Software Engineering And Knowledge Engineering

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)).

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.

The disciplines of knowledge engineering and knowledge management are closely tied. Knowledge engineering deals with the development of information systems in which knowledge and reasoning play pivotal roles. Knowledge management, a newly developed field at the intersection of computer science and management, deals with knowledge as a key resource in modern organizations. Managing knowledge within an organization is inconceivable without the use of advanced information systems; the design and implementation of such systems pose great organization as well as technical challenges.

This volume focuses on current and future trends in the interplay between software engineering and artificial intelligence.This interplay is now critical to the success of both disciplines, and it also affects a wide range of subject areas. The articles in this volume survey the significant work that has been accomplished, describe the state of the art, analyze the current trends, and predict which future directions have the most potential for success. Areas covered include requirements engineering, real-time systems, reuse technology, development environments and meta-environments, process representations, safety-critical systems, and metrics and measures for processes and products.

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.

Empirical verification of knowledge is one of the foundations for developing any discipline. As far as software construction is concerned, the empirically verified knowledge is not only sparse but also not very widely disseminated among developers and researchers. This book aims to spread the idea of the importance of empirical knowledge in software development from a highly practical viewpoint. It has two goals: (1) Define the body of empirically validated knowledge in software development so as to advise practitioners on what methods or techniques have been empirically analysed and what the results were; (2) as empirical tests have traditionally been carried out by universities or research centres, propose techniques applicable by industry to check on the software development technologies they use.

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.

Today, software engineers need to know not only how to program effectively but also how to develop proper engineering practices to make their codebase sustainable and healthy. This book emphasizes this difference between programming and software engineering. How can software engineers manage a living codebase that evolves and responds to changing requirements and demands over the length of its life? Based on their experience at Google, software engineers Titus Winters and Hyrum Wright, along with technical writer Tom Manshreck, present a candid and insightful look at how some of the world’s leading practitioners construct and maintain software. This book covers Google’s unique engineering culture, processes, and tools and how these aspects contribute to the effectiveness of an engineering organization. You’ll explore three fundamental principles that software organizations should keep in mind when designing, architecting, writing, and maintaining code: How time affects the sustainability of software and how to make your code resilient over time How scale affects the viability of software practices within an engineering organization What trade-offs a typical engineer needs to make when evaluating design and development decisions

This is the first handbook to cover comprehensively both software engineering and knowledge engineering OCo two important fields that have become interwoven in recent years. Over 60 international experts have contributed to the book. Each chapter has been written in such a way that a practitioner of software engineering and knowledge engineering can easily understand and obtain useful information. Each chapter covers one topic and can be read independently of other chapters, providing both a general survey of the topic and an in-depth exposition of the state of the art. Practitioners will find this handbook useful when looking for solutions to practical problems. Researchers can use it for quick access to the background, current trends and most important references regarding a certain topic. The handbook consists of two volumes. Volume One covers the basic principles and applications of software engineering and knowledge engineering. Volume Two will cover the basic principles and applications of visual and multimedia software engineering, knowledge engineering, data mining for software knowledge, and emerging topics in software engineering and knowledge engineering. Sample Chapter(s). Chapter 1.1: Introduction (97k). Chapter 1.2: Theoretical Language Research (97k). Chapter 1.3: Experimental Science (96k). Chapter 1.4: Evolutionary Versus Revolutionary (108k). Chapter 1.5: Concurrency and Parallelisms (232k). Chapter 1.6: Summary (123k). Contents: Computer Language Advances (D E Cooke et al.); Software Maintenance (G Canfora & A Cimitile); Requirements Engineering (A T Berztiss); Software Engineering Standards: Review and Perspectives (Y-X Wang); A Large Scale Neural Network and Its Applications (D Graupe & H Kordylewski); Software Configuration Management in Software and Hypermedia Engineering: A Survey (L Bendix et al.); The Knowledge Modeling Paradigm in Knowledge Engineering (E Motta); Software Engineering and Knowledge Engineering Issues in Bioinformatics (J T L Wang et al.); Conceptual Modeling in Software Engineering and Knowledge Engineering: Concepts, Techniques and Trends (O Dieste et al.); Rationale Management in Software Engineering (A H Dutoit & B Paech); Exploring Ontologies (Y Kalfoglou), and other papers. Readership: Graduate students, researchers, programmers, managers and academics in software engineering and knowledge engineering."

The volume includes a set of selected papers extended and revised from the I2009 Pacific-Asia Conference on Knowledge Engineering and Software Engineering (KESE 2009) was held on December 19~ 20, 2009, Shenzhen, China. Volume 1 is to provide a forum for researchers, educators, engineers, and government officials involved in the general areas of Computer and Software Engineering to disseminate their latest research results and exchange views on the future research directions of these fields. 140 high-quality papers are included in the volume. Each paper has been peer-reviewed by at least 2 program committee members and selected by the volume editor Prof. Yanwen Wu. On behalf of this volume, we would like to express our sincere appreciation to all of authors and referees for their efforts reviewing the papers. Hoping you can find lots of profound research ideas and results on the related fields of Computer and Software Engineering.