Safety Assurance under Uncertainties: From Software to Cyber-Physical/Machine Learning Systems
English | 2025 | ISBN: 0367554011 | 366 Pages | PDF (True) | 41 MB
English | 2025 | ISBN: 0367554011 | 366 Pages | PDF (True) | 41 MB
Safety assurance of software systems has never been as imminent a problem as it is today. Practitioners and researchers who work on the problem face a challenge unique to modern software systems: uncertainties. For one, the cyber-physical nature of modern software systems as exemplified by automated driving systems mandates environmental uncertainties to be addressed and the resulting hazards to be mitigated. Besides, the abundance of statistical machine-learning components massive numerical computing units for statistical reasoning such as deep neural networks make systems hard to explain, understand, analyze or verify.