TY - JOUR
T1 - Multi-paradigm modelling for cyber–physical systems
T2 - a descriptive framework
AU - Amrani, Moussa
AU - Blouin, Dominique
AU - Heinrich, Robert
AU - Rensink, Arend
AU - Vangheluwe, Hans
AU - Wortmann, Andreas
N1 - Funding Information:
Moussa Amrani was funded by the Walloon Region Cluster of Excellence SkyWin SW_D-DAMS Project. Dominique Blouin was partially supported by the ISC Chair (Ingénierie des Systèmes Complexes) on cyber–physical systems and distributed control systems. Robert Heinrich was partially funded by the German Federal Ministry of Education and Research under grant 01IS18067D (RESPOND), and the KASTEL institutional funding. Hans Vangheluwe’s Research Group was partially supported by Flanders Make, the strategic research centre for the Flemish manufacturing industry. Andreas Wortmann was partially funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany Excellence Strategy—EXC 2023 Internet of Production.
Publisher Copyright:
© 2021, The Author(s).
PY - 2021/6/9
Y1 - 2021/6/9
N2 - The complexity of cyber–physical systems (CPSs) is commonly addressed through complex workflows, involving models in a plethora of different formalisms, each with their own methods, techniques, and tools. Some workflow patterns, combined with particular types of formalisms and operations on models in these formalisms, are used successfully in engineering practice. To identify and reuse them, we refer to these combinations of workflow and formalism patterns as modelling paradigms. This paper proposes a unifying (Descriptive) Framework to describe these paradigms, as well as their combinations. This work is set in the context of Multi-Paradigm Modelling (MPM), which is based on the principle to model every part and aspect of a system explicitly, at the most appropriate level(s) of abstraction, using the most appropriate modelling formalism(s) and workflows. The purpose of the Descriptive Framework presented in this paper is to serve as a basis to reason about these formalisms, workflows, and their combinations. One crucial part of the framework is the ability to capture the structural essence of a paradigm through the concept of a paradigmatic structure. This is illustrated informally by means of two example paradigms commonly used in CPS: Discrete Event Dynamic Systems and Synchronous Data Flow. The presented framework also identifies the need to establish whether a paradigm candidate follows, or qualifies as, a (given) paradigm. To illustrate the ability of the framework to support combining paradigms, the paper shows examples of both workflow and formalism combinations. The presented framework is intended as a basis for characterisation and classification of paradigms, as a starting point for a rigorous formalisation of the framework (allowing formal analyses), and as a foundation for MPM tool development.
AB - The complexity of cyber–physical systems (CPSs) is commonly addressed through complex workflows, involving models in a plethora of different formalisms, each with their own methods, techniques, and tools. Some workflow patterns, combined with particular types of formalisms and operations on models in these formalisms, are used successfully in engineering practice. To identify and reuse them, we refer to these combinations of workflow and formalism patterns as modelling paradigms. This paper proposes a unifying (Descriptive) Framework to describe these paradigms, as well as their combinations. This work is set in the context of Multi-Paradigm Modelling (MPM), which is based on the principle to model every part and aspect of a system explicitly, at the most appropriate level(s) of abstraction, using the most appropriate modelling formalism(s) and workflows. The purpose of the Descriptive Framework presented in this paper is to serve as a basis to reason about these formalisms, workflows, and their combinations. One crucial part of the framework is the ability to capture the structural essence of a paradigm through the concept of a paradigmatic structure. This is illustrated informally by means of two example paradigms commonly used in CPS: Discrete Event Dynamic Systems and Synchronous Data Flow. The presented framework also identifies the need to establish whether a paradigm candidate follows, or qualifies as, a (given) paradigm. To illustrate the ability of the framework to support combining paradigms, the paper shows examples of both workflow and formalism combinations. The presented framework is intended as a basis for characterisation and classification of paradigms, as a starting point for a rigorous formalisation of the framework (allowing formal analyses), and as a foundation for MPM tool development.
KW - UT-Hybrid-D
U2 - 10.1007/s10270-021-00876-z
DO - 10.1007/s10270-021-00876-z
M3 - Article
VL - 20
SP - 611
EP - 639
JO - Software and systems modeling
JF - Software and systems modeling
SN - 1619-1366
IS - 3
ER -