Multi-stage programming with generative and analytical macros

Stucki, Nicolas; Brachthäuser, Jonathan Immanuel; Odersky, Martin

doi:10.1145/3486609.3487203

Cited by 4 publications

(1 citation statement)

References 23 publications

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“…Pattern matching against code Analytic metaprogramming that allows pattern matching against code values is considered beneficial and explored recently [18,28,9]. Especially, Moebius [9] provides a contextual modal type system capable of pattern matching against open code with polymorphic types.…”

Section: Related Workmentioning

confidence: 99%

Contextual Modal Type Theory with Polymorphic Contexts

Murase

Nishiwaki²,

Igarashi

2023

Lecture Notes in Computer Science

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Modal types—types that are derived from proof systems of modal logic—have been studied as theoretical foundations of metaprogramming, where program code is manipulated as first-class values. In modal type systems, modality corresponds to a type constructor for code types and controls free variables and their types in code values. Nanevski et al. have proposed contextual modal type theory, which has modal types with fine-grained information on free variables: modal types are explicitly indexed by contexts—the types of all free variables in code values.This paper presents $$\lambda _{\forall []}$$ λ ∀ [ ] , a novel extension of contextual modal type theory with parametric polymorphism over contexts. Such an extension has been studied in the literature but, unlike earlier proposals, $$\lambda _{\forall []}$$ λ ∀ [ ] is more general in that it allows multiple occurrence of context variables in a single context. We formalize $$\lambda _{\forall []}$$ λ ∀ [ ] with its type system and operational semantics given by $$\beta $$ β -reduction and prove its basic properties including subject reduction, strong normalization, and confluence. Moreover, to demonstrate the expressive power of polymorphic contexts, we show a type-preserving embedding from a two-level fragment of Davies’ $$\lambda _{\bigcirc }$$ λ ◯ , which is based on linear-time temporal logic, to $$\lambda _{\forall []}$$ λ ∀ [ ] .

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Section: Related Workmentioning

confidence: 99%

Contextual Modal Type Theory with Polymorphic Contexts

Murase

Nishiwaki²,

Igarashi

2023

Lecture Notes in Computer Science

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The essence of online data processing

Dexter

Liu

Chiu

2022

Proc. ACM Program. Lang.

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Data processing systems are a fundamental component of the modern computing stack. These systems are routinely deployed online: they continuously receive the requests of data processing operations, and continuously return the results to end users or client applications. Online data processing systems have unique features beyond conventional data processing, and the optimizations designed for them are complex, especially when data themselves are structured and dynamic. This paper describes DON Calculus, the first rigorous foundation for online data processing. It captures the essential behavior of both the backend data processing engine and the frontend application, with the focus on two design dimensions essential yet unique to online data processing systems: incremental operation processing (IOP) and temporal locality optimization (TLO). A novel design insight is that the operations continuously applied to the data can be defined as an operation stream flowing through the data structure, and this abstraction unifies diverse designs of IOP and TLO in one calculus. DON Calculus is endowed with a mechanized metatheory centering around a key observable equivalence property: despite the significant non-deterministic executions introduced by IOP and TLO, the observable result of DON Calculus data processing is identical to that of conventional data processing without IOP and TLO. Broadly, DON Calculus is a novel instance in the active pursuit of providing rigorous guarantees to the software system stack. The specification and mechanization of DON Calculus provide a sound base for the designers of future data processing systems to build upon, helping them embrace rigorous semantic engineering without the need of developing from scratch.

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Deep Fusion for Efficient Nested Recursive Computations

Shaikhha

2022

Proceedings of the 21st ACM SIGPLAN International Conference on Generative Programming: Concepts and Experiences

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Multi-stage programming with generative and analytical macros

Cited by 4 publications

References 23 publications

Contextual Modal Type Theory with Polymorphic Contexts

Contextual Modal Type Theory with Polymorphic Contexts

The essence of online data processing

Deep Fusion for Efficient Nested Recursive Computations

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