Scenes: A Meta-Logical Algebra for Mutable State

2026-09-24

AI Summary

This study addresses the imprecise description of program variables in mutable state modeling and the difficulty of composing objects within Lens algebra. To overcome these challenges, this work proposes a "Scene" algebraic structure to characterize sets of state space variables. Methodologically, it employs shallow embedding combined with lens and prism theories, introducing the concept of scene spaces to recover set-algebraic structures analogous to vector spaces. This approach enables meta-logical analysis and program reasoning without requiring syntactic embedding. The proposed framework successfully characterizes free and bound variables and derives inference principles for parallel composition operators, thereby overcoming the inherent limitations of directly composing Lenses. Ultimately, this work significantly enhances the automation efficiency of formal verification.

Abstract

Modelling of mutable state spaces and precisely describing how variables are manipulated in a program is a fundamental problem in compositional verification. Though we can make use of the embedded abstract syntax of a program for such analysis, this runs contrary to the shallow-embedding approach, and hampers efficient proof automation. On the other hand, lenses and prisms provide an elegant algebraic foundation for modelling state, which provide sufficient structure to provide meta-logical program analysis, but without requiring a deep embedding. Nevertheless lenses, as complex algebraic objects, cannot easily be combined, complemented, or collected in sets. In this paper we contribute an accompanying algebraic structure called the scene, which allows us to characterise the set of variables, or coordinates, in a state space. Scenes intuitively correspond to sets of lenses, but like lenses they are purely semantic algebraic objects. We demonstrate that scenes provide us with sufficient structure to characterise the lens-based meta-logical properties, like independence and equivalence. Moreover, we introduce the notion of a scene space, analogous to a vector space, which allows us to recover a set-like algebraic structure. Finally, we show how scenes allow us to characterise the free and bound variables of expressions and programs, without any need for syntax, and demonstrate their use for reasoning about programs by deriving reasoning principles for the parallel composition operator.

Problem

• mutable state
• compositional verification
• lenses
• shallow embedding
• meta-logical analysis

Innovation

• Scenes
• Lenses
• Mutable State
• Meta-Logical Algebra
• Compositional Verification