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ORCID17th EDCC 2021: Munich, Germany
- 17th European Dependable Computing Conference, EDCC 2021, Munich, Germany, September 13-16, 2021. IEEE 2021, ISBN 978-1-6654-3671-7
- José D'Abruzzo Pereira, João R. Campos
, Marco Vieira:
Machine Learning to Combine Static Analysis Alerts with Software Metrics to Detect Security Vulnerabilities: An Empirical Study. 1-8 - Marta Grobelna, João-Vitor Zacchi, Philipp Schleiß, Simon Burton:
Dynamic Risk Management for Safely Automating Connected Driving Maneuvers. 9-16 - Marcello Cinque, Raffaele Della Corte, Roberto Ruggiero:
Preventing timing failures in mixed-criticality clouds with dynamic real-time containers. 17-24 - Jacopo Parri, Samuele Sampietro, Enrico Vicario:
FaultFlow: a tool supporting an MDE approach for Timed Failure Logic Analysis. 25-32 - Dániel Szekeres, Kristóf Marussy, István Majzik:
Tensor-based reliability analysis of complex static fault trees. 33-40 - Jomar Domingos, Raul Barbosa, Henrique Madeira:
Why is it so hard to predict computer systems failures? 41-44 - Mehdi Maleki, Behrooz Sangchoolie:
SUFI: A Simulation-based Fault Injection Tool for Safety Evaluation of Advanced Driver Assistance Systems Modelled in SUMO. 45-52 - Daniel Loche, Aléxis Génèrès, Michaël Lauer, Jean-Charles Fabre:
Run-time Monitoring and Control for Temporal Fault Prevention in Mixed-criticality Systems. 53-60 - Andreas Schmidt, Jan Reich, Ioannis Sorokos:
Live in ConSerts: Model-Driven Runtime Safety Assurance on Microcontrollers, Edge, and Cloud. 61-66 - David Ferreira, João Paulo, Miguel Matos:
ATOCS: Automatic Configuration of Encryption Schemes for Secure NoSQL Databases. 67-74 - Simona Bernardi, Raúl Javierre, José Merseguer, José Ignacio Requeno:
Detectors of Smart Grid Integrity Attacks: an Experimental Assessment. 75-82 - Ricardo M. Czekster, Charles Morisset:
BDMPathfinder: a tool for exploring attack paths in models defined by Boolean logic Driven Markov Processes. 83-86 - Nadia Patricia Da Silva Medeiros, Naghmeh Ramezani Ivaki, Pedro Costa, Marco Vieira:
An Empirical Study On Software Metrics and Machine Learning to Identify Untrustworthy Code. 87-94 - Michael Kläs, Rasmus Adler, Ioannis Sorokos, Lisa Jöckel, Jan Reich:
Handling Uncertainties of Data-Driven Models in Compliance with Safety Constraints for Autonomous Behaviour. 95-102 - Ahmad Adee, Roman Gansch, Peter Liggesmeyer:
Systematic Modeling Approach for Environmental Perception Limitations in Automated Driving. 103-110 - Oskar Lundström, Michel Raynal, Elad Michael Schiller:
Self-stabilizing Multivalued Consensus in Asynchronous Crash-prone Systems. 111-118 - Laura Lawniczak, Tobias Distler:
Stream-based State-Machine Replication. 119-126 - Michael Conard, Ali Ebnenasir:
A Practical Self-Stabilizing Leader Election for Networks of Resource-Constrained IoT Devices. 127-134
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