Refinement types for Haskell
By Niki Vazou, Eric L. Seidel, Ranjit Jhala, Dimitrios Vytiniotis, Simon L. Peyton Jones. ACM SIGPLAN International Conference on Functional Programming, 2014
300 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computational Theory and Mathematics
View Paper: https://www.semanticscholar.org/paper/af04e0810d4100e7e04bb96c063c8bf7b3888b94
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
- Earl T. Barr
- Panagiotis Vekris
- Benjamin Cosman
- Pierre-Yves Strub
- Charles Sutton
- Ranjit Jhala
- A. Gordon
- Santiago Zanella-B'eguelin
In Computational Theory and Mathematics
- Panagiotis Vekris
- Benjamin Cosman
- Ranjit Jhala
- Santiago Zanella-B'eguelin
- A. Gordon
- Irene Vlassi Pandi
- Earl T. Barr
- Markulf Kohlweiss
Citations in the corpus
- Dependent types and multi-monadic effects in F* (2016, background): “More recently, old-F ⋆ (Swamy et al. 2013a) adds value-dependent types to an ML-like language; Rondon et al. (2008) add decidable, refinement types to OCaml and Vazou et al. (2014) adapt that work to Haskell—we have compared these prior refinement type systems to F ⋆ in § 3.2.”
- OptTyper: Probabilistic Type Inference by Optimising Logical and Natural Constraints (2020, background): “LiquidHaskell [Vazou et al. 2014] is a static verifier of Haskell based on Liquid Types via SMT and predicate abstraction.”
- Higher-Order Approximate Relational Refinement Types for Mechanism Design and Differential Privacy (2014, unknown): “Figure 2: Relational interpretation of assertions”
- Refinement types for TypeScript (2016, background): “The extensibility and modularity offered by refinement types have enabled their use in a variety of applications in typed, functional languages, like ML [28, 40], Haskell [37], and F ] [33].”