Notions of Stack-Manipulating Computation and Relative Monads

Monads provide a simple and concise interface to user-defined computational effects in functional programming languages. This enables equational reasoning about effects, abstraction over monadic interfaces and the development of monad transformer stacks to combine different effects. Compiler implementors and assembly code programmers similarly virtualize effects, and would benefit from similar abstractions if possible. However, the implementation details of effects seem disconnected from the high-level monad interface: at this lower level much of the design is in the layout of the runtime stack, which is not accessible in a high-level programming language. We demonstrate that the monadic interface can be faithfully adapted from high-level functional programming to a lower level setting with explicit stack manipulation. We use a polymorphic call-by-push-value (CBPV) calculus as a setting that captures the essence of stack-manipulation, with a type system that allows programs to define domain-specific stack structures. Within this setting, we show that the existing category-theoretic notion of a relative monad can be used to model the stack-based implementation of computational effects. To demonstrate generality, we adapt a variety of standard monads to relative monads. Additionally, we show that stack-manipulating programs can benefit from a generalization of do-notation we call "monadic blocks" that allow all CBPV code to be reinterpreted to work with an arbitrary relative monad. As an application, we show that all relative monads extend automatically to relative monad transformers, a process which is not automatic for monads in pure languages.

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Publication Details

Journal
Proceedings of the ACM on Programming Languages
Published
2025-04-09
DOI
https://doi.org/10.1145/3720434
Citations
1
Primary Topic
Logic, programming, and type systems
Type
article
Field-Weighted Citation Impact
2.48
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article

Notions of Stack-Manipulating Computation and Relative Monads

Max S. New, Ruiyang Xue, Yajun Jiang
1 citations
Proceedings of the ACM on Programming Languages
Logic, programming, and type systems
2.48
article

Notions of Stack-Manipulating Computation and Relative Monads

Max S. New, Ruiyang Xue, Yajun Jiang
article en
1 citations

Abstract

Monads provide a simple and concise interface to user-defined computational effects in functional programming languages. This enables equational reasoning about effects, abstraction over monadic interfaces and the development of monad transformer stacks to combine different effects. Compiler implementors and assembly code programmers similarly virtualize effects, and would benefit from similar abstractions if possible. However, the implementation details of effects seem disconnected from the high-level monad interface: at this lower level much of the design is in the layout of the runtime stack, which is not accessible in a high-level programming language. We demonstrate that the monadic interface can be faithfully adapted from high-level functional programming to a lower level setting with explicit stack manipulation. We use a polymorphic call-by-push-value (CBPV) calculus as a setting that captures the essence of stack-manipulation, with a type system that allows programs to define domain-specific stack structures. Within this setting, we show that the existing category-theoretic notion of a relative monad can be used to model the stack-based implementation of computational effects. To demonstrate generality, we adapt a variety of standard monads to relative monads. Additionally, we show that stack-manipulating programs can benefit from a generalization of do-notation we call "monadic blocks" that allow all CBPV code to be reinterpreted to work with an arbitrary relative monad. As an application, we show that all relative monads extend automatically to relative monad transformers, a process which is not automatic for monads in pure languages.

Proceedings of the ACM on Programming LanguagesVol. 9(OOPSLA1)
University of Cambridge (GB), University of Michigan (US)
Openalex Percentile: Top 11%
Logic, programming, and type systems
2.48
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Notions of Stack-Manipulating Computation and Relative Monads — Max S. New, Ruiyang Xue, et al. · Proceedings of the ACM on Programming Languages (2025) | TGRS Research Map | TGRS