Exploring the modeling of declarative processes using a hybrid approach

Amine Abbad Andaloussi*, Jon Buch-Lorentsen, Hugo A. López, Tijs Slaats, Barbara Weber

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

16 Citations (Scopus)
29 Downloads (Pure)

Abstract

Process modeling aims at providing an external representation of a business process in the shape of a process model. The complexity of the modeling language, the usability of the modeling tool, and the expertise of the modeler are among the key factors defining the difficulty of a modeling task. Following a qualitative analysis approach, this work explores a hybrid modeling technique enhanced with a tool (i.e., the Highlighter) to guide the transition from informal text-based process descriptions to formal declarative process models. The exploratory results suggest that this technique provides cognitive support to modelers and hint towards an enhanced quality of process models in terms of alignment, traceability of process requirements and availability of documentation. The outcome of this work shows a clear opportunity for future work and provides a framework for further empirical studies.

Original languageEnglish
Title of host publicationConceptual Modeling - 38th International Conference, ER 2019, Proceedings
EditorsAlberto H.F. Laender, Barbara Pernici, Ee-Peng Lim, José Palazzo M. de Oliveira
Number of pages9
PublisherSpringer VS
Publication date1 Jan 2019
Pages162-170
ISBN (Print)9783030332228
DOIs
Publication statusPublished - 1 Jan 2019
Event38th International Conference on Conceptual Modeling, ER 2019 - Salvador, Brazil
Duration: 4 Nov 20197 Nov 2019

Conference

Conference38th International Conference on Conceptual Modeling, ER 2019
Country/TerritoryBrazil
CitySalvador
Period04/11/201907/11/2019
SeriesLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11788 LNCS
ISSN0302-9743

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