6,899 research outputs found
Liquidate your assets: reasoning about resource usage in liquid Haskell
Liquid Haskell is an extension to the type system of Haskell that supports formal reasoning about program correctness by encoding logical properties as refinement types. In this article, we show how Liquid Haskell can also be used to reason about program efficiency in the same setting. We use the system’s existing verification machinery to ensure that the results of our cost analysis are valid, together with custom invariants for particular program contexts to ensure that the results of our analysis are precise. To illustrate our approach, we analyse the efficiency of a wide range of popular data structures and algorithms, and in doing so, explore various notions of resource usage. Our experience is that reasoning about efficiency in Liquid Haskell is often just as simple as reasoning about correctness, and that the two can naturally be combined
Gradual Liquid Type Inference
Liquid typing provides a decidable refinement inference mechanism that is
convenient but subject to two major issues: (1) inference is global and
requires top-level annotations, making it unsuitable for inference of modular
code components and prohibiting its applicability to library code, and (2)
inference failure results in obscure error messages. These difficulties
seriously hamper the migration of existing code to use refinements. This paper
shows that gradual liquid type inference---a novel combination of liquid
inference and gradual refinement types---addresses both issues. Gradual
refinement types, which support imprecise predicates that are optimistically
interpreted, can be used in argument positions to constrain liquid inference so
that the global inference process e effectively infers modular specifications
usable for library components. Dually, when gradual refinements appear as the
result of inference, they signal an inconsistency in the use of static
refinements. Because liquid refinements are drawn from a nite set of
predicates, in gradual liquid type inference we can enumerate the safe
concretizations of each imprecise refinement, i.e. the static refinements that
justify why a program is gradually well-typed. This enumeration is useful for
static liquid type error explanation, since the safe concretizations exhibit
all the potential inconsistencies that lead to static type errors. We develop
the theory of gradual liquid type inference and explore its pragmatics in the
setting of Liquid Haskell.Comment: To appear at OOPSLA 201
Functional Extensionality for Refinement Types
Refinement type checkers are a powerful way to reason about functional
programs. For example, one can prove properties of a slow, specification
implementation, porting the proofs to an optimized implementation that behaves
the same. Without functional extensionality, proofs must relate functions that
are fully applied. When data itself has a higher-order representation, fully
applied proofs face serious impediments! When working with first-order data,
fully applied proofs lead to noisome duplication when using higher-order
functions.
While dependent type theories are typically consistent with functional
extensionality axioms, refinement type systems with semantic subtyping treat
naive phrasings of functional extensionality inconsistently, leading to
unsoundness. We demonstrate this unsoundness and develop a new approach to
equality in Liquid Haskell: we define a propositional equality in a library we
call PEq. Using PEq avoids the unsoundness while still proving useful
equalities at higher types; we demonstrate its use in several case studies. We
validate PEq by building a small model and developing its metatheory.
Additionally, we prove metaproperties of PEq inside Liquid Haskell itself using
an unnamed folklore technique, which we dub `classy induction'
Bounded Refinement Types
We present a notion of bounded quantification for refinement types and show
how it expands the expressiveness of refinement typing by using it to develop
typed combinators for: (1) relational algebra and safe database access, (2)
Floyd-Hoare logic within a state transformer monad equipped with combinators
for branching and looping, and (3) using the above to implement a refined IO
monad that tracks capabilities and resource usage. This leap in expressiveness
comes via a translation to "ghost" functions, which lets us retain the
automated and decidable SMT based checking and inference that makes refinement
typing effective in practice.Comment: 14 pages, International Conference on Functional Programming, ICFP
201
A Modular Toolkit for Distributed Interactions
We discuss the design, architecture, and implementation of a toolkit which
supports some theories for distributed interactions. The main design principles
of our architecture are flexibility and modularity. Our main goal is to provide
an easily extensible workbench to encompass current algorithms and incorporate
future developments of the theories. With the help of some examples, we
illustrate the main features of our toolkit.Comment: In Proceedings PLACES 2010, arXiv:1110.385
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