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Sinopsis
This book presents an intelligent framework for identifying, predicting, prioritizing, and estimating software risks during the design phase of the Software Development Life Cycle (SDLC). Software design is exposed to diverse risks arising from requirements, architectural decisions, design activities, programming technologies, validation, and documentation, which can adversely affect software quality, cost, and delivery schedules.The book systematically examines the characteristics, sources, and causes of software design risks and investigates the relationships among identified risk factors. It presents a Bayesian Network-based Risk Prediction Model (RPM) for predicting potential risks, supported by risk trees and graphical analysis. A Fuzzy Inference System (FIS) is employed to prioritize risks according to their severity, detectability, and dependability. Furthermore, an Extreme Learning Machine (ELM)-based approach is presented for risk estimation and impact analysis.
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Analysis and Design of a Framework for Software Design Risk Prediction
Publicado por
LAP LAMBERT Academic Publishing, 2026
ISBN 10: 6630474155
ISBN 13: 9786630474152
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Imagen de archivo
Analysis and Design of a Framework for Software Design Risk Prediction
Publicado por
LAP LAMBERT Academic Publishing, 2026
ISBN 10: 6630474155
ISBN 13: 9786630474152
Nuevo
PAP
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Analysis and Design of a Framework for Software Design Risk Prediction
Publicado por
LAP LAMBERT Academic Publishing Sep 2026, 2026
ISBN 10: 6630474155
ISBN 13: 9786630474152
Nuevo
Taschenbuch
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 228 pp. Englisch. Nº de ref. del artículo: 9786630474152
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Analysis and Design of a Framework for Software Design Risk Prediction (Paperback)
Publicado por
LAP Lambert Academic Publishing, 2026
ISBN 10: 6630474155
ISBN 13: 9786630474152
Nuevo
Paperback
Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de America
Calificación del vendedor: 5 de 5 estrellas
Paperback. Condición: new. Paperback. This book presents an intelligent framework for identifying, predicting, prioritizing, and estimating software risks during the design phase of the Software Development Life Cycle (SDLC). Software design is exposed to diverse risks arising from requirements, architectural decisions, design activities, programming technologies, validation, and documentation, which can adversely affect software quality, cost, and delivery schedules.The book systematically examines the characteristics, sources, and causes of software design risks and investigates the relationships among identified risk factors. It presents a Bayesian Network-based Risk Prediction Model (RPM) for predicting potential risks, supported by risk trees and graphical analysis. A Fuzzy Inference System (FIS) is employed to prioritize risks according to their severity, detectability, and dependability. Furthermore, an Extreme Learning Machine (ELM)-based approach is presented for risk estimation and impact analysis. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9786630474152
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Analysis and Design of a Framework for Software Design Risk Prediction
Publicado por
LAP LAMBERT Academic Publishing, 2026
ISBN 10: 6630474155
ISBN 13: 9786630474152
Nuevo
Taschenbuch
Librería: AHA-BUCH GmbH, Einbeck, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book presents an intelligent framework for identifying, predicting, prioritizing, and estimating software risks during the design phase of the Software Development Life Cycle (SDLC). Software design is exposed to diverse risks arising from requirements, architectural decisions, design activities, programming technologies, validation, and documentation, which can adversely affect software quality, cost, and delivery schedules.The book systematically examines the characteristics, sources, and causes of software design risks and investigates the relationships among identified risk factors. It presents a Bayesian Network-based Risk Prediction Model (RPM) for predicting potential risks, supported by risk trees and graphical analysis. A Fuzzy Inference System (FIS) is employed to prioritize risks according to their severity, detectability, and dependability. Furthermore, an Extreme Learning Machine (ELM)-based approach is presented for risk estimation and impact analysis. Nº de ref. del artículo: 9786630474152
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Analysis and Design of a Framework for Software Design Risk Prediction
Publicado por
LAP LAMBERT Academic Publishing, 2026
ISBN 10: 6630474155
ISBN 13: 9786630474152
Nuevo
Taschenbuch
Librería: preigu, Osnabrück, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: Neu. Analysis and Design of a Framework for Software Design Risk Prediction | Tabrez Khan (u. a.) | Taschenbuch | Englisch | 2026 | LAP LAMBERT Academic Publishing | EAN 9786630474152 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand. Nº de ref. del artículo: 138100463
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Analysis and Design of a Framework for Software Design Risk Prediction
Publicado por
LAP LAMBERT Academic Publishing Sep 2026, 2026
ISBN 10: 6630474155
ISBN 13: 9786630474152
Nuevo
Taschenbuch
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
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Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware 228 pp. Englisch. Nº de ref. del artículo: 9786630474152
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Analysis and Design of a Framework for Software Design Risk Prediction (Paperback)
Publicado por
LAP Lambert Academic Publishing, 2026
ISBN 10: 6630474155
ISBN 13: 9786630474152
Nuevo
Paperback
Librería: CitiRetail, Stevenage, Reino Unido
Calificación del vendedor: 5 de 5 estrellas
Paperback. Condición: new. Paperback. This book presents an intelligent framework for identifying, predicting, prioritizing, and estimating software risks during the design phase of the Software Development Life Cycle (SDLC). Software design is exposed to diverse risks arising from requirements, architectural decisions, design activities, programming technologies, validation, and documentation, which can adversely affect software quality, cost, and delivery schedules.The book systematically examines the characteristics, sources, and causes of software design risks and investigates the relationships among identified risk factors. It presents a Bayesian Network-based Risk Prediction Model (RPM) for predicting potential risks, supported by risk trees and graphical analysis. A Fuzzy Inference System (FIS) is employed to prioritize risks according to their severity, detectability, and dependability. Furthermore, an Extreme Learning Machine (ELM)-based approach is presented for risk estimation and impact analysis. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Nº de ref. del artículo: 9786630474152
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Analysis and Design of a Framework for Software Design Risk Prediction
Publicado por
LAP LAMBERT Academic Publishing, 2026
ISBN 10: 6630474155
ISBN 13: 9786630474152
Nuevo
Softcover/Taschenbuch
Librería: Home-set, Mannheim, Alemania
Calificación del vendedor: 5 de 5 estrellas
Softcover/Taschenbuch. Condición: Neu. This book presents an intelligent framework for identifying, predicting, prioritizing, and estimating software risks during the design phase of the Software Development Life Cycle (SDLC). Software design is exposed to diverse risks arising from requirements, architectural decisions, design activities, programming technologies, validation, and documentation, which can adversely affect software quality, cost, and delivery schedules.The book systematically examines the characteristics, sources, and causes of software design risks and investigates the relationships among identified risk factors. It presents a Bayesian Network-based Risk Prediction Model (RPM) for predicting potential risks, supported by risk trees and graphical analysis. A Fuzzy Inference System (FIS) is employed to prioritize risks according to their severity, detectability, and dependability. Furthermore, an Extreme Learning Machine (ELM)-based approach is presented for risk estimation and impact analysis. Sprache: Englisch Gewicht in Gramm: 358. Nº de ref. del artículo: IB-489146
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