Runtime Verification (eBook, PDF)

24th International Conference, RV 2024, Istanbul, Turkey, October 15-17, 2024, Proceedings
Redaktion: Ábrahám, Erika; Abbas, Houssam

• Format: PDF

Produktbeschreibung

This book constitutes the refereed proceedings of the 24th International Conference on Runtime Verification, RV 2024, held in Istanbul, Turkey, during October 15-17, 2024.

The 11 full papers, 5 short papers and 2 tool papers included in this book were carefully reviewed and selected from 31 submissions. They were organized in topical sections as follows: Invited Paper; Cyber-physical Systems; Temporal Logics; Speci cation and Visualization; Deep Neural Networks; and Distributed Systems.

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Produktdetails

• Verlag: Springer International Publishing
• Seitenzahl: 304
• Erscheinungstermin: 11. Oktober 2024
• Englisch
• ISBN-13: 9783031742347
• Artikelnr.: 72242601

Inhaltsangabe

.- Invited Paper.
.- Distributed Runtime Verification with Imperfect Monitors: Challenges and Opportunities.
.- Cyber-physical Systems.
.- A Formal Approach for Safe Reinforcement Learning: A Rate-Adaptive Pacemaker Case Study.
.- Stream-based Monitoring under Measurement Noise.
.- Dynamic, Multi-Objective Specification and Falsification of Autonomous CPS.
.- Oblivious Monitoring for Discrete-Time STL via Fully Homomorphic Encryption.
.- Sampling-based and Gradient-based Efficient Scenario Generation.
.- HyperPart-X: Probabilistic Guarantees for Parameter Mining of Signal Temporal Logic Formulas in Cyber-Physical Systems.
.- Temporal Logics.
.- faRM-LTL: A Domain-Specific Architecture for Flexible and Accelerated Runtime Monitoring of LTL Properties.
.- Efficient Online Monitoring for Dynamic Metric Temporal Logic.
.- TimelyMon: A Streaming Parallel First-Order Monitor.
.- Specification and Visualization.
.- Adding State to Stream Runtime Verification.
.- The Complexity of Data-Free Nfer.
.- RTLolaMo3Vis - A Mobile and Modular Visualization Framework for Online Monitoring.
.- Deep Neural Networks.
.- Case Study: Runtime Safety Verification of Neural Network Controlled System.
.- Gaussian-Based and Outside-the-Box Runtime Monitoring Join Forces.
.- Box-based Monitor Approach for Out-of-Distribution Detection in YOLO: An Exploratory Study.
.- Distributed Systems.
.- Distributed Monitoring of Timed Properties.
.- Towards Efficient Runtime Veri ed Linearizable Algorithms.
.- Approximate Distributed Monitoring under Partial Synchrony: Balancing Speed and Accuracy.