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This book is designed for professionals and students in software engineering or information technology who are interested in understanding the dynamics of software development in order to assess and optimize their own process strategies. It explains how simulation of interrelated technical and social factors can provide a means for organizations to vastly improve their processes. It is structured for readers to approach the subject from different perspectives, and includes descriptive summaries of the best research and applications.
This practical book presents fundamental concepts and issues in computer modeling and simulation (M&S) in a simple and practical way for engineers, scientists, and managers who wish to apply simulation successfully to their real-world problems. It offers a concise approach to the coverage of generic (tool-independent) M&S concepts and enables engineering practitioners to easily learn, evaluate, and apply various available simulation concepts. Worked out examples are included to illustrate the concepts and an example modeling application is continued throughout the chapters to demonstrate the techniques. The book discusses modeling purposes, scoping a model, levels of modeling abstraction, the benefits and cost of including randomness, types of simulation, and statistical techniques. It also includes a chapter on modeling and simulation projects and how to conduct them for customer and engineer benefit and covers the stages of a modeling and simulation study, including process and system investigation, data collection, modeling scoping and production, model verification and validation, experimentation, and analysis of results.
Don't become a statistic--take control of your software projects and plan for success! Success in all types of organization depends increasingly on the development of customized software solutions, yet more than half of software projects now in the works will exceed both their schedules and their budgets by more than 50%. While some types of overruns remain unpredictable, most can be avoided by sound modeling. COCOMO II provides you with a thorough rework of the classic COCOMO model to address modern software processes and construction techniques along with representative examples of applying the models to key software decision situations. It was calibrated and validated using innovative sta...
Emphasises an introduction and explanation of the practical methods used in reliability, and risk studies with a discussion of their uses and limitations Offers basic and advanced methods in reliability analysis that are commonly used in daily practice Provides methods that address unique topics such as dependent failure analysis, importance analysis, and analysis of repairable systems Presents a comprehensive overview of modern probabilistic life assessment methods such as Bayesian estimation, system reliability analysis, and human reliability Includes many ends of chapter problems, a tools website with computational codes, along with a solutions manual to support course adoptions
Ethical Engineering: A Practical Guide with Case Studies provides detailed and practical guidance in making decisions about the many ethical issues practicing engineers may face in their professional lives. It outlines a decision-making procedure and helps engineers construct an ethics toolkit consisting of professional models, a comprehensive set of ethical considerations and factors that help in weighing those considerations, and analyses of particular issues, such as reverse engineering a patented process. Illustrating case studies, both brief and detailed, are provided. Features: • Introduces the nature of ethical decision-making as applied to engineering values and issues. • Helps r...
The book is based on the "best practices" of the UT Software Quality Institute Software Project Management certificates program. Quality Software Project Management identifies and teaches 34 essential project management competencies project managers can use to minimize cost, risk, and time-to-market. Covers the entire project lifecycle: planning. initiation, monitoring/control, and closing. Illuminates its techniques with real-world software management case studies. Authors (leading practitioners) address the pillars of any successful software venture: process, project, and people. Endorsed by the Software Quality Institute.
What Every Engineer Should Know About Data-Driven Analytics provides a comprehensive introduction to the theoretical concepts and approaches of machine learning that are used in predictive data analytics. By introducing the theory and by providing practical applications, this text can be understood by every engineering discipline. It offers a detailed and focused treatment of the important machine learning approaches and concepts that can be exploited to build models to enable decision making in different domains. Utilizes practical examples from different disciplines and sectors within engineering and other related technical areas to demonstrate how to go from data, to insight, and to decis...
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Completely updated, this new edition uniquely explains how to assess and handle technical risk, schedule risk, and cost risk efficiently and effectively for complex systems that include Artificial Intelligence, Machine Learning, and Deep Learning. It enables engineering professionals to anticipate failures and highlight opportunities to turn failure into success through the systematic application of Risk Engineering. What Every Engineer Should Know About Risk Engineering and Management, Second Edition discusses Risk Engineering and how to deal with System Complexity and Engineering Dynamics, as it highlights how AI can present new and unique ways that failures can take place. The new edition...