03981nam a22006375i 4500 978-3-031-64803-8 DE-He213 20251030113103.0 cr nn 008mamaa 240925s2024 sz | s |||| 0|eng d 9783031648038 978-3-031-64803-8 10.1007/978-3-031-64803-8 doi QA76.76.O62 U bicssc COM051390 bisacsh ULJ thema Tamura, Yoshinobu. author. aut http://id.loc.gov/vocabulary/relators/aut 84954 Applied OSS Reliability Assessment Modeling, AI and Tools [electronic resource] : Mathematics and AI for OSS Reliability Assessment / by Yoshinobu Tamura, Shigeru Yamada. 1st ed. 2024. Cham : Springer Nature Switzerland : Imprint: Springer, 2024. XI, 188 p. 99 illus., 80 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Springer Series in Reliability Engineering, 2196-999X 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. 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. Open source software. 9313 Artificial intelligence. 58441 Cooperating objects (Computer systems). 64303 Industrial engineering. Production engineering. Data protection. Computers. 65793 Open Source. 66214 Artificial Intelligence. 58441 Cyber-Physical Systems. 65638 Industrial and Production Engineering. Data and Information Security. 66492 Hardware Performance and Reliability. 71397 Yamada, Shigeru. author. aut http://id.loc.gov/vocabulary/relators/aut 84955 SpringerLink (Online service) Springer Nature eBook Printed edition: 9783031648021 Printed edition: 9783031648045 Printed edition: 9783031648052 Springer Series in Reliability Engineering, 2196-999X 71674 https://doi.org/10.1007/978-3-031-64803-8 ZDB-2-ENG ZDB-2-SXE 63682 63682