Blended graphical and textual modelling for UML profiles: A proof-of-concept implementation and experiment
2021 (English)In: Journal of Systems and Software, ISSN 0164-1212, E-ISSN 1873-1228, Vol. 175, article id 110912Article in journal (Refereed) Published
Abstract [en]
Domain-specific modelling languages defined by extending or constraining the Unified Modelling Language (UML) through the profiling mechanism have historically relied on graphical notations to maximise human understanding and facilitate communication among stakeholders. Other notations, such as text-, form-, or table-based are, however, often preferred for specific modelling purposes, due to the nature of a specific domain or the available tooling, or for personal preference. Currently, the state of the art support for UML-based languages provides an almost completely detached, or even entirely mutually exclusive, use of graphical and textual modelling. This becomes inadequate when dealing with the development of modern systems carried out by heterogeneous stakeholders. Our intuition is that a modelling framework based on seamless blended multi-notations can disclose several benefits, among which: flexible separation of concerns, multi-view modelling based on multiple notations, convenient text-based editing operations (inside and outside the modelling environment), and eventually faster modelling activities. In this paper we report on: (i) a proof-of-concept implementation of a framework for UML and profiles modelling using blended textual and graphical notations, and (ii) an experiment on the framework, which eventually shows that blended multi-notation modelling performs better than standard single-notation modelling.
Place, publisher, year, edition, pages
Elsevier Inc. , 2021. Vol. 175, article id 110912
Keywords [en]
Blended modelling, MARTE, Multi-view modelling, Papyrus, UML profiles, Xtext, Software engineering, Domain-Specific Modelling Languages, Editing operations, Human understanding, Modelling environment, Modelling framework, Personal preferences, Separation of concerns, Modeling languages
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:mdh:diva-53478DOI: 10.1016/j.jss.2021.110912ISI: 000623099500005Scopus ID: 2-s2.0-85100104994OAI: oai:DiVA.org:mdh-53478DiVA, id: diva2:1529704
2021-02-192021-02-192021-03-25Bibliographically approved