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Fault Prediction Modeling for the Prediction of Number of Software Faults (SpringerBriefs in Computer Science) - Tapa blanda
Sinopsis
This book addresses software faults-a critical issue that not only reduces the quality of software, but also increases their development costs. Various models for predicting the fault-proneness of software systems have been proposed; however, most of them provide inadequate information, limiting their effectiveness. This book focuses on the prediction of number of faults in software modules, and provides readers with essential insights into the generalized architecture, different techniques, and state-of-the art literature. In addition, it covers various software fault datasets and issues that crop up when predicting number of faults.
A must-read for readers seeking a "one-stop" source of information on software fault prediction and recent research trends, the book will especially benefit those interested in pursuing research in this area. At the same time, it will provide experienced researchers with a valuable summary of the latest developments.
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Acerca del autor
Dr. Santosh Singh Rathore is currently working as an Assistant Professor at the Department of Computer Science and Engineering, National Institute of Technology (NIT) Jalandhar, India. He received his Ph.D. degree from the Indian Institute of Technology Roorkee (IIT) and his master’s degree (M.Tech.) from the Indian Institute of Information Technology Design and Manufacturing (IIITDM) in Jabalpur, India. His research interests include Software Fault Prediction, Software Quality Assurance, Empirical Software Engineering, Object-Oriented Software Development, and Object-Oriented Metrics. He has published in various peer-reviewed journals and international conference proceedings.
Dr. Sandeep Kumar is currently working as an Assistant Professor at the Department of Computer Science and Engineering, Indian Institute of Technology (IIT) Roorkee, India. His areas of interest include Semantic Web, Web Services, and Software Engineering. He is currently engaged in various national and international research/consultancy projects and has many accolades to his credit, e.g. a Young Faculty Research Fellowship from the MeitY (Govt. of India), NSF/TCPP early adopter award―2014, 2015, ITS Travel Award 2011 and 2013, etc. He is a member of the ACM and senior member of the IEEE. His name has also been listed in major directories such as Marquis Who’s Who, IBC, and others.
De la contraportada
This book addresses software faults—a critical issue that not only reduces the quality of software, but also increases their development costs. Various models for predicting the fault-proneness of software systems have been proposed; however, most of them provide inadequate information, limiting their effectiveness. This book focuses on the prediction of number of faults in software modules, and provides readers with essential insights into the generalized architecture, different techniques, and state-of-the art literature. In addition, it covers various software fault datasets and issues that crop up when predicting number of faults.
A must-read for readers seeking a “one-stop” source of information on software fault prediction and recent research trends, the book will especially benefit those interested in pursuing research in this area. At the same time, it will provide experienced researchers with a valuable summary of the latest developments.
"Sobre este título" puede pertenecer a otra edición de este libro.
- EditorialSpringer
- Año de publicación2019
- ISBN 10 981137130X
- ISBN 13 9789811371301
- EncuadernaciónTapa blanda
- IdiomaInglés
- Número de edición1
- Número de páginas92
- Contacto del fabricanteno disponible
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Fault Prediction Modeling for the Prediction of Number of Software Faults
Publicado por
Springer Nature Singapore, 2019
ISBN 10: 981137130X
ISBN 13: 9789811371301
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Calificación del vendedor: 5 de 5 estrellas
Condición: Sehr gut. Zustand: Sehr gut | Seiten: 92 | Sprache: Englisch | Produktart: Bücher. Nº de ref. del artículo: 33643668/2
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Fault Prediction Modeling for the Prediction of Number of Software Faults
Publicado por
Springer Nature Singapore Apr 2019, 2019
ISBN 10: 981137130X
ISBN 13: 9789811371301
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book addresses software faults-a critical issue that not only reduces the quality of software, but also increases their development costs. Various models for predicting the fault-proneness of software systems have been proposed; however, most of them provide inadequate information, limiting their effectiveness. This book focuses on the prediction of number of faults in software modules, and provides readers with essential insights into the generalized architecture, different techniques, and state-of-the art literature. In addition, it covers various software fault datasets and issues that crop up when predicting number of faults.A must-read for readers seeking a 'one-stop' source of information on software fault prediction and recent research trends, the book will especially benefit those interested in pursuing research in this area. At the same time, it will provide experienced researchers with a valuable summary of the latest developments. 92 pp. Englisch. Nº de ref. del artículo: 9789811371301
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Fault Prediction Modeling for the Prediction of Number of Software Faults (SpringerBriefs in Computer Science)
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Fault Prediction Modeling for the Prediction of Number of Software Faults
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Fault Prediction Modeling for the Prediction of Number of Software Faults
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Springer Nature Singapore, Springer Nature Singapore, 2019
ISBN 10: 981137130X
ISBN 13: 9789811371301
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Librería: AHA-BUCH GmbH, Einbeck, Alemania
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Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book addresses software faults-a critical issue that not only reduces the quality of software, but also increases their development costs. Various models for predicting the fault-proneness of software systems have been proposed; however, most of them provide inadequate information, limiting their effectiveness. This book focuses on the prediction of number of faults in software modules, and provides readers with essential insights into the generalized architecture, different techniques, and state-of-the art literature. In addition, it covers various software fault datasets and issues that crop up when predicting number of faults.A must-read for readers seeking a 'one-stop' source of information on software fault prediction and recent research trends, the book will especially benefit those interested in pursuing research in this area. At the same time, it will provide experienced researchers with a valuable summary of the latest developments. Nº de ref. del artículo: 9789811371301
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Fault Prediction Modeling for the Prediction of Number of Software Faults
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Fault Prediction Modeling for the Prediction of Number of Software Faults (SpringerBriefs in Computer Science)
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Fault Prediction Modeling for the Prediction of Number of Software Faults
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Springer-Verlag New York Inc, 2019
ISBN 10: 981137130X
ISBN 13: 9789811371301
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Librería: Revaluation Books, Exeter, Reino Unido
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Paperback. Condición: Brand New. 92 pages. 9.25x6.10x0.22 inches. In Stock. Nº de ref. del artículo: x-981137130X
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Fault Prediction Modeling for the Prediction of Number of Software Faults
Publicado por
Springer Nature Singapore, Springer Nature Singapore Apr 2019, 2019
ISBN 10: 981137130X
ISBN 13: 9789811371301
Nuevo
Taschenbuch
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: Neu. Neuware -This book addresses software faults¿a critical issue that not only reduces the quality of software, but also increases their development costs. Various models for predicting the fault-proneness of software systems have been proposed; however, most of them provide inadequate information, limiting their effectiveness. This book focuses on the prediction of number of faults in software modules, and provides readers with essential insights into the generalized architecture, different techniques, and state-of-the art literature. In addition, it covers various software fault datasets and issues that crop up when predicting number of faults.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 92 pp. Englisch. Nº de ref. del artículo: 9789811371301
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Fault Prediction Modeling for the Prediction of Number of Software Faults
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Condición: New. pp. XIII, 78 8 illus., 1 illus. in color. 1 Edition NO-PA16APR2015-KAP. Nº de ref. del artículo: 26384557662
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