This paper shows how the Improvement Theorem---a semantic condition

Functional logic languages combine the operational principles of the most important declarative programming paradigms, namely functional and logic programming. Inductively sequential programs admit the definition of optimal computation strategies and are the basis of several recent (lazy) functional logic languages. In this paper, we define a partial evaluator for inductively sequential functional logic programs. We prove strong correctness of this partial evaluator and show that the nice properties of inductively sequential programs carry over to the specialization process and the specialized programs. In particular, the structure of the programs is preserved by the specialization process. This is in contrast to other partial evaluation methods for functional logic programs which can destroy the original program structure. Finally, we present some experiments which highlight the practical advantages of our approach. 1 Introduction Functional logic languages combine the operational p...

. The aim of this work is to compute descriptions of successful computation paths in logic or functional program executions. Computation paths are represented as terms, built from special constructor symbols, each constructor symbol corresponding to a specific clause or equation in a program. Such terms, called trace-terms, are abstractions of computation trees, which capture information about the control flow of the program. A method of approximating trace-terms is described, based on well-established methods for computing regular approximations of terms. The special function symbols are first introduced into programs as extra arguments in predicates or functions. Then a regular approximation of the program is computed, describing the terms occurring in some set of program executions. The approximation of the extra arguments (the trace-terms) can then be examined to see what computation paths were followed during the computation. This information can then be used to control both off-l...

We present an algorithm for inverse computation in a first-order functional language based on the notion of a perfect process tree. The Universal Resolving Algorithm (URA) introduced in this paper is sound and complete, and computes each solution, if it exists, in finite time. The algorithm has been implemented for TSG, a typed dialect of S-Graph, and shows some remarkable results for the inverse computation of functional programs such as pattern matching and the inverse interpretation of While-programs.

We have recently defined a framework for Narrowing-driven Partial Evaluation (NPE) of functional logic programs. This method is as powerful as partial deduction of logic programs and positive supercompilation of functional programs. Although it is possible to treat complex terms containing primitive functions (e.g. conjunctions or equations) in the NPE framework, its basic control mechanisms do not allow for effective polygenetic specialization of these complex expressions. We introduce a sophisticated unfolding rule endowed with a dynamic narrowing strategy which permits flexible scheduling of the elements (in conjunctions) which are reduced during specialization. We also present a novel abstraction operator which carefully considers primitive functions and is the key to achieving accurate polygenetic specialization. The abstraction operator extends some recent partitioning techniques defined in the framework of conjunctive partial deduction. We provide experimental results obtained from an implementation using the INDY system which demonstrate that the control refinements produce better specializations.

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Functional logic languages 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. Needed narrowing is an optimal narrowing strategy and the basis of several recent functional logic languages. In this paper, we define a partial evaluator for functional logic programs based on needed narrowing. We prove strong correctness of this partial evaluator and show that the nice properties of needed narrowing carry over to the specialization process and the specialized programs. In particular, the structure of the specialized programs provides for the application of optimal evaluation strategies. This is in contrast to other partial evaluation methods for functional logic programs which can change the original program structure in a negative way. Finally, we present some experiments which highlight the practical advantages of our approach.

rogramming (computation of normal forms) as well as logic programming (computation of answers). Essentially, it consists of computing an appropriate substitution such that when applied to the current goal it becomes reducible, and then reducing it [10]. This work has been partially supported by CICYT under grant TIC 95-0433-C03-03 and by HCM project CONSOLE. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or direct commercial advantage and that copies show this notice on the first page or initial screen of a display along with the full citation. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, to republish, to post on servers, to redistribute to lists, or to use any component of this work in other works, requires prior specific permission and/or a fee. Permissions

A supercompiler is a program which can perform a deep transformation of programs using a principle which is similar to partial evaluation, and can be referred to as metacomputation. Supercompilers that have been in existence up to now (see [12], [13]) were not self-applicable: this is a more di cult problem than self-application of a partial evaluator, because of the more intricate logic of supercompilation. In the present paper we describe the rst self-applicable model of a supercompiler and present some tests. Three features distinguish it from the previous models and make self-application possible: (1) The input language is a subset of Refal which we refer to as at Refal. (2) The process of driving is performed as a transformation of pattern-matching graphs. (3) Metasystem jumps are implemented, which allows the supercompiler to avoid interpretation whenever direct computation is possible.

The aim of this work is the development and application of a partial evaluation procedure for rewriting-based functional logic programs. Functional logic programming languages unite the two main declarative programming paradigms. The rewriting-based computational model extends traditional functional programming languages by incorporating logical features, including logical variables and built-in search, into its framework. This work is the first to address the automatic specialisation of these functional logic programs. In particular, a theoretical framework for the partial evaluation of rewriting-based functional logic programs is defined and its correctness is established. Then, an algorithm is formalised which incorporates the theoretical framework for the procedure in a fully automatic technique. Constraint solving is used to represent additional information about the terms encountered during the transformation in order to improve the efficiency and size of the residual programs. ...