By Gopalan Nadathur (auth.), Herbert Kuchen, Kazunori Ueda (eds.)

This publication constitutes the refereed complaints of the fifth foreign Symposium on sensible and common sense Programming, FLOPS 2001, held in Tokyo, Japan in March 2001.

The 21 revised complete papers provided including 3 invited papers have been conscientiously reviewed and chosen from forty submissions. The booklet deals topical sections on practical programming, good judgment programming, practical common sense programming, varieties, software research and transformation, and Lambda calculus.

**Read or Download Functional and Logic Programming: 5th International Symposium, FLOPS 2001 Tokyo, Japan, March 7–9, 2001 Proceedings PDF**

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CONTENTS

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Preface

CHAPTER ONE. fundamentals FROM ALGEBRA AND TOPOLOGY

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1. five Semimetric and Semiuniform Spaces

1. 6 Completeness and the Canonical Completion

CHAPTER . different types, DEFINITIONS, AND EXAMPLES

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**Extra info for Functional and Logic Programming: 5th International Symposium, FLOPS 2001 Tokyo, Japan, March 7–9, 2001 Proceedings**

**Sample text**

The description of PCC so far has been in abstract terms without referring to a particular form of safety explanations. There are a number of possible forms of explanations each with its own advantages and disadvantages. In any implementation the safety explanations must be precise and comprehensive, just like formal proofs. In fact, in the first realization of a PCC architecture [Nec98] the explanations were precisely formal proofs represented as terms in a variant of the dependently-typed λ-calculus called the Edinburgh Logical Framework (LF) [HHP93].

It is obvious that this safety policy is tailored to our example and thus is not very general. To alleviate this problem we allow the host to define a language of types along with their meaning and the agent to customize the safety policy by declaring the type of the arguments that it expects and the type of the return value. This constitutes the interface of the agent and in our system is expressed as a pair of a function precondition and postcondition formulas constructed by the code producer using a number of type constructors defined by the host’s safety policy.

One interesting observation is that while LFi checking is faster than oracle checking, it also uses a lot more memory. While oracles can be consumed a few bits at a time, the LFi syntactic representation of a proof must be entirely brought in memory for checking. While we have not measured precisely the memory usage we encountered examples whose oracles can be checked using less than 1Mbyte of memory while the checking of the corresponding LFi terms could not be performed even with 1Gbyte of virtual memory.

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