Dependent types for JavaScript

By Ravi Chugh, David Herman, Ranjit Jhala. 2011

105 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems, Software, Program Analysis & Verification

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 Information Systems

In Software

In Program Analysis & Verification

Citations in the corpus

Do Machine Learning Models Produce TypeScript Types that Type Check? (2023, methodology): “Although this paper focuses on type migration for TypeScript, there are several other gradual type systems for JavaScript [15, 22, 30, 49].”
Understanding TypeScript (2014, methodology): “[4] employed nested refinements and heap types in DJS, and Guha et al.”
Fast and precise type checking for JavaScript (2017, methodology): “DJS [Chugh et al. 2012] combines nested refinements with alias types [Smith et al. 2000], a restricted separation logic, to account for aliasing and flow-sensitive heap updates to obtain a static type system for a large portion of JavaScript. DJS comes with very limited type inference and hence requ”
Checking correctness of TypeScript interfaces for JavaScript libraries (2014, methodology): “Several more expressive type systems for JavaScript than the one in TypeScript have been proposed, including TeJaS [9] and DJS [1].”
Practical Optional Types for Clojure (2016, methodology): “These include TypeScript [19] and Flow [11] for JavaScript, Hack [10] for PHP, and mypy [15] for Python among the optional systems, and Typed Racket [23], Reticulated Python [25], and Gradualtalk [1] among gradually-typed systems.1 1 We use “gradual typing” for systems like Typed Racket with sound i”
Refinement types for TypeScript (2016, methodology): “DJS combines nested refinements with alias types [29], a restricted separation logic, to account for aliasing and flow-sensitive heap updates to obtain a static type system for a large portion of JS [5].”
OptTyper: Probabilistic Type Inference by Optimising Logical and Natural Constraints (2020, methodology): “ent types [Bierman et al. 2012], provides a different approach. LiquidHaskell [Vazou et al. 2014] is a static verifier of Haskell based on Liquid Types via SMT and predicate abstraction. DependentJS [Chugh et al. 2012] incorporates dependent types into JavaScript. We note also, that HM(X) is a famil”