User interface derivation based on role-enriched business process model

Lei Han, Weiliang Zhao*, Jian Yang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

1 Citation (Scopus)

Abstract

This work proposes an approach for User Interface (UI) derivation based on a role-enriched Business Process (BP) model with the capability to describe the details of the control flow and data operations in a BP. For each user role, data relationships are extracted according to the identified control flow patterns and data operation patterns. A set of mandatory and recommended UI derivation rules are specified as the cornerstones to derive the UI logic from a BP. The algorithm for UI derivation is provided. This UI derivation approach provides the basis for UI development and maintenance.

Original languageEnglish
Title of host publicationService-Oriented Computing - 14th International Conference, ICSOC 2016, Proceedings
EditorsQuan Z. Sheng, Eleni Stroulia, Samir Tata, Sami Bhiri
Place of PublicationSwitzerland
PublisherSpringer, Springer Nature
Pages450-464
Number of pages15
Volume9936 LNCS
ISBN (Print)9783319462943
DOIs
Publication statusPublished - 2016
Event14th International Conference on Service-Oriented Computing, ICSOC 2016 - Banff, Canada
Duration: 10 Oct 201613 Oct 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9936 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other14th International Conference on Service-Oriented Computing, ICSOC 2016
CountryCanada
CityBanff
Period10/10/1613/10/16

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  • Cite this

    Han, L., Zhao, W., & Yang, J. (2016). User interface derivation based on role-enriched business process model. In Q. Z. Sheng, E. Stroulia, S. Tata, & S. Bhiri (Eds.), Service-Oriented Computing - 14th International Conference, ICSOC 2016, Proceedings (Vol. 9936 LNCS, pp. 450-464). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9936 LNCS). Switzerland: Springer, Springer Nature. https://doi.org/10.1007/978-3-319-46295-0_28