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Systems
Article . 2025 . Peer-reviewed
License: CC BY
Data sources: Crossref
DBLP
Article . 2025
Data sources: DBLP
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Measuring the Complexity of SysML Models

Authors: Anoushka Bhatnager; Lakshmi Bhargav Gullapalli; Pierre de Saqui-Sannes; Rob A. Vingerhoeds;

Measuring the Complexity of SysML Models

Abstract

Model-Based Systems Engineering (MBSE) is employing systems analysis, design, and development on models of these systems, bringing together different viewpoints, with a step-by-step increase of detail. As such, it replaces traditional document-centric approaches with a methodology that uses structured domain models for information exchange and system representation throughout the engineering lifecycle. MBSE comprises different languages, each with distinct features and approaches. SysML is a widely used language in MBSE, and many tools exist for it. This paper is interested in the complexity of SysML models, as it may yield useful quantitative indicators to assess and predict the complexity of systems modeled in SysML, and, by extension, the complexity of their subsequent development. Two avenues are explored: objective structural metrics applied to the SysML model and assessment of the team experience. The proposed approach is implemented as a Java prototype. Although simpler models are easier to comprehend and modify, they may fail to capture the full scope of system functionality. Conversely, more complex models, though richer in detail, require greater development effort and pose challenges for maintenance and stakeholder communication. Technical and environmental factors are integrated into the complexity assessment to reflect real-world project conditions. A drone-based image acquisition system serves as a case study.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
gold