| ISBN13: | 9789819789429 |
| ISBN10: | 9819789427 |
| Binding: | Paperback |
| No. of pages: | 389 pages |
| Size: | 235x155 mm |
| Language: | English |
| Illustrations: | 71 Illustrations, black & white; 149 Illustrations, color |
| 699 |
Programming Languages and Systems
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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. These papers have been categorized under the following topical sections: Type theory and Semantic Frameworks; Probabilistic and Declarative Programming; Quantum Computation; Logical Relations; Verification.
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.