Work

Type Inference for Functional and Imperative Dynamic Languages

Year: 2026

Type: article

Abstract: In this paper, we formalize a type system based on set-theoretic types for dynamic languages that support both functional and imperative programming paradigms. We adapt prior work in the typing of overloaded and generic functions to support an impure λ -calculus, focusing on imperative features commonly found in dynamic languages such as JavaScript, Python, and Julia. We introduce a general notion of parametric opaque data types using set-theoretic types, enabling precise modeling of mutable data structures while promoting modularity, clarity, and readability. Finally, we compare our approach to existing work and evaluate our prototype implementation on a range of examples.

Source: Proceedings of the ACM on Programming Languages

DOI: 10.1145/3798220

Authors: Mickaël Laurent, Jan Vitek

Institutions: Charles University, Czech Technical University in Prague

Language: English

Topic: Logic, programming, and type systems

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: diamond

Funder: Ministerstvo Školství, Mládeže a Tělovýchovy

OpenAlex ID: W7153239283

FWCI: 3.552

Cites: 20

Cited by: 1

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