On the Correctness of Pull-Tabbing

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

Programming with narrowing: A tutorial

AbstractNarrowing is a computation implemented by some declarative programming languages. Research in the last decade has produced significant results on the theory and foundation of narrowing, but little has been published on the use of narrowing in programming. This paper introduces narrowing from a programmer’s viewpoint; shows, by means of examples, when, why and how to use narrowing in a program; and discusses the impact of narrowing on software development activities such as design and maintenance. The examples are coded in the programming language Curry, which provides narrowing as a first class feature

A Virtual Machine for Functional Logic Computations

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.

Architecture of a virtual machine for functional logic computations

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, represented as definitional trees, to sequences of machine instructions. The machine has been implemented in Java and in Standard ML.