, as well as model activities that are missing from the textual description. A quantitative evaluation with 46 real-life model-text pairs demonstrates that our approach allows users to quickly and effectively identify those descriptions in a process repository that are inconsistent.
Original languageEnglish
Title of host publicationBusiness Process Management
Subtitle of host publication13th International Conference, BPM 2015, Innsbruck, Austria, August 31 -- September 3, 2015, Proceedings
EditorsH.R. Motahari-Nezhad, J. Recker, M. Weidlich
Place of PublicationDordrecht
PublisherSpringer
Pages90-105
ISBN (Electronic)978-3-319-23063-4
ISBN (Print)978-3-319-23062-7
DOIs
Publication statusPublished - 2015

Publication series

NameLecture Notes in Computer Science
Volume9253
ISSN (Print)0302-9743

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