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OOPSLA2026顶会

Refined² Environment Classifiers

Yuito Murase, Atsushi Igarashi

2026年份

摘要

MetaML-style multi-stage programming (MSP) supports quasi-quotation-based code generation, runtime execution of generated code, and cross-stage persistence (CSP). However, its interaction with computational effects is subtle: mutable state can cause scope extrusion, where generated code escapes the scope of variables on which it depends. This paper presents a type system for MetaML-style MSP with mutable state that statically rules out harmful scope extrusion while supporting multi-level code generation, runtime execution, and a variant of CSP. Our system builds on refined environment classifiers (RECs), a discipline that annotates code types with the variable scopes on which generated code depends. To scale RECs to the MetaML-style setting, we refine classifiers so that they track not only variable scopes, but also the scopes of classifiers themselves. Further, we integrated polymorphism over classifiers, enabling more general and reusable code generation patterns in a multi-level setting. For the resulting system, we define an operational semantics via a definitional interpreter and prove type soundness and safety of offline code generation, showing that generated code can be extracted as standalone well-typed programs. We provide working implementations and mechanized proofs in Rocq.

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