🤖 AI Summary
This paper addresses the challenge of consistently synthesizing a global model from locally interacting components in distributed systems. To this end, it proposes an algebraic modeling and generalization framework based on gate composition. The core methodological innovation is a constant-preserving variant of anti-unification, integrated with rule-driven computation under equational theories, which guarantees termination, correctness, and completeness of the synthesis process. System behavior is modeled as algebraic terms; local views are aligned via gate mechanisms, and local interaction structures are generalized using the proposed anti-unification algorithm to reconstruct a global model satisfying algebraic laws (e.g., associativity, commutativity). Experimental evaluation with a prototype tool demonstrates that the approach effectively recovers semantically consistent global interaction behavior from heterogeneous local models, significantly enhancing composability and verifiability in distributed protocol modeling.
📝 Abstract
Interaction models describe distributed systems as algebraic terms, with gates marking interaction points between local views. Composing local models into a coherent global one requires aligning these gates while respecting the algebraic laws of interaction operators. We specialize anti-unification (or generalization) via a special constant-preserving variant, which preserves designated constants while generalizing the remaining structure. We develop a dedicated rule-based procedure for computing these generalizations, prove its termination, soundness, and completeness, extend it modulo equational theories, and integrate it into a standard anti-unification framework. A prototype tool demonstrates the approach's ability to recompose global interactions from partial views.