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Synopsis
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
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LAP LAMBERT Academic Publishing, 2026
ISBN 10: 6630474155
ISBN 13: 9786630474152
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Analysis and Design of a Framework for Software Design Risk Prediction
Published by
LAP LAMBERT Academic Publishing, 2026
ISBN 10: 6630474155
ISBN 13: 9786630474152
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PAP
Seller: PBShop.store US, Wood Dale, IL, U.S.A.
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PAP. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Seller Inventory # L0-9786630474152
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Analysis and Design of a Framework for Software Design Risk Prediction
Published by
LAP LAMBERT Academic Publishing Sep 2026, 2026
ISBN 10: 6630474155
ISBN 13: 9786630474152
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Taschenbuch
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 228 pp. Englisch. Seller Inventory # 9786630474152
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Analysis and Design of a Framework for Software Design Risk Prediction (Paperback)
Published by
LAP Lambert Academic Publishing, 2026
ISBN 10: 6630474155
ISBN 13: 9786630474152
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Paperback
Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.
Seller rating 5 out of 5 stars
Paperback. Condition: 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. Seller Inventory # 9786630474152
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Analysis and Design of a Framework for Software Design Risk Prediction
Published by
LAP LAMBERT Academic Publishing, 2026
ISBN 10: 6630474155
ISBN 13: 9786630474152
New
Taschenbuch
Seller: AHA-BUCH GmbH, Einbeck, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: 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. Seller Inventory # 9786630474152
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Analysis and Design of a Framework for Software Design Risk Prediction
Published by
LAP LAMBERT Academic Publishing, 2026
ISBN 10: 6630474155
ISBN 13: 9786630474152
New
Taschenbuch
Seller: preigu, Osnabrück, Germany
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Taschenbuch. Condition: 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. Seller Inventory # 138100463
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Analysis and Design of a Framework for Software Design Risk Prediction (Paperback)
Published by
LAP Lambert Academic Publishing, 2026
ISBN 10: 6630474155
ISBN 13: 9786630474152
New
Paperback
Seller: CitiRetail, Stevenage, United Kingdom
Seller rating 5 out of 5 stars
Paperback. Condition: 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. Seller Inventory # 9786630474152
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Analysis and Design of a Framework for Software Design Risk Prediction
Published by
LAP LAMBERT Academic Publishing Sep 2026, 2026
ISBN 10: 6630474155
ISBN 13: 9786630474152
New
Taschenbuch
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware 228 pp. Englisch. Seller Inventory # 9786630474152
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Analysis and Design of a Framework for Software Design Risk Prediction
Published by
LAP LAMBERT Academic Publishing, 2026
ISBN 10: 6630474155
ISBN 13: 9786630474152
New
Softcover/Taschenbuch
Seller: Home-set, Mannheim, Germany
Seller rating 5 out of 5 stars
Softcover/Taschenbuch. Condition: 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. Seller Inventory # IB-489146