Evaluation Of Functional Logic Programs Research Articles

Cost-Augmented Partial Evaluation of Functional Logic Programs

We enhance the narrowing-driven partial evaluation scheme for lazy functional logic programs with the computation of symbolic costs. The enhanced scheme allows us to estimate the effects of the program transformer in a precise framework and, moreover, to quantify these effects. The considered costs are “symbolic” in the sense that they measure the number of basic operations performed during a computation rather than actual execution times. Our scheme may serve as a basis to develop speedup analyses and cost-guided transformers. A cost-augmented partial evaluator, which demonstrates the usefulness of our approach, has been implemented in the multi-paradigm language Curry.

A residualizing semantics for the partial evaluation of functional logic programs

Recent proposals for multi-paradigm declarative programming combine the most important features of functional, logic and concurrent programming into a single framework. The operational semantics of these languages is usually based on a combination of narrowing and residuation. In this paper, we introduce a non-standard, residualizing semantics for multi-paradigm declarative programs and prove its equivalence with a standard operational semantics. Our residualizing semantics is particularly relevant within the area of program transformation where it is useful, e.g., to perform computations during partial evaluation. Thus, the proof of equivalence is a crucial result to demonstrate the correctness of (existing) partial evaluation schemes.

Functional logic overloading

Functional logic overloading is a novel approach to user-defined overloading that extends Haskell's concept of type classes in significant ways. Whereas type classes are conceptually predicates on types in standard Haskell, they are type functions in our approach. Thus, we can base type inference on the evaluation of functional logic programs. Functional logic programming provides a solid theoretical foundation for type functions and, at the same time, allows for programmable overloading resolution strategies by choosing different evaluation strategies for functional logic programs. Type inference with type functions is an instance of type inference with constrained types, where the underlying constraint system is defined by a functional logic program. We have designed a variant of Haskell which supports our approach to overloading, and implemented a prototype front-end for the language.

A unifying view of functional and logic program specialization

We give a general introduction to the particular problems associated with the partial evaluation of functional logic programs, explain the relationship with similar techniques for functional and logic languages, and show that it is useful to transfer the technology of narrowing into a technique for driving specialization in integrated languages. Preliminary version. Final version in Computing Surveys (ACM Press), Vol. 30, No. 3es (Sept. 1998), pp. 9-es, 1998

Partial evaluation of functional logic programs

Languages that integrate functional and logic programming with a complete operational semantics are based on narrowing, a unification-based goal-solving mechanism which subsumes the reduction principle of functional languages and the resolution principle of logic languages. In this article, we present a partial evaluation scheme for functional logic languages based on an automatic unfolding algorithm which builds narrowing trees. The method is formalized within the theoretical framework established by Lloyd and Shepherdson for the partial deduction of logic programs, which we have generalized for dealing with functional computations. A generic specialization algorithm is proposed which does not depend on the eager or lazy nature of the narrower being used. To the best of our knowledge, this is the first generic algorithm for the specialization of functional logic programs. We also discuss the relation to work on partial evaluation in functional programming, term-rewriting systems, and logic programming. Finally, we present some experimental results with an implementation of the algorithm which show in practice that the narrowing-driven partial evaluator effectively combines the propagation of partial data structures (by means of logical variables and unification) with better opportunities for optimization (thanks to the functional dimension).

Specialization of lazy functional logic programs

Partial evaluation is a method for program specialization based on fold/unfold transformations [8, 25]. Partial evaluation of pure functional programs uses mainly static values of given data to specialize the program [15, 44]. In logic programming, the so-called static/dynamic distinction is hardly present, whereas considerations of determinacy and choice points are far more important for control [12]. We discuss these issues in the context of a (lazy) functional logic language. We formalize a two-phase specialization method for a non-strict, first order, integrated language which makes use of lazy narrowing to specialize the program w.r. t. a goal. The basic algorithm (first phase) is formalized as an instance of the framework for the partial evaluation of functional logic programs of [2, 3], using lazy narrowing. However, the results inherited by [2, 3] mainly regard the termination of the PE method, while the (strong) soundness and completeness results must be restated for the lazy strategy. A post-processing renaming scheme (second phase) is necessary which we describe and illustrate on the well-known matching example. This phase is essential also for other non-lazy narrowing strategies, like innermost narrowing, and our method can be easily extended to these strategies. We show that our method preserves the lazy narrowing semantics and that the inclusion of simplification steps in narrowing derivations can improve control during specialization.