Category-Based MLM: Unifying Powertypes with Superclasses

2026-09-23

AI Summary

This study addresses the inherent contradiction between the non-transitivity of instantiation relationships and deep characterization in multi-level software modeling by proposing the CatMLM model. Integrating ontological philosophy, conceptual modeling, and object-oriented analysis techniques, this model distinguishes category from object characteristics to unify power types and superclass roles. Furthermore, it establishes quantitative stratification criteria and decision rules for subclass-instantiation relationships, fundamentally clarifying the nature of hierarchical structures. This work constructs a rigorously defined multi-level modeling framework and systematically demonstrates its advantages over traditional object-oriented modeling approaches. Ultimately, it provides both a robust theoretical foundation and a practical paradigm for complex multi-level modeling tasks.

Abstract

MultiLevel software Modeling (MLM) suggests that conceptual modeling in broad subject domains might require abstraction of multiple classification levels. The MLM approach relies on philosophical arguments, claiming that faithful modeling of real-world domains involves repeated type classification as in ontologies of natural kinds. MLM leveled architecture is interwoven and defined by instance-of interlevel relationships between clabject classes in lower levels to classes termed category classes, in upper levels. The instance-of relation denotes membership of clabjects as type objects in their (powertypes) category classes, and is not transitive. All MLM approaches support forms of deep characterization, i.e., category classes can influence classes in lower levels. Deep characterization is an essential feature of superclasses and contradicts the non-transitive membership meaning of instance-of. In this paper, we introduce the Category-Based MLM (CatMLM) model, in which category classes have dual superclass and powertype facets, based on the distinction between category features that do not participate in deep characterization, and object features that do. This distinction clarifies the role of levels, provides a clear quantifiable criterion for leveling, and yields a decision rule between the subclass and instance-of relations. The contribution of this paper is to introduce a well-defined MLM model that (1) is based on simple, quantifiable level decisions; (2) clarifies how leveling emerges from domain needs; and (3) analyzes gains and losses of MLM vs. plain OO modeling.

Problem

• MultiLevel Modeling
• powertype
• superclass
• deep characterization
• instance-of relation

Innovation

• MultiLevel Modeling
• CatMLM
• Powertypes
• Deep Characterization
• Quantifiable Leveling