Software Engineering

Incomplete or missed requirements, omissions, ambiguous product features, lack of user involvement, unrealistic customer expectations, and the proverbial scope creep can result in cost overruns, missed deadlines, poor product quality, and can very well ruin a project. Project Scope Management: A Practical Guide to Requirements for Engineering, Product, Construction, IT and Enterprise Projects describes how to elicit, document, and manage requirements to control project scope creep. It also explains how to manage project stakeholders to minimize the risk of an ever-growing list of user requirements. The book begins by discussing how to collect project requirements and define the project scope. Next, it considers the creation of work breakdown structures and examines the verification and control of the scope. Most of the book is dedicated to explaining how to collect requirements and how to define product and project scope inasmuch as they represent the bulk of the project scope management work undertaken on any project regardless of the industry or the nature of the work involved. The book maintains a focus on practical and sensible tools and techniques rather than academic theories. It examines five different projects and traces their development from a project scope management perspective-from project initiation to the end of the execution and control phases. The types of projects considered include CRM system implementation, mobile number portability, port upgrade, energy-efficient house design, and airport check-in kiosk software. After reading this book, you will learn how to create project charters, high-level scope, detailed requirements specifications, requirements management plans, traceability matrices, and a work breakdown structure for the projects covered.

About the Author

Jamal Moustafaev, MBA, PMP, president and founder of Thinktank Consulting, is an internationally acclaimed expert in the areas of project/portfolio management, project scoping, process improvement, and corporate training. He has completed projects for private sector companies and government organizations in the United States, Canada, Europe, Asia, and the Middle East, including the US Department of Defense (USA), Siemens (Germany), Petronas Oil (Malaysia), and TeliaSonera (Sweden), to name a few. Moustafaev is a certified Project Management Professional (PMPR). He holds an MBA in Finance and a BBA (Finance and Management Science) from Simon Fraser University. In addition to teaching a highly acclaimed Project Management Essentials course at the British Columbia Institute of Technology (Vancouver, Canada), Moustafaev also offers several project and portfolio management corporate seminars through his company: * Practical Portfolio Management-Selecting and Managing the Right Projects * Successful Hands-On Management of IT and Software Projects * Successful Hands-On Management of Modern-Day Projects * Project Scope Management.

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.

About the Author

Dr. Sherif Sakr is a Senior Researcher at National ICT Australia (NICTA), Sydney, Australia. He is also a Conjoint Senior Lecturer at the University of New South Wales (UNSW). He received his PhD degree in Computer and Information Science from Konstanz University, Germany in 2007. He received his BSc and MSc degrees in Computer Science from Cairo University, Egypt, in 2000 and 2003 respectively. In 2011, Sherif held a Visiting Researcher position at the eXtreme Computing Group, Microsoft Research, USA. In 2012, he held a Research MTS position in Alcatel-Lucent Bell Labs. Dr. Sakr has published more than 60 refereed research publications in international journals and conferences such as the IEEE TSC, ACM CSUR, JCSS, IEEE COMST, VLDB, SIGMOD, ICDE, WWW, and CIKM. He has served in the organizing and program committees of numerous conferences and workshops. Dr. Mohamed Medhat Gaber is a reader in the School of Computing Science and Digital Media of Robert Gordon University, UK. Mohamed received his PhD from Monash University, Australia, in 2006. He then held appointments with the University of Sydney, CSIRO, Monash University, and the University of Portsmouth. Dr. Gaber has published over 100 papers, coauthored one monograph-style book, and edited/coedited four books on data mining, and knowledge discovery. He has served in the program committees of major conferences related to data mining, including ICDM, PAKDD, ECML/PKDD, and ICML. He has also been a member of the organizing committees of numerous conferences and workshops.

Practical Guidance on the Efficient Development of High-Quality Software Introduction to Software Engineering, Second Edition equips students with the fundamentals to prepare them for satisfying careers as software engineers regardless of future changes in the field, even if the changes are unpredictable or disruptive in nature. Retaining the same organization as its predecessor, this second edition adds considerable material on open source and agile development models. The text helps students understand software development techniques and processes at a reasonably sophisticated level. Students acquire practical experience through team software projects. Throughout much of the book, a relatively large project is used to teach about the requirements, design, and coding of software. In addition, a continuing case study of an agile software development project offers a complete picture of how a successful agile project can work. The book covers each major phase of the software development life cycle, from developing software requirements to software maintenance. It also discusses project management and explains how to read software engineering literature. Three appendices describe software patents, command-line arguments, and flowcharts.

About the Author

Ronald J. Leach is an independent consultant and professor and department chair emeritus of computer science at Howard University. His research interests include software reuse, software measurement and metrics, and software fault-tolerance. He earned a BS, an MS, and a PhD in mathematics from the University of Maryland as well as an MS in computer science from Johns Hopkins University.

Empirical research has now become an essential component of software engineering yet software practitioners and researchers often lack an understanding of how the empirical procedures and practices are applied in the field. Empirical Research in Software Engineering: Concepts, Analysis, and Applications shows how to implement empirical research processes, procedures, and practices in software engineering. Written by a leading researcher in empirical software engineering, the book describes the necessary steps to perform replicated and empirical research. It explains how to plan and design experiments, conduct systematic reviews and case studies, and analyze the results produced by the empirical studies. The book balances empirical research concepts with exercises, examples, and real-life case studies, making it suitable for a course on empirical software engineering. The author discusses the process of developing predictive models, such as defect prediction and change prediction, on data collected from source code repositories. She also covers the application of machine learning techniques in empirical software engineering, includes guidelines for publishing and reporting results, and presents popular software tools for carrying out empirical studies.

About the Author

Ruchika Malhotra is an assistant professor in the Department of Software Engineering at Delhi Technological University (formerly Delhi College of Engineering). She was awarded the prestigious UGC Raman Fellowship for pursuing post-doctoral research in the Department of Computer and Information Science at Indiana University-Purdue University. She received her master’s and doctorate degrees in software engineering from the University School of Information Technology of Guru Gobind Singh Indraprastha University. She received the IBM Best Faculty Award in 2013 and has published more than 100 research papers in international journals and conferences. Her research interests include software testing, improving software quality, statistical and adaptive prediction models, software metrics, neural nets modeling, and the definition and validation of software metrics.

Intended for introductory and advanced courses in software engineering.

The ninth edition of Software Engineering presents a broad perspective of software engineering, focusing on the processes and techniques fundamental to the creation of reliable, software systems. Increased coverage of agile methods and software reuse, along with coverage of ‘traditional’ plan-driven software engineering, gives readers the most up-to-date view of the field currently available. Practical case studies, a full set of easy-to-access supplements, and extensive web resources make teaching the course easier than ever.

For introductory courses in C Programming. Also for courses in Programming for Engineers, Programming for Business, and Programming for Technology.

The Deitels’ How to Program series offers unparalleled breadth and depth of object-oriented programming concepts and intermediate-level topics for further study. Using the Deitels’ signature “Live-Code™ Approach,” this complete, authoritative introduction to C programming introduces fundamentals of structured programming, and covers relevant features of C language’s C-201X standard. It also includes an updated treatment of C for those who want to transition to object-oriented concepts.