Abstracting gradual references

Toro, Matías; Tanter, Éric

doi:10.1016/j.scico.2020.102496

Cited by 12 publications

(10 citation statements)

References 6 publications

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“…Toro et al [2018] tuned their AGT abstraction to achieve type enforcement. Guided by intuition, Toro and Tanter [2020] tuned their abstraction to achieve a space-efficient implementation. This work develops a principled approach to tuning the runtime checks in an AGT-based language, and shows that it suffices to address the two challenges above.…”

Section: ]mentioning

confidence: 99%

Abstracting gradual typing moving forward: precise and space-efficient

Schwerter

Clark²,

Jafery³

et al. 2021

Proc. ACM Program. Lang.

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Abstracting Gradual Typing (AGT) is a systematic approach to designing gradually-typed languages. Languages developed using AGT automatically satisfy the formal semantic criteria for gradual languages identified by Siek et al. Nonetheless, vanilla AGT semantics can still have important shortcomings. First, a gradual language's runtime checks should preserve the space-efficiency guarantees inherent to the underlying static and dynamic languages. To the contrary, the default operational semantics of AGT break proper tail calls. Second, a gradual language's runtime checks should enforce basic modular type-based invariants expected from the static type discipline. To the contrary, the default operational semantics of AGT may fail to enforce some invariants in surprising ways. We demonstrate this in the GTFL ≲ language of Garcia et al. This paper addresses both problems at once by refining the theory underlying AGT's dynamic checks. Garcia et al. observe that AGT involves two abstractions of static types: one for the static semantics and one for the dynamic semantics. We recast the latter as an abstract interpretation of subtyping itself, while gradual types still abstract static types. Then we show how forward-completeness (Giacobazzi and Quintarelli) is key to supporting both space-efficient execution and reliable runtime type enforcement.

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Section: ]mentioning

confidence: 99%

Abstracting gradual typing moving forward: precise and space-efficient

Schwerter

Clark²,

Jafery³

et al. 2021

Proc. ACM Program. Lang.

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“…terms to 𝜆 𝜀 D? terms, provided in supplementary material, is straightforward [Toro and Tanter 2020], and very similar to a standard cast insertion translation [Siek and Taha 2006]. It inserts ascriptions on every raw value and on every term whose typing derivation relies on a consistent judgment, synthesizing the corresponding evidence that supports the ascription.…”

Section: Dynamic Semantics Of 𝜆 D?mentioning

confidence: 99%

“…: type characterizing data.are only resolved after a call returns. Recent work shows how to achieve space efficiency withAGT [Bañados Schwerter et al 2021;Toro and Tanter 2020], and the technique directly applies to the semantics presented here. The novel implementation challenge introduced by GSD is the representation of datatypes.…”

mentioning

confidence: 99%

Gradually structured data

Malewski

Greenberg

Tanter

2021

Proc. ACM Program. Lang.

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Dynamically-typed languages offer easy interaction with ad hoc data such as JSON and S-expressions; statically-typed languages offer powerful tools for working with structured data, notably algebraic datatypes , which are a core feature of typed languages both functional and otherwise. Gradual typing aims to reconcile dynamic and static typing smoothly. The gradual typing literature has extensively focused on the computational aspect of types, such as type safety, effects, noninterference, or parametricity, but the application of graduality to data structuring mechanisms has been much less explored. While row polymorphism and set-theoretic types have been studied in the context of gradual typing, algebraic datatypes in particular have not, which is surprising considering their wide use in practice. We develop, formalize, and prototype a novel approach to gradually structured data with algebraic datatypes. Gradually structured data bridges the gap between traditional algebraic datatypes and flexible data management mechanisms such as tagged data in dynamic languages, or polymorphic variants in OCaml. We illustrate the key ideas of gradual algebraic datatypes through the evolution of a small server application from dynamic to progressively more static checking, formalize a core functional language with gradually structured data, and establish its metatheory, including the gradual guarantees.

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“…Siek & Wadler (2010) propose another approach that compresses a sequence of casts into two casts where the middle type is the least upper bound with respect to precision. The AGT methodology uses a similar representation (Garcia et al, 2016) and was proved space-efficient (Toro & Tanter, 2020;Bañados Schwerter et al, 2021).…”

Section: Reduction Semantics and Type Safetymentioning

confidence: 99%

“…We encourage other researchers to join us in this project of developing reusable meta-theory for gradually typed languages. We conjecture that the Parameterized Cast Calculus, with some minor modifications, could model the intrinsic calculi used in the AGT methodology (Toro & Tanter, 2020).…”

Section: Introductionmentioning

confidence: 99%

Parameterized cast calculi and reusable meta-theory for gradually typed lambda calculi

Siek¹,

Chen²

2021

J. Funct. Prog.

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The research on gradual typing has led to many variations on the Gradually Typed Lambda Calculus (GTLC) of Siek & Taha (2006) and its underlying cast calculus. For example, Wadler and Findler (2009) added blame tracking, Siek et al. (2009) investigated alternate cast evaluation strategies, and Herman et al. (2010) replaced casts with coercions for space efficiency. The meta-theory for the GTLC has also expanded beyond type safety to include blame safety (Tobin-Hochstadt & Felleisen, 2006), space consumption (Herman et al., 2010), and the gradual guarantees (Siek et al., 2015). These results have been proven for some variations of the GTLC but not others. Furthermore, researchers continue to develop variations on the GTLC, but establishing all of the meta-theory for new variations is time-consuming. This article identifies abstractions that capture similarities between many cast calculi in the form of two parameterized cast calculi, one for the purposes of language specification and the other to guide space-efficient implementations. The article then develops reusable meta-theory for these two calculi, proving type safety, blame safety, the gradual guarantees, and space consumption. Finally, the article instantiates this meta-theory for eight cast calculi including five from the literature and three new calculi. All of these definitions and theorems, including the two parameterized calculi, the reusable meta-theory, and the eight instantiations, are mechanized in Agda making extensive use of module parameters and dependent records to define the abstractions.

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Abstracting gradual references

Cited by 12 publications

References 6 publications

Abstracting gradual typing moving forward: precise and space-efficient

Abstracting gradual typing moving forward: precise and space-efficient

Gradually structured data

Parameterized cast calculi and reusable meta-theory for gradually typed lambda calculi

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