A Virtual Machine for Functional Logic Computations

Antoy, Sergio; Hanus, Michael; Liu, Jimeng; Tolmach, Andrew

doi:10.1007/11431664_7

Cited by 20 publications

(19 citation statements)

References 18 publications

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“…In the introduction we already discussed the various efforts to implement functional logic languages, like the construction of abstract machines [9,27,32] and the compilation into Prolog [5] or Haskell [13,15,16]. Our benchmarks show that an efficient implementation by compiling into a functional language depends on carefully handling the sharing of non-deterministic choices.…”

Section: Conclusion and Related Workmentioning

confidence: 99%

“…One possible approach is the design of new abstract machines appropriately supporting these operational features and implementing them in some (typically, imperative) language, like C [32] or Java [9,27]. Another approach is the reuse of already existing implementations of some of these features by translating functional logic programs into either logic or functional languages.…”

Section: Introductionmentioning

confidence: 99%

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KiCS2: A New Compiler from Curry to Haskell

Braßel

Hanus

Peemöller

et al. 2011

Functional and Constraint Logic Programming

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Abstract. In this paper we present our first steps towards a new system to compile functional logic programs of the source language Curry into purely functional Haskell programs. Our implementation is based on the idea to represent non-deterministic results as values of the data types corresponding to the results. This enables the application of various search strategies to extract values from the search space. We show by several benchmarks that our implementation can compete with or outperform other existing implementations of Curry.

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Section: Conclusion and Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

KiCS2: A New Compiler from Curry to Haskell

Braßel

Hanus

Peemöller

et al. 2011

Functional and Constraint Logic Programming

Self Cite

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“…In contrast to our approach, however, KiCS provides sharing of deterministic expressions across non-deterministic computations [7]. Regarding (c), sharing across non-determinism is also provided by FLVM, the abstract machine described in [5], which is implemented in Java. The FLVM has undergone substantial changes from the implementation described in [5], and can still be considered to be in an experimental state.…”

Section: Conclusion and Related Workmentioning

confidence: 99%

“…Regarding (c), sharing across non-determinism is also provided by FLVM, the abstract machine described in [5], which is implemented in Java. The FLVM has undergone substantial changes from the implementation described in [5], and can still be considered to be in an experimental state. Finally, the MCC [18] is based on an abstract machine implemented in C. The MCC provides a programatic approach to support different search strategies, i.e., the Curry programmer can influence the search strategy by calling primitive operators provided in this system.…”

Section: Conclusion and Related Workmentioning

confidence: 99%

“…Many older implementations (e.g., [11,16,18]) are based on Prolog's depth-first backtracking strategy to explore the search space. Since this strategy leads to operational incompleteness and reduces the potential of modern architectures for parallelism, more recent implementations of functional logic languages offer more flexible search strategies (e.g., [5,7]). In order to avoid separate implementations for different strategies, it would be desirable to specify the search strategy (e.g., depth-first, breadth-first, parallel) as a parameter of the implementation.…”

Section: Introductionmentioning

confidence: 99%

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Transforming Functional Logic Programs into Monadic Functional Programs

Braßel¹,

Fischer²,

Hanus³

et al. 2011

Functional and Constraint Logic Programming

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Abstract. We present a high-level transformation scheme to translate lazy functional logic programs into pure Haskell programs. This transformation is based on a recent proposal to efficiently implement lazy non-deterministic computations in Haskell into monadic style. We build on this work and define a systematic method to transform lazy functional logic programs into monadic programs with explicit sharing. This results in a transformation scheme which produces high-level and flexible target code. For instance, the target code is parametric w.r.t. the concrete evaluation monad. Thus, different monad instances could, for example, define different search strategies (e.g., depth-first, breadth-first, parallel). We formally describe the basic compilation scheme and some useful extensions.

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Overlapping Rules and Logic Variables in Functional Logic Programs

2006

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Abstract. Functional logic languages extend purely functional languages with two features: operations defined by overlapping rules and logic variables in both defining rules and expressions to evaluate. In this paper, we show that only one of these features is sufficient in a core language. On the one hand, overlapping rules can be eliminated by introducing logic variables in rules. On the other hand, logic variables can be eliminated by introducing operations defined by overlapping rules. The proposed transformations between different classes of programs not only give a better understanding of the features of functional logic programs but also may simplify implementations of functional logic languages. MotivationFunctional logic languages [20] integrate the best features of functional and logic languages in order to provide a variety of programming concepts. For instance, the concepts of demand-driven evaluation and higher-order functions from functional programming can be combined with logic programming features like computing with partial information (logic variables), constraint solving, and nondeterministic search for solutions. In contrast to purely functional languages, functional logic languages allow computations with overlapping rules (i.e., more than one rule can be applied to evaluate a function call) and logic variables (i.e., unbound variables occurring in the initial expression and/or rules, also called extra variables). Operationally, these features are supported by nondeterministic computation steps.Functional logic languages are modeled by constructor-based term rewriting systems (TRS) with narrowing as the evaluation mechanism. A crucial choice in the design of a language, both at the source level and the implementation level, is the class of rewrite systems used to model the programs. Early languages (e.g., ) were modeled by weakly orthogonal, constructor-based TRSs. Larger classes are more expressive, i.e., programs in

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A Virtual Machine for Functional Logic Computations

Cited by 20 publications

References 18 publications

KiCS2: A New Compiler from Curry to Haskell

KiCS2: A New Compiler from Curry to Haskell

Transforming Functional Logic Programs into Monadic Functional Programs

Overlapping Rules and Logic Variables in Functional Logic Programs

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