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Functional and Logic Programming: 16th International Symposium, FLOPS 2022, Kyoto, Japan, May 10–12, 2022, Proceedings: Lecture Notes in Computer Science, cartea 13215

Editat de Michael Hanus, Atsushi Igarashi
en Limba Engleză Paperback – 31 mar 2022
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.


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Specificații

ISBN-13: 9783030994600
ISBN-10: 3030994600
Pagini: 283
Ilustrații: XVI, 283 p. 68 illus., 14 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.42 kg
Ediția:1st ed. 2022
Editura: Springer International Publishing
Colecția Springer
Seria Lecture Notes in Computer Science

Locul publicării:Cham, Switzerland

Cuprins

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.