Description
Book Synopsis.- Safety Arguments/Cases.
.- SmartGSN: An Online Tool to Semi-automatically Manage Assurance Cases.
.- Principled Safety Assurance Arguments.
.- Consensus Building in Level 4 Automated Driving Field Trials through Assurance Cases.
.- Data Sets and Dependability Properties.
.- Creation and use of a representative dataset for Advanced Persistent Threats detection.
.- How Post-Completion Error Leads to Software Faults and Vulnerabilities: Industrial Case Studies.
.- Efficient Injury Risk Assessment for Automated Driving Systems Using Subset Simulation.
.- Testing and Complex Environments.
.- Alignment of SOTIF and Scenario-based Safety Evaluation Framework.
.- Managing capability in software dependability testing through generic test rigs.
.- Improving Out-of-Distribution Detection via Test-Time Augmentation.
.- Methodologies (1) – Safety Design and Risk Assessment.
.- Can C-Based ECC Models Leverage High-Level Synthesis? Evaluating Description Variants for Efficient Circuit.
.- Hot PASTA: Improved Pragmatics for System-Theoretic Process Analysis.
.- ULS: A Unified Likelihood Scale for Cross-Standard Risk Assessment.
.- Methodologies (2) – Machine Learning and Large Language Models.
.- Large Language Models in Code Co-generation for Safe Autonomous Vehicles.
.-Balancing the Risks and Benefits of using Large Language Models to Support Assurance Case Development.
.- Exploring the Potential of LSTM On Emulating Multiple-bit Fault Injection in SRAM-FPGA.
