996 research outputs found
Type Inference for Bimorphic Recursion
This paper proposes bimorphic recursion, which is restricted polymorphic
recursion such that every recursive call in the body of a function definition
has the same type. Bimorphic recursion allows us to assign two different types
to a recursively defined function: one is for its recursive calls and the other
is for its calls outside its definition. Bimorphic recursion in this paper can
be nested. This paper shows bimorphic recursion has principal types and
decidable type inference. Hence bimorphic recursion gives us flexible typing
for recursion with decidable type inference. This paper also shows that its
typability becomes undecidable because of nesting of recursions when one
removes the instantiation property from the bimorphic recursion.Comment: In Proceedings GandALF 2011, arXiv:1106.081
Compositional Explanation of Types and Algorithmic Debugging of Type Errors
The type systems of most typed functional programming languages are based on the Hindley-Milner type system. A practical problem with these type systems is that it is often hard to understand why a program is not type correct or a function does not have the intended type. We suggest that at the core of this problem is the difficulty of explaining why a given expression has a certain type. The type system is not defined compositionally. We propose to explain types using a variant of the Hindley-Milner type system that defines a compositional type explanation graph of principal typings. We describe how the programmer understands types by interactive navigation through the explanation graph. Furthermore, the explanation graph can be the foundation for algorithmic debugging of type errors, that is, semi-automatic localisation of the source of a type error without even having to understand the type inference steps. We implemented a prototype of a tool to explore the usefulness of the proposed methods
Inferring Algebraic Effects
We present a complete polymorphic effect inference algorithm for an ML-style
language with handlers of not only exceptions, but of any other algebraic
effect such as input & output, mutable references and many others. Our main aim
is to offer the programmer a useful insight into the effectful behaviour of
programs. Handlers help here by cutting down possible effects and the resulting
lengthy output that often plagues precise effect systems. Additionally, we
present a set of methods that further simplify the displayed types, some even
by deliberately hiding inferred information from the programmer
Practical Subtyping for System F with Sized (Co-)Induction
We present a rich type system with subtyping for an extension of System F.
Our type constructors include sum and product types, universal and existential
quantifiers, inductive and coinductive types. The latter two size annotations
allowing the preservation of size invariants. For example it is possible to
derive the termination of the quicksort by showing that partitioning a list
does not increase its size. The system deals with complex programs involving
mixed induction and coinduction, or even mixed (co-)induction and polymorphism
(as for Scott-encoded datatypes). One of the key ideas is to completely
separate the induction on sizes from the notion of recursive programs. We use
the size change principle to check that the proof is well-founded, not that the
program terminates. Termination is obtained by a strong normalization proof.
Another key idea is the use symbolic witnesses to handle quantifiers of all
sorts. To demonstrate the practicality of our system, we provide an
implementation that accepts all the examples discussed in the paper and much
more
Koka: Programming with Row Polymorphic Effect Types
We propose a programming model where effects are treated in a disciplined
way, and where the potential side-effects of a function are apparent in its
type signature. The type and effect of expressions can also be inferred
automatically, and we describe a polymorphic type inference system based on
Hindley-Milner style inference. A novel feature is that we support polymorphic
effects through row-polymorphism using duplicate labels. Moreover, we show that
our effects are not just syntactic labels but have a deep semantic connection
to the program. For example, if an expression can be typed without an exn
effect, then it will never throw an unhandled exception. Similar to Haskell's
`runST` we show how we can safely encapsulate stateful operations. Through the
state effect, we can also safely combine state with let-polymorphism without
needing either imperative type variables or a syntactic value restriction.
Finally, our system is implemented fully in a new language called Koka and has
been used successfully on various small to medium-sized sample programs ranging
from a Markdown processor to a tier-splitted chat application. You can try out
Koka live at www.rise4fun.com/koka/tutorial.Comment: In Proceedings MSFP 2014, arXiv:1406.153
Set-Theoretic Types for Polymorphic Variants
Polymorphic variants are a useful feature of the OCaml language whose current
definition and implementation rely on kinding constraints to simulate a
subtyping relation via unification. This yields an awkward formalization and
results in a type system whose behaviour is in some cases unintuitive and/or
unduly restrictive. In this work, we present an alternative formalization of
poly-morphic variants, based on set-theoretic types and subtyping, that yields
a cleaner and more streamlined system. Our formalization is more expressive
than the current one (it types more programs while preserving type safety), it
can internalize some meta-theoretic properties, and it removes some
pathological cases of the current implementation resulting in a more intuitive
and, thus, predictable type system. More generally, this work shows how to add
full-fledged union types to functional languages of the ML family that usually
rely on the Hindley-Milner type system. As an aside, our system also improves
the theory of semantic subtyping, notably by proving completeness for the type
reconstruction algorithm.Comment: ACM SIGPLAN International Conference on Functional Programming, Sep
2016, Nara, Japan. ICFP 16, 21st ACM SIGPLAN International Conference on
Functional Programming, 201
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 -tree syntax, in
which binding is explicit; and a new 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
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