Runtime Verification

Assumption Generation for Learning-Enabled Autonomous Systems.- Customizable Reference Runtime Monitoring of Neural Networks using Resolution Boxes.- Scalable Stochastic Parametric Verification with Stochastic Variational Smoothed Model Checking.- Monitoring Blackbox Implementations of Multiparty Session Protocols.- Specification Parameters for Multi-Class Classification.- General Anticipatory Monitoring for Temporal Logics on Finite Traces.- Metric First-order Temporal Logic with Complex Data Types.- Runtime Verification Prediction for Traces with Data.- Monitoring Hyperproperties With Prefix Transducers.- Compositional Simulation-Based Analysis of AI-Based Autonomous Systems for Markovian Specifications.- Decentralized Predicate Detection over Partially Synchronous Continuous-Time Signals.- Flexible Runtime Security Enforcement with Tagged C.- Pattern Matching for Perception Streams.- Learning Monitor Ensembles for Operational Design Domains.- Monitoring Algorithmic Fairness underPartial Observations.- AMT: a Runtime Verification Tool of Video Streams.- Bridging the Gap: A Focused DSL for RV-Oriented Instrumentation with BISM.- CCMOP: A Runtime Verification Tool for C/C++ Programs.- A Stream Runtime Verification Tool with Nested and Retroactive Parametrizations.- eMOP: A Maven Plugin for Evolution-Aware Runtime Verification.- Runtime Monitoring of Accidents in Driving Recordings with Multi-Type Logic in Empirical Models.- Safety Monitoring for Pedestrian Detection in Adverse Conditions.- Instrumentation for RV: From Basic Monitoring to Advanced Use Cases.- Runtime Monitoring DNN-based Perception.- Monitorability for Runtime Verification.- Learning-Based Approaches to Predictive Monitoring with Conformal Statistical Guarantees.