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The main goal of this book is to help organizations improve their effort estimates and effort estimation processes by providing a step-by-step methodology that takes them through the creation and validation of models that are based on their own knowledge and experience. Such models, once validated, can then be used to obtain predictions, carry out risk analyses, enhance their estimation processes for new projects, and generally advance them as learning organizations. Emilia Mendes presents the Expert-Based Knowledge Engineering of Bayesian Networks (EKEBNs) methodology, which she has used and adapted during the course of several industry collaborations with different companies world-wide over more than 6 years. The book itself consists of two major parts: first, the methodology’s foundations in knowledge management, effort estimation (with special emphasis on the intricacies of software and Web development), and Bayesian networks are detailed; then six industry case studies are presented which illustrate the practical use of EKEBNs.  Domain experts from each company participated in the elicitation of the bespoke models for effort estimation, and all models were built employing the widely-used Netica ™ tool. This part is rounded off with a chapter summarizing the experiences with the methodology and the derived models. Practitioners working on software project management, software process quality, or effort estimation and risk analysis in general will find a thorough introduction into an industry-proven methodology as well as numerous experiences, tips and possible pitfalls invaluable for their daily work.

Knowledge representation (Information theory) --- Data processing. --- Representation of knowledge (Information theory) --- Artificial intelligence --- Information theory --- Software engineering. --- Computer science. --- Project management. --- Information Systems. --- Artificial intelligence. --- Knowledge management. --- Software Engineering. --- Probability and Statistics in Computer Science. --- Project Management. --- Management of Computing and Information Systems. --- Artificial Intelligence. --- Knowledge Management. --- Management of knowledge assets --- Management --- Information technology --- Intellectual capital --- Organizational learning --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Industrial project management --- Informatics --- Science --- Computer software engineering --- Engineering --- Mathematical statistics. --- Management information systems. --- Computer-based information systems --- EIS (Information systems) --- Executive information systems --- MIS (Information systems) --- Sociotechnical systems --- Information resources management --- Mathematics --- Statistical inference --- Statistics, Mathematical --- Statistics --- Probabilities --- Sampling (Statistics) --- Communication systems --- Statistical methods

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Since its original inception back in 1989 the Web has changed into an environment where Web applications range from small-scale information dissemination applications, often developed by non-IT professionals, to large-scale, commercial, enterprise-planning and scheduling applications, developed by multidisciplinary teams of people with diverse skills and backgrounds and using cutting-edge, diverse technologies. As an engineering discipline, Web engineering must provide principles, methodologies and frameworks to help Web professionals and researchers develop applications and manage projects effectively. Mendes and Mosley have selected experts from numerous areas in Web engineering, who contribute chapters where important concepts are presented and then detailed using real industrial case studies. After an introduction into the discipline itself and its intricacies, the contributions range from Web effort estimation, productivity benchmarking and conceptual and model-based application development methodologies, to other important principles such as usability, reliability, testing, process improvement and quality measurement. This is the first book that looks at Web engineering from a measurement perspective. The result is a self-containing, comprehensive overview detailing the role of measurement and metrics within the context of Web engineering. This book is ideal for professionals and researchers who want to know how to use sound principles for the effective management of Web projects, as well as for courses at an advanced undergraduate or graduate level.

Web site development. --- Web sites --- Application software --- Engineering models. --- Testing. --- Development. --- Engineering --- Similitude in engineering --- Models and modelmaking --- Application computer programs --- Application computer software --- Applications software --- Apps (Computer software) --- Computer software --- Development of application software --- Pages, Web --- Sites, Web --- Web pages --- Websites --- World Wide Web pages --- World Wide Web sites --- WWW pages --- WWW sites --- Computer network resources --- Development of Web sites --- Internet programming --- Models --- Development --- Information Technology --- Software Engineering --- Software engineering. --- Computer system performance. --- Information Systems. --- Software Engineering. --- System Performance and Evaluation. --- Management of Computing and Information Systems. --- Computer software engineering --- Computer system failures. --- Management information systems. --- Computer science. --- Informatics --- Science --- Computer-based information systems --- EIS (Information systems) --- Executive information systems --- MIS (Information systems) --- Sociotechnical systems --- Information resources management --- Management --- Computer failures --- Computer malfunctions --- Computer systems --- Failure of computer systems --- System failures (Engineering) --- Fault-tolerant computing --- Communication systems --- Failures

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Software engineering

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