438 research outputs found
Doo bee doo bee doo
We explore the design and implementation of Frank, a strict functional programming language with a bidirectional effect type system designed from the ground up around a novel variant of Plotkin and Pretnar's effect handler abstraction. Effect handlers provide an abstraction for modular effectful programming: a handler acts as an interpreter for a collection of commands whose interfaces are statically tracked by the type system. However, Frank eliminates the need for an additional effect handling construct by generalising the basic mechanism of functional abstraction itself. A function is but the special case of a Frank operator that interprets no commands. Moreover, Frank's operators can be multihandlers which simultaneously interpret commands from several sources at once, without disturbing the direct style of functional programming with values. Effect typing in Frank employs a novel form of effect polymorphism which avoids mentioning effect variables in source code. This is achieved by propagating an ambient ability inwards, rather than accumulating unions of potential effects outwards. With the ambient ability describing the effects that are available at a certain point in the code, it can become necessary to reconfigure access to the ambient ability. A primary goal is to be able to encapsulate internal effects, eliminating a phenomenon we call effect pollution. Moreover, it is sometimes desirable to rewire the effect flow between effectful library components. We propose adaptors as a means for supporting both effect encapsulation and more general rewiring. Programming with effects and handlers is in its infancy. We contribute an exploration of future possibilities, particularly in combination with other forms of rich type systems
Reify Your Collection Queries for Modularity and Speed!
Modularity and efficiency are often contradicting requirements, such that
programers have to trade one for the other. We analyze this dilemma in the
context of programs operating on collections. Performance-critical code using
collections need often to be hand-optimized, leading to non-modular, brittle,
and redundant code. In principle, this dilemma could be avoided by automatic
collection-specific optimizations, such as fusion of collection traversals,
usage of indexing, or reordering of filters. Unfortunately, it is not obvious
how to encode such optimizations in terms of ordinary collection APIs, because
the program operating on the collections is not reified and hence cannot be
analyzed.
We propose SQuOpt, the Scala Query Optimizer--a deep embedding of the Scala
collections API that allows such analyses and optimizations to be defined and
executed within Scala, without relying on external tools or compiler
extensions. SQuOpt provides the same "look and feel" (syntax and static typing
guarantees) as the standard collections API. We evaluate SQuOpt by
re-implementing several code analyses of the Findbugs tool using SQuOpt, show
average speedups of 12x with a maximum of 12800x and hence demonstrate that
SQuOpt can reconcile modularity and efficiency in real-world applications.Comment: 20 page
Versatile event correlation with algebraic effects
We present the first language design to uniformly express variants of
n
-way joins over asynchronous event streams from different domains, e.g., stream-relational algebra, event processing, reactive and concurrent programming. We model asynchronous reactive programs and joins in direct style, on top of algebraic effects and handlers. Effect handlers act as modular interpreters of event notifications, enabling fine-grained control abstractions and customizable event matching. Join variants can be considered as cartesian product computations with ”degenerate” control flow, such that unnecessary tuples are not materialized a priori. Based on this computational interpretation, we decompose joins into a generic, naive enumeration procedure of the cartesian product, plus variant-specific extensions, represented in terms of user-supplied effect handlers. Our microbenchmarks validate that this extensible design avoids needless materialization. Alongside a formal semantics for joining and prototypes in Koka and multicore OCaml, we contribute a systematic comparison of the covered domains and features.
ERC, Advanced Grant No. 321217
ERC, Consolidator Grant No. 617805
DFG, SFB 1053
DFG, SA 2918/2-
Effect handlers via generalised continuations
Plotkin and Pretnar's effect handlers offer a versatile abstraction for modular programming with user-defined effects. This paper focuses on foundations for implementing effect handlers, for the three different kinds of effect handlers that have been proposed in the literature: deep, shallow, and parameterised. Traditional deep handlers are defined by folds over computation trees, and are the original construct proposed by Plotkin and Pretnar. Shallow handlers are defined by case splits (rather than folds) over computation trees. Parameterised handlers are deep handlers extended with a state value that is threaded through the folds over computation trees. We formulate the extensions both directly and via encodings in terms of deep handlers, and illustrate how the direct implementations avoid the generation of unnecessary closures. We give two distinct foundational implementations of all the kinds of handlers we consider: a continuation passing style (CPS) transformation and a CEK-style abstract machine. In both cases, the key ingredient is a generalisation of the notion of continuation to accommodate stacks of effect handlers. We obtain our CPS translation through a series of refinements as follows. We begin with a first-order CPS translation into untyped lambda calculus which manages a stack of continuations and handlers as a curried sequence of arguments. We then refine the initial CPS translation by uncurrying it to yield a properly tail-recursive translation, and then moving towards more and more intensional representations of continuations in order to support different kinds of effect handlers. Finally, we make the translation higher-order in order to contract administrative redexes at translation time. Our abstract machine design then uses the same generalised continuation representation as the CPS translation. We have implemented both the abstract machine and the CPS transformation (plus extensions) as backends for the Links web programming language
Types and Semantics for Extensible Data Types (Extended Version)
Developing and maintaining software commonly requires (1) adding new data
type constructors to existing applications, but also (2) adding new functions
that work on existing data. Most programming languages have native support for
defining data types and functions in a way that supports either (1) or (2), but
not both. This lack of native support makes it difficult to use and extend
libraries. A theoretically well-studied solution is to define data types and
functions using initial algebra semantics. While it is possible to encode this
solution in existing programming languages, such encodings add syntactic and
interpretive overhead, and commonly fail to take advantage of the map and fold
fusion laws of initial algebras which compilers could exploit to generate more
efficient code. A solution to these is to provide native support for initial
algebra semantics. In this paper, we develop such a solution and present a type
discipline and core calculus for a language with native support for initial
algebra semantics.Comment: Extended version (28 pages) of the eponymous paper to appear in the
conference proceedings of APLAS 202
Modular Probabilistic Models via Algebraic Effects
Probabilistic programming languages (PPLs) allow programmers to construct
statistical models and then simulate data or perform inference over them. Many
PPLs restrict models to a particular instance of simulation or inference,
limiting their reusability. In other PPLs, models are not readily composable.
Using Haskell as the host language, we present an embedded domain specific
language based on algebraic effects, where probabilistic models are modular,
first-class, and reusable for both simulation and inference. We also
demonstrate how simulation and inference can be expressed naturally as
composable program transformations using algebraic effect handlers
Programming with Purity Reflection: Peaceful Coexistence of Effects, Laziness, and Parallelism
We present purity reflection, a programming language feature that enables higher-order functions to inspect the purity of their function arguments and to vary their behavior based on this information. The upshot is that operations on data structures can selectively use lazy and/or parallel evaluation while ensuring that side effects are never lost or re-ordered. The technique builds on a recent Hindley-Milner style type and effect system based on Boolean unification which supports both effect polymorphism and complete type inference. We illustrate that avoiding the so-called \u27poisoning problem\u27 is crucial to support purity reflection.
We propose several new data structures that use purity reflection to switch between eager and lazy, sequential and parallel evaluation. We propose a DelayList, which is maximally lazy but switches to eager evaluation for impure operations. We also propose a DelayMap which is maximally lazy in its values, but also exploits eager and parallel evaluation.
We implement purity reflection as an extension of the Flix programming language. We present a new effect-aware form of monomorphization that eliminates purity reflection at compile-time. And finally, we evaluate the cost of this new monomorphization on compilation time and on code size, and determine that it is minimal
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