Fault Prediction Modeling for the Prediction of Number of Software Faults

Santosh Singh Rathore, Sandeep Kumar (Autoren)

Buch | Softcover

78 Seiten

2019 | 1st ed. 2019
Springer Verlag, Singapore
978-981-13-7130-1 (ISBN)

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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.

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.

Introduction.- Techniques used for the Prediction of Number of Faults.- Homogeneous Ensemble Methods for the Prediction of Number of Faults.- Linear Rule based Ensemble Methods for the prediction of Number of Faults.- Non-Linear Rule based Ensemble Methods for the prediction of Number of Faults.- Conclusions.

Erscheinungsdatum	26.04.2019
Reihe/Serie	SpringerBriefs in Computer Science
Zusatzinfo	1 Illustrations, color; 7 Illustrations, black and white; XIII, 78 p. 8 illus., 1 illus. in color.
Verlagsort	Singapore
Sprache	englisch
Maße	155 x 235 mm
Themenwelt	Mathematik / Informatik ► Informatik ► Software Entwicklung
Themenwelt	Wirtschaft ► Betriebswirtschaft / Management ► Wirtschaftsinformatik
Schlagworte	Ensemble methods • learning models • Number of Fault Prediction • Quality assurance • Soft computing and machine learning • Software engineering • software fault prediction • Testing
ISBN-10	981-13-7130-X / 981137130X
ISBN-13	978-981-13-7130-1 / 9789811371301
Zustand	Neuware