Modular Inference of Linear Types for Multiplicity-Annotated Arrows

Bernardy et al. [2018] proposed a linear type system $\lambda^q_\to$ as a core type system of Linear Haskell. In the system, linearity is represented by annotated arrow types $A \to_m B$, where $m$ denotes the multiplicity of the argument. Thanks to this representation, existing non-linear code typechecks as it is, and newly written linear code can be used with existing non-linear code in many cases. However, little is known about the type inference of $\lambda^q_\to$. Although the Linear Haskell implementation is equipped with type inference, its algorithm has not been formalized, and the implementation often fails to infer principal types, especially for higher-order functions. In this paper, based on OutsideIn(X) [Vytiniotis et al., 2011], we propose an inference system for a rank 1 qualified-typed variant of $\lambda^q_\to$, which infers principal types. A technical challenge in this new setting is to deal with ambiguous types inferred by naive qualified typing. We address this ambiguity issue through quantifier elimination and demonstrate the effectiveness of the approach with examples.Comment: The full version of our paper to appear in ESOP 202

Safe zero-cost coercions for Haskell

Generative type abstractions – present in Haskell, OCaml, and other languages – are useful concepts to help prevent programmer errors. They serve to create new types that are distinct at compile time but share a run-time representation with some base type. We present a new mechanism that allows for zero-cost conversions between generative type abstractions and their representations, even when such types are deeply nested. We prove type safety in the presence of these conversions and have implemented our work in GHC

Safe zero-cost coercions for Haskell

Generative type abstractions – present in Haskell, OCaml, and other languages – are useful concepts to help prevent programmer errors. They serve to create new types that are distinct at compile time but share a run-time representation with some base type. We present a new mechanism that allows for zero-cost conversions between generative type abstractions and their representations, even when such types are deeply nested. We prove type safety in the presence of these conversions and have implemented our work in GHC

Ambivalent Types for Principal Type Inference with GADTs (extended version)

GADTs, short for Generalized Algebraic DataTypes, which allow constructors of algebraic datatypes to be non-surjective, have many useful applications. However, pattern matching on GADTsintroduces local type equality assumptions, which are a source of ambiguities that may destroy principal types---and must be resolved by type annotations. We introduce ambivalent types to tighten the definition of ambiguities and better confine them, so that type inference has principal types, remains monotonic, and requires fewer type annotations

Constraint Handling Rules with Binders, Patterns and Generic Quantification

Constraint Handling Rules provide descriptions for constraint solvers. However, they fall short when those constraints specify some binding structure, like higher-rank types in a constraint-based type inference algorithm. In this paper, the term syntax of constraints is replaced by $\lambda$-tree syntax, in which binding is explicit; and a new $\nabla$ generic quantifier is introduced, which is used to create new fresh constants.Comment: Paper presented at the 33nd International Conference on Logic Programming (ICLP 2017), Melbourne, Australia, August 28 to September 1, 2017 16 pages, LaTeX, no PDF figure

Dependent Types In Haskell: Theory And Practice

Haskell, as implemented in the Glasgow Haskell Compiler (GHC), has been adding new type-level programming features for some time. Many of these features---generalized algebraic datatypes (GADTs), type families, kind polymorphism, and promoted datatypes---have brought Haskell to the doorstep of dependent types. Many dependently typed programs can even currently be encoded, but often the constructions are painful. In this dissertation, I describe Dependent Haskell, which supports full dependent types via a backward-compatible extension to today\u27s Haskell. An important contribution of this work is an implementation, in GHC, of a portion of Dependent Haskell, with the rest to follow. The features I have implemented are already released, in GHC 8.0. This dissertation contains several practical examples of Dependent Haskell code, a full description of the differences between Dependent Haskell and today\u27s Haskell, a novel dependently typed lambda-calculus (called Pico) suitable for use as an intermediate language for compiling Dependent Haskell, and a type inference and elaboration algorithm, Bake, that translates Dependent Haskell to type-correct Pico. Full proofs of type safety of Pico and the soundness of Bake are included in the appendix

The Thoralf Plugin: For Your Fancy Type Needs

Many fancy types (e.g., generalized algebraic data types, type families) require a type checker plugin. These fancy types have a type index (e.g., type level natural numbers) with an equality relation that is difficult or impossible to represent using GHC’s built-in type equality. The most practical way to represent these equality relations is through a plugin that asserts equality constraints. However, such plugins are difficult to write and reason about. In this paper, we (1) present a formal theory of reasoning about the correctness of type checker plugins for type indices, and, (2) apply this theory in creating Thoralf, a generic and extensible plugin for type indices that translates GHC constraint problems to queries to an external SMT solver. By “generic and extensible”, we mean the restrictions on extending Thoralf are slight, and, if some type index could be encoded as an SMT sort, then a programmer could extend Thoralf by providing this encoding function

Sound and complete bidirectional typechecking for higher-rank polymorphism with existentials and indexed types

Bidirectional typechecking, in which terms either synthesize a type or are checked against a known type, has become popular for its applicability to a variety of type systems, its error reporting, and its ease of implementation. Following principles from proof theory, bidirectional typing can be applied to many type constructs. The principles underlying a bidirectional approach to indexed types (generalized algebraic datatypes) are less clear. Building on proof-theoretic treatments of equality, we give a declarative specification of typing based on focalization. This approach permits declarative rules for coverage of pattern matching, as well as support for first-class existential types using a focalized subtyping judgment. We use refinement types to avoid explicitly passing equality proofs in our term syntax, making our calculus similar to languages such as Haskell and OCaml. We also extend the declarative specification with an explicit rules for deducing when a type is principal, permitting us to give a complete declarative specification for a rich type system with significant type inference. We also give a set of algorithmic typing rules, and prove that it is sound and complete with respect to the declarative system. The proof requires a number of technical innovations, including proving soundness and completeness in a mutually recursive fashion.EPSRC grant EP/N02706X/