Del 15194 i serien Lecture Notes in Computer Science

Programming Languages and Systems

22nd Asian Symposium, APLAS 2024, Kyoto, Japan, October 22-24, 2024, Proceedings

Häftad, Engelska, 2024

799 kr

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This book constitutes the proceedings of the 22nd Asian Symposium on Programming Languages and Systems, APLAS 2024, held in Kyoto, Japan, during October 22-24, 2024. The 18 full papers presented here were carefully reviewed and selected from 37 submissions.

Produktinformation

Utgivningsdatum2024-10-29
Mått155 x 235 x 22 mm
Vikt610 g
FormatHäftad
SpråkEngelska
SerieLecture Notes in Computer Science
Antal sidor389
FörlagSpringer Verlag, Singapore
ISBN9789819789429

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Systemvetenskap och AI inom Data och IT
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Type theory and Semantic Frameworks.- Comparing semantic frameworks of dependently sorted algebraic theories.- Random access lists from EE to FP.- Generic Reasoning of the Locally Nameless Representation.- Building A Correct By Construction Type Checker for a Dependently Typed Core.- Extending the Quantitative Pattern Matching Paradigm.- Probabilistic and Declarative Programming.- Hybrid Verification of Declarative Programs with Arithmetic Non Fail Conditions.- Explaining Explanations in Probabilistic Logic Programming.- Quantum Computation.- Quantum Programming Without the Quantum Physics.- Quantum Bisimilarity is a Congruence under Physically Admissible Schedulers.- Non deterministic, probabilistic, and quantum effects through the lens of event structures.- Type Based Verification of Connectivity Constraints in Lattice Surgery.- Logical Relations.- On Computational Indistinguishability and Logical Relations.- Relative Completeness of Incorrectness Separation Logic.- OBRA Oracle based, relational, algorithmic type verification.- Verification.- A Formal Verification Framework for Tezos Smart Contracts Based on Symbolic Execution.- Mode based Reduction from Validity Checking of Fixpoint Logic Formulas to Test Friendly Reachability Problem.- Efficiently Adapting Stateless Model Checking for C11/C++11 to Mixed Size Accesses.- Effective Search Space Pruning for Testing Deep Neural Networks.