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Yusuke Miyazaki 0001

dblp:73/11064-1 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2019
0000-0003-3884-2636ORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Software engineering, system software, and programming languages
1 paper
Programming languages and type systems · 100%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Programming languages and type systems › type inference
dynamic type inference
0.412019
Dynamic type inference for gradual Hindley-Milner typing · Proc. ACM Program. Lang. 2019
Programming languages and type systems › type systems
gradual typing
0.412019
Dynamic type inference for gradual Hindley-Milner typing · Proc. ACM Program. Lang. 2019
Programming languages and type systems › type systems › polymorphism
hindley-milner type system
0.112019
Dynamic type inference for gradual Hindley-Milner typing · Proc. ACM Program. Lang. 2019

Methods — techniques the papers use, named apart from their topics

operational semantics · 0.4cast insertion · 0.4
YearPublicationVenuePosition
2019 Dynamic type inference for gradual Hindley-Milner typing
abstract
Garcia and Cimini study a type inference problem for the ITGL, an implicitly and gradually typed language with let-polymorphism, and develop a sound and complete inference algorithm for it. Soundness and completeness mean that, if the algorithm succeeds, the input term can be translated to a well-typed term of an explicitly typed blame calculus by cast insertion and vice versa. However, in general, there are many possible translations depending on how type variables that were left undecided by static type inference are instantiated with concrete static types. Worse, the translated terms may behave differently—some evaluate to values but others raise blame. In this paper, we propose and formalize a new blame calculus λ B DTI that avoids such divergence as an intermediate language for the ITGL. A main idea is to allow a term to contain type variables (that have not been instantiated during static type inference) and defer instantiation of these type variables to run time. We introduce dynamic type inference (DTI) into the semantics of λ B DTI so that type variables are instantiated along reduction. The DTI-based semantics not only avoids the divergence described above but also is sound and complete with respect to the semantics of fully instantiated terms in the following sense: if the evaluation of a term succeeds (i.e., terminates with a value) in the DTI-based semantics, then there is a fully instantiated version of the term that also succeeds in the explicitly typed blame calculus and vice versa. Finally, we prove the gradual guarantee, which is an important correctness criterion of a gradually typed language, for the ITGL.
Yusuke Miyazaki 0001, Taro Sekiyama, Atsushi Igarashi
Proc. ACM Program. Lang.1