System Dependability and Analytics

Edited by Long Wang (), Karthik Pattabiraman (), Catello Di Martino (), Arjun Athreya () and Saurabh Bagchi ()

in Springer Series in Reliability Engineering from Springer, currently edited by Hoang Pham

Date: 2023
ISBN: 978-3-031-02063-6
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Chapters in this book:

Introduction: Software Dependability

Long Wang

Intelligent Software Engineering for Reliable Cloud Operations

Michael R. Lyu and Yuxin Su

Data Analytics: Predicting Software Bugs in Industrial Products

Robert Hanmer and Veena Mendiratta

From Dependability to Security—A Path in the Trustworthy Computing Research

Shuo Chen

Assessment of Security Defense of Native Programs Against Software Faults

Keun Soo Yim

Multi-layered Monitoring for Virtual Machines

Cuong Pham

Security for Software on Tiny Devices

Saurabh Bagchi

Introduction: Large-Scale Systems and Data Analytics

Saurabh Bagchi

On the Reliability of Computing-in-Memory Accelerators for Deep Neural Networks

Zheyu Yan, Xiaobo Sharon Hu and Yiyu Shi

Providing Compliance in Critical Computing Systems

Long Wang

Application-Aware Reliability and Security: The Trusted Illiac Experience

Karthik Pattabiraman

Mining Dependability Properties from System Logs: What We Learned in the Last 40 Years

Marcello Cinque, Domenico Cotroneo and Antonio Pecchia

Critical Infrastructure Protection: Where Convergence of Logical and Physical Security Technologies is a Must

Luigi Coppolino, Salvatore D’Antonio, Giovanni Mazzeo and Luigi Romano

Introduction: Cyber Physical Systems and Healthcare Analytics

Arjun P. Athreya

On Improving the Reliability of Power Grids for Multiple Power Line Outages and Anomaly Detection

Jie Wu, Jinjun Xiong and Yiyu Shi

Domain-Specific Security Approaches for Cyber-Physical Systems

Hui Lin

Uniting Computational Science with Biomedicine: The NSF Center for Computational Biotechnology and Genomic Medicine (CCBGM)

Liewei Wang and Richard M. Weinshilboum

Data-Driven Approaches to Selecting Samples for Training Neural Networks

Murthy V. Devarakonda

Classifying COVID-19 Variants Based on Genetic Sequences Using Deep Learning Models

Sayantani Basu and Roy H. Campbell

Twenty-First Century Cybernetics and Disorders of Brain and Mind

Gregory Worrell

Introduction: Dependability Assessment

Karthik Pattabiraman

Effect of Epistemic Uncertainty in Markovian Reliability Models

Hiroyuki Okamura, Junjun Zheng, Tadashi Dohi and Kishor S. Trivedi

System Dependability Assessment—Interplay Between Research and Practice

Mohamed Kaâniche and Karama Kanoun

Assessing Dependability of Autonomous Vehicles

Saurabh Jha

Foreword: Computing and Genomics at Illinois

Gene E. Robinson

An Academic Life Begins and Continues at University of Illinois at Urbana-Champaign

Janak H. Patel

Learning from Prof. Iyer

Wen-Mei Hwu

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:ssreng:978-3-031-02063-6

Ordering information: This item can be ordered from
http://www.springer.com/9783031020636

DOI: 10.1007/978-3-031-02063-6

Access Statistics for this book

More books in Springer Series in Reliability Engineering from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().