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.
Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.
Emilia Mendes is a Professor of Software Engineering at the Blekinge Institute of Technology (Sweden) and has been a full-time academic for the past 14 years, making significant research and practical contributions to her fields of research - empirical Web/software engineering, measurement and metrics. Her findings provide solutions to industry, helping to improve development processes and products. Her Springer book on Web engineering in 2006 was the first to provide industry and academia with theory as well as case studies on numerous aspects related to Web development and measurement. Prior to her academic career, she worked in the ICT industry for ten years as a programmer, business analyst and project manager.
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.
„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.
Anbieter: GreatBookPrices, Columbia, MD, USA
Zustand: New. Bestandsnummer des Verkäufers 21318242-n
Anzahl: Mehr als 20 verfügbar
Anbieter: BargainBookStores, Grand Rapids, MI, USA
Hardback or Cased Book. Zustand: New. Practitioner's Knowledge Representation: A Pathway to Improve Software Effort Estimation. Book. Bestandsnummer des Verkäufers BBS-9783642541568
Anbieter: California Books, Miami, FL, USA
Zustand: New. Bestandsnummer des Verkäufers I-9783642541568
Anzahl: Mehr als 20 verfügbar
Anbieter: GreatBookPrices, Columbia, MD, USA
Zustand: As New. Unread book in perfect condition. Bestandsnummer des Verkäufers 21318242
Anzahl: Mehr als 20 verfügbar
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
Zustand: New. In. Bestandsnummer des Verkäufers ria9783642541568_new
Anzahl: Mehr als 20 verfügbar
Anbieter: Brook Bookstore On Demand, Napoli, NA, Italien
Zustand: new. Questo è un articolo print on demand. Bestandsnummer des Verkäufers 5150eb75820aab52fc59f8b55ced21f6
Anzahl: Mehr als 20 verfügbar
Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
Buch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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 (TM) 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. 224 pp. Englisch. Bestandsnummer des Verkäufers 9783642541568
Anzahl: 2 verfügbar
Anbieter: GreatBookPricesUK, Woodford Green, Vereinigtes Königreich
Zustand: New. Bestandsnummer des Verkäufers 21318242-n
Anzahl: Mehr als 20 verfügbar
Anbieter: Buchmarie, Darmstadt, Deutschland
Zustand: Good. Bestandsnummer des Verkäufers 3482351_a10_2x
Anzahl: 1 verfügbar
Anbieter: Books Puddle, New York, NY, USA
Zustand: New. pp. 224. Bestandsnummer des Verkäufers 26142283420
Anzahl: 4 verfügbar