We propose a transformation system for Constraint Logic Programming (CLP) programs and modules. The framework is inspired by the one of Tamaki and Sato for pure logic programs [37]. However, the use of CLP allows us to introduce some new operations such as splitting and constraint replacement. We provide two sets of applicability conditions. The first one guarantees that the original and the transformed programs have the same computational behaviour, in terms of answer constraints. The second set contains more restrictive conditions that ensure compositionality: we prove that under these conditions the original and the transformed modules have the same answer constraints also when they are composed with other modules. This result is proved by first introducing a new formulation, in terms of trees, of a resultants semantics for CLP. As corollaries we obtain the correctness of both the modular and the non-modular system w.r.t. the least model semantics. AMS Subject Classification (1991)...

In this paper we describe work in progress concerning the (semi-)automatic support for developing agents. We focus on the scenario in which agents have to be designed to follow an electronic institution. An initial design pattern is automatically extracted from a given electronic institution and oered to programmers willing to develop agents for the speci c purpose of joining and performing in the electronic institution. We resort to logic programming as our underlying computational framework, explaining and justifying this decision.

In this report, the syntactic manipulation of temporal logic programs is considered. Transformation rules are provided for a temporal programming language that forms part of the METATEM framework for executable temporal logics [2]. Soundness of the various transformations is shown and several applications are given, such as the production of a normal form for programs, which is the basis of both compilation and resolution techniques. The use of transformation techniques in METATEM program synthesis is also considered. Here, a high-level specification, represented as a non-deterministic METATEM program is translated into an `implementation', which is again represented as a METATEM program. The synthesised program is deterministic in that, for any action by the environment, the component has at least one possible (deterministic) response. * This work was supported both by ESPRIT under Basic Research Action 3096 (SPEC), and by SERC under Research Grant GR/F 30123. Contents 1 ...

The transformation of constructive program synthesis proofs is discussed and compared with the more traditional approaches to program transformation. An example system for adapting programs to special situations by transforming constructive synthesis proofs has been reconstructed and is compared with the original implementation [Goad 80]. A brief account of more general proof transformation applications is also presented. The overall moral is that constructiveexistence proofs contain more information over and above that required for simple execution and that this can be exploited by a proof transformation system.

The research described in this paper involved developing transformation techniques which increase the efficiency of the noriginal program, the source, by transforming its synthesis proof into one, the target, which yields a computationally more efficient algorithm. We describe a working proof transformation system which, by exploiting the duality between mathematical induction and recursion, employs the novel strategy of optimizing recursive programs by transforming inductive proofs. We compare and contrast this approach with the more traditional approaches to program transformation, and highlight the benefits of proof transformation with regards to search, correctness, automatability and generality.

This paper contains a discussion, and reconstruction, of Goad's proof transformation system. Information contained in constructive existence proofs, which goes beyond that needed for simple execution, is exploited in the adaption of algorithms to special situations. Goad's system is reconstructed, and extended, in the Oyster proof refinement environment and subjected to test on a number of examples. Differences in methodology between Goad's system and the reconstruction are discussed. In particular, a more active role is given to the actual proof, as opposed to the extracted algorithm, in the transformation process.

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