SpringerBriefs in Computer Science

Fault Prediction Modeling for the Prediction of Number of Software Faults

Authors: Rathore, Santosh Singh, Kumar, Sandeep

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  • Illustrates the process of number of fault prediction
  • Features special chapters on number of fault prediction and ensemble methods
  • Broadens readers’ understanding with an empirical study on learning models 
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eBook $44.99
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  • ISBN 978-981-13-7131-8
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  • Immediate eBook download after purchase
Softcover $59.99
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  • ISBN 978-981-13-7130-1
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  • Usually dispatched within 3 to 5 business days.
About this book

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.

 

About the authors

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.

Table of contents (6 chapters)

Table of contents (6 chapters)
  • Introduction

    Rathore, Santosh Singh (et al.)

    Pages 1-9

  • Techniques Used for the Prediction of Number of Faults

    Rathore, Santosh Singh (et al.)

    Pages 11-29

  • Homogeneous Ensemble Methods for the Prediction of Number of Faults

    Rathore, Santosh Singh (et al.)

    Pages 31-45

  • Linear Rule Based Ensemble Methods for the Prediction of Number of Faults

    Rathore, Santosh Singh (et al.)

    Pages 47-58

  • Nonlinear Rule Based Ensemble Methods for the Prediction of Number of Faults

    Rathore, Santosh Singh (et al.)

    Pages 59-69

Buy this book

eBook $44.99
price for USA in USD (gross)
  • ISBN 978-981-13-7131-8
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover $59.99
price for USA in USD
  • ISBN 978-981-13-7130-1
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Fault Prediction Modeling for the Prediction of Number of Software Faults
Authors
Series Title
SpringerBriefs in Computer Science
Copyright
2019
Publisher
Springer Singapore
Copyright Holder
The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
eBook ISBN
978-981-13-7131-8
DOI
10.1007/978-981-13-7131-8
Softcover ISBN
978-981-13-7130-1
Series ISSN
2191-5768
Edition Number
1
Number of Pages
XIII, 78
Number of Illustrations
7 b/w illustrations, 1 illustrations in colour
Topics