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Perspectives on Data Science for Software Engineering, Tim Menzies


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Цена: 8588.00р.
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При оформлении заказа до: 2025-07-28
Ориентировочная дата поставки: Август-начало Сентября
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Автор: Tim Menzies
Название:  Perspectives on Data Science for Software Engineering
ISBN: 9780128042069
Издательство: Elsevier Science
Классификация:

ISBN-10: 0128042060
Обложка/Формат: Paperback
Страницы: 300
Вес: 0.84 кг.
Дата издания: 01.02.2016
Язык: English
Размер: 194 x 241 x 23
Ссылка на Издательство: Link
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Поставляется из: Европейский союз
Описание:

Perspectives on Data Science for Software Engineering presents the best practices of seasoned data miners in software engineering. The idea for this book was created during the 2014 conference at Dagstuhl, an invitation-only gathering of leading computer scientists who meet to identify and discuss cutting-edge informatics topics. At the 2014 conference, the concept of how to transfer the knowledge of experts from seasoned software engineers and data scientists to newcomers in the field highlighted many discussions.

While there are many books covering data mining and software engineering basics, they present only the fundamentals and lack the perspective that comes from real-world experience. This book offers unique insights into the wisdom of the community s leaders gathered to share hard-won lessons from the trenches. Ideas are presented in digestible chapters designed to be applicable across many domains.

Topics included cover data collection, data sharing, data mining, and how to utilize these techniques in successful software projects. Newcomers to software engineering data science will learn the tips and tricks of the trade, while more experienced data scientists will benefit from war stories that show what traps to avoid.
Presents the wisdom of community experts, derived from a summit on software analyticsProvides contributed chapters that share discrete ideas and technique from the trenchesCovers top areas of concern, including mining security and social data, data visualization, and cloud-based dataPresented in digestible chapters designed to be applicable across many domains



Software engineering project management

Автор: Thayer
Название: Software engineering project management
ISBN: 0818680008 ISBN-13(EAN): 9780818680007
Издательство: Wiley
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Цена: 16782.00 р.
Наличие на складе: Поставка под заказ.

Описание: Newly revised for 2001, this second edition of Richard Thayer's popular, bestselling book presents a top-down, practical view of managing a successful software engineering project. The book builds a framework for project management activities based on the planning, organizing, staffing, directing, and controlling model. Thayer provides information designed to help you understand and successfully perform the unique role of a project manager.

This book is a must for all project managers in the software field. The text focuses on the five functions of general management by first describing each function and then detailing the project management activities that support each function. This second edition shows you how to manage a software development project, discusses current software engineering management methodologies and techniques, and presents general descriptions and project management problems. The book serves as a guide for your future project management activities. The text also offers students sufficient background and instructional material to serve as a main or supplementary text for a course in software engineering project management.

Note: The 2001 revision includes a new Chapter 4 Introduction and a new paper that replaces an older paper.

Site Reliability Engineering: How Google Runs Production Systems

Автор: Beyer Betsy, Jones Chris, Petoff Jennifer
Название: Site Reliability Engineering: How Google Runs Production Systems
ISBN: 149192912X ISBN-13(EAN): 9781491929124
Издательство: Wiley
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Цена: 7602.00 р.
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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.

Developing Safety-Critical Software

Автор: Rierson
Название: Developing Safety-Critical Software
ISBN: 143981368X ISBN-13(EAN): 9781439813683
Издательство: Taylor&Francis
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Цена: 13014.00 р.
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Описание: The amount of software used in safety-critical systems is increasing at a rapid rate. At the same time, software technology is changing, projects are pressed to develop software faster and more cheaply, and the software is being used in more critical ways. Developing Safety-Critical Software: A Practical Guide for Aviation Software and DO-178C Compliance equips you with the information you need to effectively and efficiently develop safety-critical, life-critical, and mission-critical software for aviation. The principles also apply to software for automotive, medical, nuclear, and other safety-critical domains. An international authority on safety-critical software, the author helped write DO-178C and the U.S. Federal Aviation Administration’s policy and guidance on safety-critical software. In this book, she draws on more than 20 years of experience as a certification authority, an avionics manufacturer, an aircraft integrator, and a software developer to present best practices, real-world examples, and concrete recommendations. The book includes: An overview of how software fits into the systems and safety processes Detailed examination of DO-178C and how to effectively apply the guidance Insight into the DO-178C-related documents on tool qualification (DO-330), model-based development (DO-331), object-oriented technology (DO-332), and formal methods (DO-333) Practical tips for the successful development of safety-critical software and certification Insightful coverage of some of the more challenging topics in safety-critical software development and verification, including real-time operating systems, partitioning, configuration data, software reuse, previously developed software, reverse engineering, and outsourcing and offshoring An invaluable reference for systems and software managers, developers, and quality assurance personnel, this book provides a wealth of information to help you develop, manage, and approve safety-critical software more confidently.

Large Scale and Big Data

Название: Large Scale and Big Data
ISBN: 1138033944 ISBN-13(EAN): 9781138033948
Издательство: Taylor&Francis
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Цена: 8420.00 р.
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Описание:

Large Scale and Big Data: Processing and Management provides readers with a central source of reference on the data management techniques currently available for large-scale data processing. Presenting chapters written by leading researchers, academics, and practitioners, it addresses the fundamental challenges associated with Big Data processing tools and techniques across a range of computing environments.

The book begins by discussing the basic concepts and tools of large-scale Big Data processing and cloud computing. It also provides an overview of different programming models and cloud-based deployment models. The book's second section examines the usage of advanced Big Data processing techniques in different domains, including semantic web, graph processing, and stream processing. The third section discusses advanced topics of Big Data processing such as consistency management, privacy, and security.

Supplying a comprehensive summary from both the research and applied perspectives, the book covers recent research discoveries and applications, making it an ideal reference for a wide range of audiences, including researchers and academics working on databases, data mining, and web scale data processing.

After reading this book, you will gain a fundamental understanding of how to use Big Data-processing tools and techniques effectively across application domains. Coverage includes cloud data management architectures, big data analytics visualization, data management, analytics for vast amounts of unstructured data, clustering, classification, link analysis of big data, scalable data mining, and machine learning techniques.


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