Local Type Inference Research Articles

Bidirectional Typing

Bidirectional typing combines two modes of typing: type checking, which checks that a program satisfies a known type, and type synthesis, which determines a type from the program. Using checking enables bidirectional typing to support features for which inference is undecidable; using synthesis enables bidirectional typing to avoid the large annotation burden of explicitly typed languages. In addition, bidirectional typing improves error locality. We highlight the design principles that underlie bidirectional type systems, survey the development of bidirectional typing from the prehistoric period before Pierce and Turner’s local type inference to the present day, and provide guidance for future investigations.

A systematic approach to deriving incremental type checkers

Static typing can guide programmers if feedback is immediate. Therefore, all major IDEs incrementalize type checking in some way. However, prior approaches to incremental type checking are often specialized and hard to transfer to new type systems. In this paper, we propose a systematic approach for deriving incremental type checkers from textbook-style type system specifications. Our approach is based on compiling inference rules to Datalog, a carefully limited logic programming language for which incremental solvers exist. The key contribution of this paper is to discover an encoding of the infinite typing relation as a finite Datalog relation in a way that yields efficient incremental updates. We implemented the compiler as part of a type system DSL and show that it supports simple types, some local type inference, operator overloading, universal types, and iso-recursive types.

Analyzing the Adoption Rate of Local Variable Type Inference in Open-source Java 10 Projects

Analyzing the Adoption Rate of Local Variable Type Inference in Open-source Java 10 Projects

Local refinement typing

We introduce the FUSION algorithm for local refinement type inference, yielding a new SMT-based method for verifying programs with polymorphic data types and higher-order functions. FUSION is concise as the programmer need only write signatures for (externally exported) top-level functions and places with cyclic (recursive) dependencies, after which FUSION can predictably synthesize the most precise refinement types for all intermediate terms (expressible in the decidable refinement logic), thereby checking the program without false alarms. We have implemented FUSION and evaluated it on the benchmarks from the LiquidHaskell suite totalling about 12KLOC. FUSION checks an existing safety benchmark suite using about half as many templates as previously required and nearly 2 × faster. In a new set of theorem proving benchmarks FUSION is both 10 — 50 × faster and, by synthesizing the most precise types, avoids false alarms to make verification possible.

LaCasa: lightweight affinity and object capabilities in Scala

Aliasing is a known source of challenges in the context of imperative object-oriented languages, which have led to important advances in type systems for aliasing control. However, their large-scale adoption has turned out to be a surprisingly difficult challenge. While new language designs show promise, they do not address the need of aliasing control in existing languages. This paper presents a new approach to isolation and uniqueness in an existing, widely-used language, Scala. The approach is unique in the way it addresses some of the most important obstacles to the adoption of type system extensions for aliasing control. First, adaptation of existing code requires only a minimal set of annotations. Only a single bit of information is required per class. Surprisingly, the paper shows that this information can be provided by the object-capability discipline, widely-used in program security. We formalize our approach as a type system and prove key soundness theorems. The type system is implemented for the full Scala language, providing, for the first time, a sound integration with Scala's local type inference. Finally, we empirically evaluate the conformity of existing Scala open-source code on a corpus of over 75,000 LOC.

Polymorphic Functions with Set-Theoretic Types

This article is the second part of a two articles series about the definition of higher order polymorphic functions in a type system with recursive types and set-theoretic type connectives (unions, intersections, and negations). In the first part, presented in a companion paper, we defined and studied the syntax, semantics, and evaluation of the explicitly-typed version of a calculus, in which type instantiation is driven by explicit instantiation annotations. In this second part we present a local type inference system that allows the programmer to omit explicit instantiation annotations for function applications, and a type reconstruction system that allows the programmer to omit explicit type annotations for function definitions. The work presented in the two articles provides the theoretical foundations and technical machinery needed to design and implement higher-order polymorphic functional languages with union and intersection types and/or for semi-structured data processing.

Late data layout

Values need to be represented differently when interacting with certain language features. For example, an integer has to take an object-based representation when interacting with erased generics, although, for performance reasons, the stack-based value representation is better. To abstract over these implementation details, some programming languages choose to expose a unified high-level concept (the integer) and let the compiler choose its exact representation and insert coercions where necessary. This pattern appears in multiple language features such as value classes, specialization and multi-stage programming: they all expose a unified concept which they later refine into multiple representations. Yet, the underlying compiler implementations typically entangle the core mechanism with assumptions about the alternative representations and their interaction with other language features. In this paper we present the Late Data Layout mechanism, a simple but versatile type-driven generalization that subsumes and improves the state-of-the-art representation transformations. In doing so, we make two key observations: (1) annotated types conveniently capture the semantics of using multiple representations and (2) local type inference can be used to consistently and optimally introduce coercions. We validated our approach by implementing three language features as Scala compiler extensions: value classes, specialization (using the miniboxing representation) and a simplified multi-stage programming mechanism.

