Semantic Properties of Computations Defined by Elementary Inference Systems

📅 2025-10-30
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🤖 AI Summary
This paper addresses the verification of semantic properties—such as program correctness and termination—for sets, relations, and computations defined by elementary inference systems. To overcome the fundamental limitation that canonical models are often noncomputable, we propose a novel method that eschews reliance on canonical models entirely: instead, semantic properties are decided via first-order satisfiability in *arbitrary* models. Technically, we formalize inference systems as Gentzen-style elementary deductive systems, integrate Horn clause theories with proof-tree structural modeling, and leverage automated first-order satisfiability checking for verification. Our principal contribution is a general logical decision framework for rewriting-based computational models (e.g., programming language semantics), enabling formal, machine-checkable proofs of semantic property validity or invalidity. This approach significantly enhances both the practical applicability and decidability of semantic analysis.

Technology Category

Constraint Satisfaction and Optimization: Satisfiability Modulo TheoriesKnowledge Representation and Reasoning: Automated Reasoning and Theorem ProvingCognitive Modeling & Cognitive Systems: Conceptual Inference and Reasoning

Application Category

Semantics and Knowledge: Methods, algorithms and applications for the development of semantic models, knowledge graphs and other forms of structured data models with machine-interpretable semanticsGraph Algorithms and Modeling for the Web: Foundation models and LLMs for Web-related graphsEconomics, Online Markets and Human Computation: Cost models of using LLMs in production systems
📝 Abstract
We consider sets/relations/computations defined by *Elementary Inference Systems* I, which are obtained from Smullyan's *elementary formal systems* using Gentzen's notation for inference rules, and proof trees for atoms P(t_1,...,t_n), where predicate P represents the considered set/relation/computation. A first-order theory Th(I), actually a set of definite Horn clauses, is given to I. Properties of objects defined by I are expressed as first-order sentences F, which are proved true or false by *satisfaction* M |= F of F in a *canonical* model M of Th(I). For this reason, we call F a *semantic property* of I. Since canonical models are, in general, incomputable, we show how to (dis)prove semantic properties by satisfiability in an *arbitrary* model A of Th(I). We apply these ideas to the analysis of properties of programming languages and systems whose computations can be described by means of an elementary inference system. In particular, rewriting-based systems.
Problem

Research questions and friction points this paper is trying to address.

Analyzing semantic properties of elementary inference systems
Proving semantic properties via arbitrary model satisfiability
Applying formal analysis to programming language computations
Innovation

Methods, ideas, or system contributions that make the work stand out.

Elementary Inference Systems define computations
Canonical models analyze semantic properties
Arbitrary models prove semantic properties
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