Implementing functional logic languages using multiple threads and stores

Tolmach, Andrew; Antoy, Sergio; Nita, Marius

doi:10.1145/1016850.1016865

Cited by 7 publications

(4 citation statements)

References 16 publications

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“…For instance, specific instructions to handle computations that use overlapping rules need not be considered in an abstract machine if the OE transformation is applied in the compilation process. This is done in the implementations described in [15,30], although without any formal justification. Likewise, the handling of logic variables (e.g., data structures such as binding arrays and binding instructions) can be removed if the XEP transformation is applied.…”

Section: Resultsmentioning

confidence: 99%

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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Section: Resultsmentioning

confidence: 99%

Overlapping Rules and Logic Variables in Functional Logic Programs

2006

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“…In [22], Tolmach, Antoy, and Nita describe a definitional interpreter for Curry-like languages based on the semantics of Albert, et al [1]. The primary contrast with the present work is in the treatment of the heap.…”

Section: Conclusion and Related Workmentioning

confidence: 89%

“…The primary contrast with the present work is in the treatment of the heap. Rather than conceiving of the system as a graph rewriting engine that generates modified copies of the source term as it runs, [22] treats the program as fixed, read-only code that operates on multiple variant versions of the heap. A direct performance comparison between these two approaches remains to be made.…”

Section: Conclusion and Related Workmentioning

confidence: 99%

A Virtual Machine for Functional Logic Computations

Antoy

Hanus

Liu

et al. 2005

Implementation and Application of Functional Languages

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Abstract.We describe the architecture of a virtual machine for executing functional logic programming languages. A distinguishing feature of our machine is that it preserves the operational completeness of non-deterministic programs by concurrently executing a pool of independent computations. Each computation executes only root-needed sequential narrowing steps. We describe the machine's architecture and instruction set, and show how to compile overlapping inductively sequential programs to sequences of machine instructions. The machine has been implemented in Java and in Standard ML.

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“…In typical interpreters, if and when the computation of either completes, the result is consumed, e.g., printed, and the user is given the option to either terminate the execution or continue with the computation of the other. Copying is simpler than backtracking and it is used in some experimental implementations of functional logic languages Tolmach et al 2004). …”

Section: Previous Approachesmentioning

confidence: 99%

On the correctness of pull-tabbing

Antoy¹

2011

Theory and Practice of Logic Programming

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Pull-tabbing is an evaluation approach for functional logic computations, based on a graph transformation recently proposed, which avoids making irrevocable non-deterministic choices that would jeopardize the completeness of computations. In contrast to other approaches with this property, it does not require an upfront cloning of a possibly large portion of the choice's context. We formally define the pull-tab transformation, characterize the class of programs for which the transformation is intended, extend the computations in these programs to include the transformation, and prove the correctness of the extended computations.

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Implementing functional logic languages using multiple threads and stores

Cited by 7 publications

References 16 publications

Overlapping Rules and Logic Variables in Functional Logic Programs

Overlapping Rules and Logic Variables in Functional Logic Programs

A Virtual Machine for Functional Logic Computations

On the correctness of pull-tabbing

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