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For courses in computer science and software engineering The Fundamental Practice of Software Engineering Software Engineering introduces students to the overwhelmingly important subject of software programming and development. In the past few years, computer systems have come to dominate not just our technological growth, but the foundations of our world’s major industries. This text seeks to lay out the fundamental concepts of this huge and continually growing subject area in a clear and comprehensive manner. The Tenth Edition contains new information that highlights various technological updates of recent years, providing students with highly relevant and current information. Sommerville’s experience in system dependability and systems engineering guides the text through a traditional plan-based approach that incorporates some novel agile methods. The text strives to teach the innovators of tomorrow how to create software that will make our world a better, safer, and more advanced place to live.
"Software Engineering" presents a broad perspective on software systems engineering, concentrating on widely-used techniques for developing large-scale software systems. This best-selling book covers a wide spectrum of software processes from initial requirements elicitation through design and development to system evolution. It supports students taking undergraduate and graduate courses in software engineering. The sixth edition has been restructured and updated, important new topics have been added and obsolete material has been cut. Reuse now focuses on component-based development and patterns; object-oriented design has a process focus and uses the UML; the chapters on requirements have been split to cover the requirements themselves and requirements engineering process; cost estimation has been updated to include the COCOMO 2 model.
Economics and technology have dramatically re-shaped the landscape of software development. It is no longer uncommon to find a software development team dispersed across countries or continents. Geographically distributed development challenges the ability to clearly communicate, enforce standards, ensure quality levels, and coordinate tasks. Global Software Development Handbook explores techniques that can bridge distances, create cohesion, promote quality, and strengthen lines of communication. The book introduces techniques proven successful at international electronics and software giant Siemens AG. It shows how this multinational uses a high-level process framework that balances agility and discipline for globally distributed software development. The authors delineate an organizational structure that not only fosters team building, but also achieves effective collaboration among the central and satellite teams. The handbook explores the issues surrounding quality and the processes required to realize quality in a distributed environment. Communication is a tremendous challenge, especially for teams separated by several time zones, and the authors elucidate how to uncover patterns of communication among these teams to determine effective strategies for managing communication. The authors analyze successful and failed projects and apply this information to how a project can be successful with distributed teams. They also provide lightweight processes that can be dynamically adapted to the demands of any project.
This book, written from a software engineering point of view, provides the practitioner's guide to developing global e-commerce sites.
Software Engineer's Reference Book provides the fundamental principles and general approaches, contemporary information, and applications for developing the software of computer systems. The book is comprised of three main parts, an epilogue, and a comprehensive index. The first part covers the theory of computer science and relevant mathematics. Topics under this section include logic, set theory, Turing machines, theory of computation, and computational complexity. Part II is a discussion of software development methods, techniques and technology primarily based around a conventional view of the software life cycle. Topics discussed include methods such as CORE, SSADM, and SREM, and formal methods including VDM and Z. Attention is also given to other technical activities in the life cycle including testing and prototyping. The final part describes the techniques and standards which are relevant in producing particular classes of application. The text will be of great use to software engineers, software project managers, and students of computer science.
Data Science for Software Engineering: Sharing Data and Models presents guidance and procedures for reusing data and models between projects to produce results that are useful and relevant. Starting with a background section of practical lessons and warnings for beginner data scientists for software engineering, this edited volume proceeds to identify critical questions of contemporary software engineering related to data and models. Learn how to adapt data from other organizations to local problems, mine privatized data, prune spurious information, simplify complex results, how to update models for new platforms, and more. Chapters share largely applicable experimental results discussed with the blend of practitioner focused domain expertise, with commentary that highlights the methods that are most useful, and applicable to the widest range of projects. Each chapter is written by a prominent expert and offers a state-of-the-art solution to an identified problem facing data scientists in software engineering. Throughout, the editors share best practices collected from their experience training software engineering students and practitioners to master data science, and highlight the methods that are most useful, and applicable to the widest range of projects. Shares the specific experience of leading researchers and techniques developed to handle data problems in the realm of software engineering Explains how to start a project of data science for software engineering as well as how to identify and avoid likely pitfalls Provides a wide range of useful qualitative and quantitative principles ranging from very simple to cutting edge research Addresses current challenges with software engineering data such as lack of local data, access issues due to data privacy, increasing data quality via cleaning of spurious chunks in data

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