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Applied OSS Reliability Assessment Modeling, AI and Tools: Mathematics and AI for OSS Reliability Assessment de Yoshinobu Tamura

Applied OSS Reliability Assessment Modeling, AI and Tools: Mathematics and AI for OSS Reliability Assessment: Springer Series in Reliability Engineering

Autor Yoshinobu Tamura, Shigeru Yamada
en Limba Engleză Hardback – oct 2024
This textbook introduces the theory and application of open source software (OSS) reliability.
The measurement and management of open source software are essential to produce and maintain quality and reliable systems while using open source software. This book describes the latest methods for the reliability assessment of open source software. It presents the state of the art of open source software reliability measurement and assessment based on stochastic modeling and deep learning approaches. It introduces several stochastic reliability analyses of OSS computing with application along with actual OSS project data.
The book contains exercises to aid learning and is useful for graduate students and researchers.
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Specificații

ISBN-13: 9783031648021
ISBN-10: 3031648021
Pagini: 140
Ilustrații: Approx. 140 p. 14 illus.
Dimensiuni: 155 x 235 x 16 mm
Greutate: 0.48 kg
Ediția:2024
Editura: Springer Nature Switzerland
Colecția Springer
Seria Springer Series in Reliability Engineering

Locul publicării:Cham, Switzerland

Cuprins

Open Source Software Reliability.- Stochastic Differential Equation Model for OSS Reliability Analysis.- Dimensional Stochastic Differential Equation Model for OSS Reliability Analysis.- Jump Diffusion Process Model for OSS Reliability Analysis.- Cyclically Two Dimensional Stochastic Differential Equation Modeling.- Cyclically Two Dimensional Jump Diffusion Process Modeling.- Three Dimensional Tool Based on Noisy Model.- Deep Learning Method Based on fault big data Analysis for OSS Reliability Assessment.- Deep Learning Approach for OSS Reliability Assessment Considering Wiener Process.- Deep Learning Approach for OSS Reliability Assessment Considering Jump Diffusion Process.- Performance Illustrations of the Developed Application Tool Based on Deep Learning.- Exercise.

Notă biografică

Yoshinobu Tamura received the Ph.D. degree from Tottori University in 2003. Since 2021, he has been working as a professor at the Graduate School of Sciences and Technology for Innovation, Yamaguchi University, Ube, Japan. Dr. Tamura received the Research Leadership Award in Area of Reliability from the ICRITO in 2010, the Best Paper Award of the IEEE International Conference on Industrial Engineering and Engineering Management in 2012, the Honorary Professor from Amity University of India in 2017, the Best Paper Award of the 24th ISSAT International Conference on Reliability and Quality in Design in 2018, the Outstanding Paper Award of the IEEE International Conference on Industrial Engineering and Engineering Management in 2022, and the Amity Global Academic Excellence Award of the IEEE 4th International Conference on Intelligent, Engineering and  Management in 2023.
Shigeru Yamada is an  emeritus professor at Tottori University, Japan

Textul de pe ultima copertă

This textbook introduces the theory and application of open source software (OSS) reliability.
The measurement and management of open source software are essential to produce and maintain quality and reliable systems while using open source software. This book describes the latest methods for the reliability assessment of open source software. It presents the state of the art of open source software reliability measurement and assessment based on stochastic modeling and deep learning approaches. It introduces several stochastic reliability analyses of OSS computing with application along with actual OSS project data.
The book contains exercises to aid learning and is useful for graduate students and researchers.

Caracteristici

Introduces the theory and application of open course software (OSS) reliability Includes stochastic modeling and deep learning approaches Useful to university students, IT professionals, and professors