Gradual Typing for Objects

By Jeremy G. Siek, Walid Taha. European Conference on Object-Oriented Programming, 2007

439 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Theory and Mathematics

View Paper: https://www.semanticscholar.org/paper/5830631a81d12a36f4e2e0e71eae5b6ce8e3a62c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

In Computational Theory and Mathematics

Citations in the corpus

Mixed Messages: Measuring Conformance and Non-Interference in TypeScript (2017, positive): “The theory of gradual typing has been extended to support references [24], objects [23], reﬁnement types [39], polymorphism [1], intersections and unions [13].”
A Gradual Type System for Elixir (2020, methodology): “Our approach is inspired by so-called gradual typing [3, 10, 11], which is present in extensions of many dynamic languages like TypeScript, PHP, Typed Racket and Typed Clojure, among others.”
Migrating gradual types (2017, methodology): “The original formalization by Siek and Taha [2006] defined gradual typing for a simply typed lambda”
Learning to Predict User-Defined Types (2023, background): “To address these concerns, gradual type systems [6], [7] were proposed; they provide developers an attractive balance between static and dynamic typing.”
Understanding TypeScript (2014, methodology): “In §7 we give an alternative formulation of the assignment compatibility relation for prodFTS that is analogous to the consistent-subtyping relation of Siek and Taha [14].”
Gradual typing with unification-based inference (2008, background): “Typing decisions must be made for all elements of the program, even for ones that haveyet to stabilize, and changes in these elements can ripple throughout the program.”
Dynamic type inference for gradual Hindley–Milner typing (2018, methodology): “Siek et al. [2015b] study so-calledmonotonic references, which are an efficient implementation of mutable references for gradually typed languages.”
The ins and outs of gradual type inference (2012, methodology): “, via occurrence typing [22], gradual typing [16, 17], hybrid typing [8], and like typing [26].”
Gradual typing: a new perspective (2019, background): “Just notice that, from the point of view of subtyping, the dynamic type ? is only related to itself, just like a type variable (cf. [Siek and Taha 2007]).”
LambdaNet: Probabilistic Type Inference using Graph Neural Networks (2020, background): “Gradual typing can address these shortcomings: program variables have optional type annotations so that the type system can perform static type checking whenever possible (Siek & Taha, 2007; Chung et al., 2018).”
Design and evaluation of gradual typing for python (2014, methodology): “Siek and Taha [26] introduced the gradual typing approach to melding static and dynamic type systems.”
MaxSMT-Based Type Inference for Python 3 (2018, methodology): “For these reasons, Python’s PEP484 [25] has recently introduced optional type annotations in the spirit of gradual typing [23].”
Learning type annotation: is big data enough? (2021, background): “Gradual typing [6, 23, 24] is gaining popularity, in programming languages like Python and JavaScript.”
Principal Type Schemes for Gradual Programs (2015, methodology): “…the proposed foundations for such languages, gradual typing , due to Siek and Taha (2006) has been used to integrate dynamic checks into a variety of type structures, including object-oriented (Siek and Taha 2007), substructural (Wolff et al. 2011), and ownership types (Sergey and Clarke 2012).”