Programming Languages and Systems 22nd Asian Symposium, APLAS 2024, Kyoto, Japan, October 22-24, 2024, Proceedings /
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 t...
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| 団体著者: | |
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| その他の著者: | |
| フォーマット: | 電子媒体 eBook |
| 言語: | 英語 |
| 出版事項: |
Singapore :
Springer Nature Singapore : Imprint: Springer,
2025.
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| 版: | 1st ed. 2025. |
| シリーズ: | Lecture Notes in Computer Science,
15194 |
| 主題: | |
| オンライン・アクセス: | https://doi.org/10.1007/978-981-97-8943-6 |
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目次:
- 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.