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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Bhatnager, A., Gullapalli, L. B., de Saqui-Sannes, P., & Vingerhoeds, R. A. (2025). Measuring the Complexity of SysML Models †. Systems, 13(12). https://doi.org/10.3390/systems13121128
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