Polymorphic functions with set-theoretic types

This article is the first part of a two articles series about a calculus with higher-order polymorphic functions, recursive types with arrow and product type constructors and set-theoretic type connectives (union, intersection, and negation). In this first part we define and study the explicitly-typed version of the calculus in which type instantiation is driven by explicit instantiation annotations. In particular, we define an explicitly-typed lambda-calculus with intersection types and an efficient evaluation model for it. In the second part, presented in a companion paper, we define a local type inference system that allows the programmer to omit explicit instantiation annotations, and a type reconstruction system that allows the programmer to omit explicit type annotations. The work presented in the two articles provides the theoretical foundations and technical machinery needed to design and implement higher-order polymorphic functional languages for semi-structured data.

AspectML

This article defines AspectML, a typed functional, aspect-oriented programming language. The main contribution of AspectML is the seamless integration of polymorphism, run-time type analysis and aspect-oriented programming language features. In particular, AspectML allows programmers to define type-safe polymorphic advice using pointcuts constructed from a collection of polymorphic join points. AspectML also comes equipped with a type inference algorithm that conservatively extends Hindley--Milner type inference. To support first-class polymorphic point-cut designators, a crucial feature for developing aspect-oriented profiling or logging libraries, the algorithm blends the conventional Hindley--Milner type inference algorithm with a simple form of local type inference. We give our language operational meaning via a type-directed translation into an expressive type-safe intermediate language. Many complexities of the source language are eliminated in this translation, leading to a modular specification of its semantics. One of the novelties of the intermediate language is the definition of polymorphic labels for marking control-flow points. When a set of labels is assembled as a pointcut, the type of each label is an instance of the type of the pointcut.

Practical type inference for arbitrary-rank types

AbstractHaskell's popularity has driven the need for ever more expressive type system features, most of which threaten the decidability and practicality of Damas-Milner type inference. One such feature is the ability to write functions with higher-rank types – that is, functions that take polymorphic functions as their arguments. Complete type inference is known to be undecidable for higher-rank (impredicative) type systems, but in practice programmers are more than willing to add type annotations to guide the type inference engine, and to document their code. However, the choice of just what annotations are required, and what changes are required in the type system and its inference algorithm, has been an ongoing topic of research. We take as our starting point a λ-calculus proposed by Odersky and Läufer. Their system supports arbitrary-rank polymorphism through the exploitation of type annotations on λ-bound arguments and arbitrary sub-terms. Though elegant, and more convenient than some other proposals, Odersky and Läufer's system requires many annotations. We show how to use local type inference (invented by Pierce and Turner) to greatly reduce the annotation burden, to the point where higher-rank types become eminently usable. Higher-rank types have a very modest impact on type inference. We substantiate this claim in a very concrete way, by presenting a complete type-inference engine, written in Haskell, for a traditional Damas-Milner type system, and then showing how to extend it for higher-rank types. We write the type-inference engine using a monadic framework: it turns out to be a particularly compelling example of monads in action. The paper is long, but is strongly tutorial in style. Although we use Haskell as our example source language, and our implementation language, much of our work is directly applicable to any ML-like functional language.

Region-based memory management in cyclone

Cyclone is a type-safe programming language derived from C. The primary design goal of Cyclone is to let programmers control data representation and memory management without sacrificing type-safety. In this paper, we focus on the region-based memory management of Cyclone and its static typing discipline. The design incorporates several advancements, including support for region subtyping and a coherent integration with stack allocation and a garbage collector. To support separate compilation, Cyclone requires programmers to write some explicit region annotations, but a combination of default annotations, local type inference, and a novel treatment of region effects reduces this burden. As a result, we integrate C idioms in a region-based framework. In our experience, porting legacy C to Cyclone has required altering about 8% of the code; of the changes, only 6% (of the 8%) were region annotations.

Colored local type inference

We present a type system for a language based on F ≤, which allows certain type annotations to be elided in actual programs. Local type inference determines types by a combination of type propagation and local constraint solving, rather than by global constraint solving. We re ne the previously existing local type inference system of Pierce and Turner[PT98] by allowing partial type information to be propagated. This is expressed by coloring types to indicate propagation directions. Propagating partial type information allows us to omit type annotations for the visitor pattern, the analogue of pattern matching in languages without sum types.

Local type inference

We study two partial type inference methods for a language combining subtyping and impredicative polymorphism. Both methods are local in the sense that missing annotations are recovered using only information from adjacent nodes in the syntax tree, without long-distance constraints such as unification variables. One method infers type arguments in polymorphic applications using a local constraint solver. The other infers annotations on bound variables in function abstractions by propagating type constraints downward from enclosing application nodes. We motivate our design choices by a statistical analysis of the uses of type inference in a sizable body of existing ML code.