Structural and topological complexity analysis in HLA object models
Simulation Modelling Practice and Theory, cilt.152, 2026 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 152
- Basım Tarihi: 2026
- Doi Numarası: 10.1016/j.simpat.2026.103328
- Dergi Adı: Simulation Modelling Practice and Theory
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Applied Science & Technology Source, Compendex, INSPEC, Academic Search Ultimate (EBSCO), Engineering Source (EBSCO)
- Anahtar Kelimeler: Automated code generation, Distributed simulation, Federation object model (FOM), High level architecture (HLA), Static analysis, Structural complexity, Topological complexity
- Orta Doğu Teknik Üniversitesi Adresli: Evet
Özet
The structural topology of object models in High Level Architecture (HLA) based distributed simulations strongly influences software implementation complexity. Existing validation techniques primarily verify syntax rules and elementary node counts, leaving latent architectural risk conditions undetected until the implementation phase. This paper presents a quantitative framework for the pre-execution structural and topological analysis of HLA Object Models. The methodology introduces four indicators: Weighted Hierarchy Load, Topological Skewness, Depth Variation Index, and Polymorphic Potential. Together, these indicators characterize the shape, depth distribution, and abstraction balance of the schema. They function as static covariates of structural risk: they identify topological conditions associated with increased traversal, dispatch, and implementation burden, without claiming deterministic runtime prediction. The contribution of this paper is a static, pre-execution structural characterization; the associated runtime implications are formulated as testable hypotheses for future empirical validation. The framework also formalizes the analytical distinction between global Federation Object Models (FOMs) and local Simulation Object Models (SOMs), showing how role-scoped analysis can reduce the structural footprint considered for individual federates. The derived metrics are synthesized into an Architectural Profile Matrix that maps structural diagnostics to candidate code-generation and refactoring guidance, such as flattened state representations for deep hierarchies and efficient routing structures for broad sibling populations. Extracting these properties prior to implementation enables development teams to conduct structured pre-execution risk profiling.