GOFFIN: Higher-order functions meet concurrent constraints

Chakravarty, Manual M. T.; Guo, Yike; Köhler, Martin; Lock, Hendrik C. R.

doi:10.1016/s0167-6423(97)00010-5

Cited by 12 publications

(5 citation statements)

References 7 publications

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“…νy A→A . ((cy • = x); y x) can be built, so 8 Precisely, t(n) = {fn} with fn(m) = {(n, m)}. some form of positivity condition should be imposed.…”

Section: Discussionmentioning

confidence: 99%

“…Miller [20] proposes a language with lambda-abstraction and a decidable extension of first-order unification which admits most general unifiers. Chakravarty et al [8] and Smolka [29] propose languages in which the functional-logic paradigm is modeled as a concurrent process with communication. Albert et al [1] formulate a big-step semantics for a functional-logic calculus with narrowing.…”

Section: Discussionmentioning

confidence: 99%

“…the constructors 1 : Nat, 2 : Nat are given their obvious interpretations and t : Nat → Nat → Tuple is the pairing function 8 , then for any environment ρ, if we abbreviate ρ…”

Section: N (Noting That Values Are Singletons By the Previous Item Of...mentioning

confidence: 99%

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Semantics of a Relational λ-Calculus (Extended Version)

Barenbaum,

Lochbaum,

Milicich

2020

Preprint

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We extend the λ-calculus with constructs suitable for relational and functional-logic programming: non-deterministic choice, fresh variable introduction, and unification of expressions. In order to be able to unify λ-expressions and still obtain a confluent theory, we depart from related approaches, such as λProlog, in that we do not attempt to solve higher-order unification. Instead, abstractions are decorated with a location, which intuitively may be understood as its memory address, and we impose a simple coherence invariant: abstractions in the same location must be equal. This allows us to formulate a confluent small-step operational semantics which only performs first-order unification and does not require strong evaluation (below lambdas). We study a simply typed version of the system. Moreover, a denotational semantics for the calculus is proposed and reduction is shown to be sound with respect to the denotational semantics.

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“…νy A→A . ((cy • = x); y x) can be built, so 8 Precisely, t(n) = {fn} with fn(m) = {(n, m)}. some form of positivity condition should be imposed.…”

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Semantics of a Relational λ-Calculus (Extended Version)

Barenbaum,

Lochbaum,

Milicich

2020

Preprint

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“…Several recent distributed Haskell designs use declarative coordination: Distributed Haskell (Chakravarty et al, 1998b) and Curry (Hanus, 1999) use logic-based coordination languages, while Brisk uses annotations, and an elaborated semantics (Holyer et al, 1998). Distributed Haskell coordinates distribution with a constraint programming language.…”

Section: Declarative Coordinationmentioning

confidence: 99%

“…Distributed Haskell coordinates distribution with a constraint programming language. It evolved from the Goffin parallel programming language (Chakravarty et al, 1998b) although a full implementation has not been constructed (Chakravarty et al, 1998a). Concurrently executing processes are called agents, and Distributed Haskell adds language constructs for agent placement and introduces temporal constraints to the language to deal with timeouts and potentially provide fault tolerance.…”

Section: Declarative Coordinationmentioning

confidence: 99%

Parallel and Distributed Haskells

2002

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Parallel and distributed languages specify computations on multiple processors and have a computation language to describe the algorithm, i.e. what to compute, and a coordination language to describe how to organise the computations across the processors. Haskell has been used as the computation language for a wide variety of parallel and distributed languages, and this paper is a comprehensive survey of implemented languages. We outline parallel and distributed language concepts and classify Haskell extensions using them. Similar example programs are used to illustrate and contrast the coordination languages, and the comparison is facilitated by the common computation language. A lazy language is not an obvious choice for parallel or distributed computation, and we address the question of why Haskell is a common functional computation language.

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