Автор: Beyer Betsy, Jones Chris, Petoff Jennifer Название: Site Reliability Engineering: How Google Runs Production Systems ISBN: 149192912X ISBN-13(EAN): 9781491929124 Издательство: Wiley Рейтинг: Цена: 7602.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: In this collection of essays and articles, key members of Google`s Site Reliability Team explain how and why their commitment to the entire lifecycle has enabled the company to successfully build, deploy, monitor, and maintain some of the largest software systems in the world.
Автор: Pham Hoang Название: System Software Reliability ISBN: 1852339500 ISBN-13(EAN): 9781852339500 Издательство: Springer Рейтинг: Цена: 14365.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Computers are used in areas as diverse as air traffic control, real-time military, industrial process control, and many others. Offering an introduction to software reliability engineering, this book presents a survey of the techniques, methodologies and tools used to assess the reliability of software and combined software-hardware systems.
Автор: P.K. Kapur; Hoang Pham; A. Gupta; P.C. Jha Название: Software Reliability Assessment with OR Applications ISBN: 1447126521 ISBN-13(EAN): 9781447126522 Издательство: Springer Рейтинг: Цена: 27950.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Software Reliability Assessment with OR Applications provides a comprehensive guide to software reliability measurement, prediction, and control. Readers will find solutions to decision-making problems that software developers and engineers often face.
Автор: Nowozin Sebastian, Gehler Peter V., Jancsary Jerem Название: Advanced Structured Prediction ISBN: 0262028379 ISBN-13(EAN): 9780262028370 Издательство: MIT Press Рейтинг: Цена: 11004.00 р. Наличие на складе: Нет в наличии.
Описание:
An overview of recent work in the field of structured prediction, the building of predictive machine learning models for interrelated and dependent outputs.
The goal of structured prediction is to build machine learning models that predict relational information that itself has structure, such as being composed of multiple interrelated parts. These models, which reflect prior knowledge, task-specific relations, and constraints, are used in fields including computer vision, speech recognition, natural language processing, and computational biology. They can carry out such tasks as predicting a natural language sentence, or segmenting an image into meaningful components.
These models are expressive and powerful, but exact computation is often intractable. A broad research effort in recent years has aimed at designing structured prediction models and approximate inference and learning procedures that are computationally efficient. This volume offers an overview of this recent research in order to make the work accessible to a broader research community. The chapters, by leading researchers in the field, cover a range of topics, including research trends, the linear programming relaxation approach, innovations in probabilistic modeling, recent theoretical progress, and resource-aware learning.
Sebastian Nowozin is a Researcher in the Machine Learning and Perception group (MLP) at Microsoft Research, Cambridge, England. Peter V. Gehler is a Senior Researcher in the Perceiving Systems group at the Max Planck Institute for Intelligent Systems, Tubingen, Germany. Jeremy Jancsary is a Senior Research Scientist at Nuance Communications, Vienna. Christoph H. Lampert is Assistant Professor at the Institute of Science and Technology Austria, where he heads a group for Computer Vision and Machine Learning.
Contributors Jonas Behr, Yutian Chen, Fernando De La Torre, Justin Domke, Peter V. Gehler, Andrew E. Gelfand, Sebastien Giguere, Amir Globerson, Fred A. Hamprecht, Minh Hoai, Tommi Jaakkola, Jeremy Jancsary, Joseph Keshet, Marius Kloft, Vladimir Kolmogorov, Christoph H. Lampert, Francois Laviolette, Xinghua Lou, Mario Marchand, Andre F. T. Martins, Ofer Meshi, Sebastian Nowozin, George Papandreou, Daniel Průsa, Gunnar Ratsch, Amelie Rolland, Bogdan Savchynskyy, Stefan Schmidt, Thomas Schoenemann, Gabriele Schweikert, Ben Taskar, Sinisa Todorovic, Max Welling, David Weiss, Thomas Werner, Alan Yuille, Stanislav Zivny
Описание: Now in its third edition, Foundations of Software Testing: ISTQB Certification is the essential guide to software testing and to the ISTQB Foundation qualification. Completely updated to comprehensively reflect the most recent changes to the ISTQB Foundation Syllabus, the book adopts a practical, hands-on approach, covering the fundamental topics that every system and software tester should know. The authors are themselves developers of the ISTQB syllabus and are highly respected international authorities, teachers and authors within the field of software testing.
Автор: Jacobson Название: The Road to the Unified Software Development Process ISBN: 0521787742 ISBN-13(EAN): 9780521787741 Издательство: Cambridge Academ Рейтинг: Цена: 9979.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides an excellent overview of Ivar Jacobson`s work on the Unified Software Development Process.
Описание: System science and engineering is a field that covers a wide spectrum of modern technology. A system can be seen as a collection of entities and their interrelationships, which forms a whole greater than the sum of the entities and interacts with people, organizations, cultures and activities and the interrelationships among them. Systems composed of autonomous subsystems are not new, but the increased complexity of modern technology demands ever more reliable, intelligent, robust and adaptable systems to meet evolving needs. This book presents papers delivered at the International Conference on System Science and Engineering ICSSE2015,
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