Fault Prediction Modeling for the Prediction of Number of Software Faults
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
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Santosh Singh Rathore Sandeep Kumar
Fault Prediction Modeling for the Prediction of Number of Software Faults 123
SpringerBriefs in Computer Science Series Editors Stan Zdonik, Brown University, Providence, RI, USA Shashi Shekhar, University of Minnesota, Minneapolis, MN, USA Xindong Wu, University of Vermont, Burlington, VT, USA Lakhmi C. Jain, University of South Australia, Adelaide, SA, Australia David Padua, University of Illinois Urbana-Champaign, Urbana, IL, USA Xuemin Sherman Shen, University of Waterloo, Waterloo, ON, Canada Borko Furht, Florida Atlantic University, Boca Raton, FL, USA V. S. Subrahmanian, University of Maryland, College Park, MD, USA Martial Hebert, Carnegie Mellon University, Pittsburgh, PA, USA Katsushi Ikeuchi, University of Tokyo, Tokyo, Japan Bruno Siciliano, Università di Napoli Federico II, Napoli, Italy Sushil Jajodia, George Mason University, Fairfax, VA, USA Newton Lee, Institute for Education, Research, and Scholarships, Los Angeles, CA, USA
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Santosh Singh Rathore Sandeep Kumar •
Fault Prediction Modeling for the Prediction of Number of Software Faults
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Santosh Singh Rathore Department of Computer Science and Engineering ABV-Indian Institute of Information Technology and Management Gwalior Gwalior, Madhya Pradesh, India
Sandeep Kumar Department of Computer Science and Engineering Indian Institute of Technology Roorkee Roorkee, Uttarakhand, India
ISSN 2191-5768 ISSN 2191-5776 (electronic) SpringerBriefs in Computer Science ISBN 978-981-13-7130-1 ISBN 978-981-13-7131-8 (eBook) https://doi.org/10.1007/978-981-13-7131-8 Library of Congress Control Number: 2019934353 © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2019 This work is sub
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