Guide to the Software Engineering Body of Knowledge (Swebok(r))

Guide to the Software Engineering Body of Knowledge (Swebok(r))

Author: IEEE Computer Society

Publisher:

Published: 2014

Total Pages: 348

ISBN-13: 9780769551661

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In the Guide to the Software Engineering Body of Knowledge (SWEBOK(R) Guide), the IEEE Computer Society establishes a baseline for the body of knowledge for the field of software engineering, and the work supports the Society's responsibility to promote the advancement of both theory and practice in this field. It should be noted that the Guide does not purport to define the body of knowledge but rather to serve as a compendium and guide to the knowledge that has been developing and evolving over the past four decades. Now in Version 3.0, the Guide's 15 knowledge areas summarize generally accepted topics and list references for detailed information. The editors for Version 3.0 of the SWEBOK(R) Guide are Pierre Bourque (Ecole de technologie superieure (ETS), Universite du Quebec) and Richard E. (Dick) Fairley (Software and Systems Engineering Associates (S2EA)).


Experience and Knowledge Management in Software Engineering

Experience and Knowledge Management in Software Engineering

Author: Kurt Schneider

Publisher: Springer Science & Business Media

Published: 2009-06-05

Total Pages: 247

ISBN-13: 3540958800

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Nowadays, there is software everywhere in our life. It controls cars, airplanes, factories, medical implants. Without software, banking, logistics and transportation, media, and even scientific research would not function in the accustomed way. Building and maintaining software is a knowledge-intensive endeavour and requires that specific experiences are handled successfully. However, neither knowledge nor experience can be collected, stored, and shipped like physical goods, instead these delicate resources require dedicated techniques. Knowledge and experience are often called company assets, yet this is only part of the truth: it is only software engineers and other creative employees who will effectively exploit an organisation's knowledge and experience. Kurt Schneider’s textbook is written for those who want to make better use of their own knowledge and experience – either personally or within their group or company. Everyone related to software development will benefit from his detailed explanations and case studies: project managers, software engineers, quality assurance responsibles, and knowledge managers. His presentation is based on years of both practical experience, with companies such as Boeing, Daimler, and Nokia, and research in renowned environments, such as the Fraunhofer Institute. Each chapter is self-contained, it clearly states its learning objectives, gives in-depth presentations, shows the techniques’ practical relevance in application scenarios, lists detailed references for further reading, and is finally completed by exercises that review the material presented and also challenge further, critical examinations. The overall result is a textbook that is equally suitable as a personal resource for self-directed learning and as the basis for a one-semester course on software engineering and knowledge management.


Advances In Software Engineering And Knowledge Engineering

Advances In Software Engineering And Knowledge Engineering

Author: Vincenzo Ambriola

Publisher: World Scientific

Published: 1993-12-27

Total Pages: 203

ISBN-13: 981450257X

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The papers collected in the book were invited by the editors as tutorial courses or keynote speeches for the Fourth International Conference on Software Engineering and Knowledge Engineering. It was the editors' intention that this book should offer a wide coverage of the main topics involved with the specifications, prototyping, development and maintenance of software systems and knowledge-based systems. The main issues in the area of software engineering and knowledge engineering are addressed and for each analyzed topic the corresponding of state research is reported.


Knowledge-based Software Engineering

Knowledge-based Software Engineering

Author: Vadim Stefanuk

Publisher: IOS Press

Published: 2004

Total Pages: 346

ISBN-13: 9781586034436

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JCKBSE aims to provide a forum for researchers and practitioners to discuss the latest developments in the areas of knowledge engineering and software engineering. Particular emphasis is placed upon applying knowledge-based methods to software engineering problems. This volume is a collection of contributions of authors from 8 different countries. The book covers a wide range of topics related to knowledge-based or automated software engineering. architecture of knowledge; software and information systems; requirement engineering; domain analysis and modelling; formal and semiformal specifications; knowledge engineering for domain modelling; data mining and knowledge discovery; automating software design and synthesis; object-oriented and other programming paradigms; knowledge-based methods and tools for software engineering, including testing, verification and validation; process management, maintenance and evolution, applied semiotics for knowledge-based software engineering; knowledge systems methodology; development tools and environments; practical applications and experience of software and knowledge engineering; information technology in control, design, production, logistics and management; enterprise modelling and workflow.


Current Trends on Knowledge-Based Systems

Current Trends on Knowledge-Based Systems

Author: Giner Alor-Hernández

Publisher: Springer

Published: 2017-03-13

Total Pages: 302

ISBN-13: 3319519050

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This book presents innovative and high-quality research on the implementation of conceptual frameworks, strategies, techniques, methodologies, informatics platforms and models for developing advanced knowledge-based systems and their application in different fields, including Agriculture, Education, Automotive, Electrical Industry, Business Services, Food Manufacturing, Energy Services, Medicine and others. Knowledge-based technologies employ artificial intelligence methods to heuristically address problems that cannot be solved by means of formal techniques. These technologies draw on standard and novel approaches from various disciplines within Computer Science, including Knowledge Engineering, Natural Language Processing, Decision Support Systems, Artificial Intelligence, Databases, Software Engineering, etc. As a combination of different fields of Artificial Intelligence, the area of Knowledge-Based Systems applies knowledge representation, case-based reasoning, neural networks, Semantic Web and TICs used in different domains. The book offers a valuable resource for PhD students, Master’s and undergraduate students of Information Technology (IT)-related degrees such as Computer Science, Information Systems and Electronic Engineering.


Knowledge Engineering

Knowledge Engineering

Author: Gheorghe Tecuci

Publisher: Cambridge University Press

Published: 2016-09-08

Total Pages: 481

ISBN-13: 1107122562

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Using robust software, this book focuses on learning assistants for evidence-based reasoning that learn complex problem solving from humans.


Knowledge-based Software Engineering

Knowledge-based Software Engineering

Author: Pavol Návrat

Publisher: IOS Press

Published: 1998

Total Pages: 340

ISBN-13: 9789051994179

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This text collects contributions from different countries to a wide range of topics in software engineering. Special emphasis is given to application of knowledge-base methods to software engineering problems. The papers tackle such areas as architecture of software and design patterns.


Machine Learning Applications In Software Engineering

Machine Learning Applications In Software Engineering

Author: Du Zhang

Publisher: World Scientific

Published: 2005-02-21

Total Pages: 367

ISBN-13: 9814481424

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Machine learning deals with the issue of how to build computer programs that improve their performance at some tasks through experience. Machine learning algorithms have proven to be of great practical value in a variety of application domains. Not surprisingly, the field of software engineering turns out to be a fertile ground where many software development and maintenance tasks could be formulated as learning problems and approached in terms of learning algorithms. This book deals with the subject of machine learning applications in software engineering. It provides an overview of machine learning, summarizes the state-of-the-practice in this niche area, gives a classification of the existing work, and offers some application guidelines. Also included in the book is a collection of previously published papers in this research area.