Functional and logic programming : 16th International Symposium, FLOPS 2022, Kyoto, Japan, May 10-12, 2022, proceedings

著者

    • Hanus, Michael
    • Igarashi, Atsushi (Computer engineer)

書誌事項

Functional and logic programming : 16th International Symposium, FLOPS 2022, Kyoto, Japan, May 10-12, 2022, proceedings

Michael Hanus, Atsushi Igarashi (eds.)

(Lecture notes in computer science, 13215)

Springer, c2022

  • : pbk

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注記

Includes bibliographical references and index

内容説明・目次

内容説明

This book constitutes the proceedings of the 16th International Symposium on Functional and Logic Programming, FLOPS 2022, held in Kyoto, Japan, in May 2022. The 12 papers presented in this volume were carefully reviewed and selected from 30 submissions. Additionally, the volume includes two system descriptions and a declarative pearl paper. The papers cover all aspects of the design, semantics, theory, applications, implementations, and teaching of declarative programming focusing on topics such as functional programming, logic programming, declarative programming, constraint programming, formal method, model checking, program transformation, program refinement, and type theory.

目次

Enhancing expressivity of checked corecursive streams.- Improving Type Error Reporting for Type Classes.- Asynchronous Unfold/Fold Transformation for Fixpoint Logic.- Program Logic for Higher-Order Probabilistic Programs in Isabelle/HOL.- Generating C (System Description).- Translation Certification for Smart Contracts.- Zipping Strategies and Attribute Grammars.- Unified Program Generation and Verification: A Case Study on Number-Theoretic Transform.- Scheduling Complexity of Interleaving Search.- Automated Generation of Control Concepts Annotation Rules Using Inductive Logic Programming (System Description).- A Functional Account of Probabilistic Programming with Possible Worlds (Declarative Pearl).- Explanations as Programs in Probabilistic Logic Programming.- FOLD-R++: A Scalable Toolset for Automated Inductive Learning of Default Theories from Mixed Data.- A Lazy Desugaring System for Evaluating Programs with Sugars.- On Transforming Cut- and Quantifier-Free Cyclic Proofs into Rewriting-Induction Proofs.

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