Safety Assurance under Uncertainties : From Software to Cyber-Physical/Machine Learning Systems - Ichiro Hasuo

Safety Assurance under Uncertainties

From Software to Cyber-Physical/Machine Learning Systems

By: Ichiro Hasuo (Editor), Fuyuki Ishikawa (Editor)

eText | 13 May 2025 | Edition Number 1

At a Glance

eText


$79.19

or 4 interest-free payments of $19.80 with

 or 

Available: 13th May 2025

Preorder. Online access available after release.

Why choose an eTextbook?

Instant Access *

Purchase and read your book immediately

Read Aloud

Listen and follow along as Bookshelf reads to you

Study Tools

Built-in study tools like highlights and more

* eTextbooks are not downloadable to your eReader or an app and can be accessed via web browsers only. You must be connected to the internet and have no technical issues with your device or browser that could prevent the eTextbook from operating.

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.

The book is the first to provide a comprehensive overview of such united and interdisciplinary efforts. Driven by automated driving systems as a leading example, the book describes diverse techniques to specify, model, test, analyze, and verify modern software systems. Coming out of a collaboration between industry and basic academic research, the book covers both practical analysis techniques (readily applicable to existing systems) and more long-range design techniques (that call for new designs but bring a greater degree of assurance).

The book provides high-level intuitions and use-cases of each technique, rather than technical details, with plenty of pointers for interested readers.

on
Desktop
Tablet
Mobile

More in Computer Science

Amazon.com : Get Big Fast - Robert Spector

eBOOK