Understanding TypeScript

By Gavin M. Bierman, Martín Abadi, Mads Torgersen. 2014

229 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Hardware and Architecture, Software, Software Engineering

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 Hardware and Architecture

In Software

In Software Engineering

Citations in the corpus

Do Machine Learning Models Produce TypeScript Types that Type Check? (2023, background): “Over the past decade, gradual typing has proliferated, and there are now gradually typed versions of several mainstream languages [6, 7, 11, 14, 31, 33, 37, 48, 52].”
LambdaNet: Probabilistic Type Inference using Graph Neural Networks (2020, methodology): “…principal types (Ancona & Zucca, 2004), compilers cannot perform type inference using standard algorithms from the programming languages community (Bierman et al., 2014; Traytel et al., 2011; Pierce & Turner, 2000), and manually adding type annotations to existing codebases is a tedious and…”
Contrastive Code Representation Learning (2020, methodology): “each baseline. Compared with TypeScript’s built-in type inference, ContraCode improves top-5 accuracy by 40.4%. Baseline Method Acc@1 Acc@5 (all types) (all types) Static analysis TypeScript CheckJS (Bierman et al., 2014) 45.11% 45.11% Name only (Hellendoorn et al., 2018) 28.94% 70.07% Transformer T”
Inference and Evolution of TypeScript Declaration Files (2017, methodology): “Other research on TypeScript includes formalization and variations of its type system [4,17,18,22], and several alternative techniques for JavaScript type inference exist [16,11,6], however, none of that work addresses the challenges that arise when integrating JavaScript libraries into typed applic”
Reinforcement Learning for Primary care e Appointment Scheduling (2017, methodology): “It is implemented using Type Script [77] and the Vue.”
Learning type annotation: is big data enough? (2021, unknown): “3473135 TypeScript transpiles type-annotated code into JavaScript (JS) which provides the benefits of typing wherever traditional JS is used [5].”
Gradual typing: a new perspective (2019, background): “Many subsequent works adapted consistent-subtyping to different settings [Bierman et al. 2014; Garcia et al. 2016; Ina and Igarashi 2011; Lehmann and Tanter 2017; Maidl et al. 2014; Swamy et al. 2014; Xie et al. 2018].”
Type test scripts for TypeScript testing (2017, methodology): “The discussion about soundness of the testing is complicated by the fact that TypeScript’s type system is intentionally unsound, which is well documented [Bierman et al. 2014].”
Learning to Predict User-Defined Types (2023, unknown): “Dynamic type inference techniques [58], [59] and type checkers [60], [61], [62], [63] achieve soundness by enforcing type constraints.”
Fast and precise type checking for JavaScript (2017, background): “Unlike Flow, it focuses only on finding łlikely errorsž without caring about soundness [Bierman et al. 2014].”
Mixed Messages: Measuring Conformance and Non-Interference in TypeScript (2017, unknown): “TypeScript instead favours convenience and ease of interoperation with JavaScript [4].”
OptTyper: Probabilistic Type Inference by Optimising Logical and Natural Constraints (2020, methodology): “Therefore, TypeScript’s type system is deliberately unsound [Bierman et al. 2014].”