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Fault prediction modeling for the pr...

Rathore, Santosh Singh.

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Fault prediction modeling for the prediction of number of software faults

Record Type:	Electronic resources : Monograph/item
Title/Author:	Fault prediction modeling for the prediction of number of software faults/ by Santosh Singh Rathore, Sandeep Kumar.
Author:	Rathore, Santosh Singh.
other author:	Kumar, Sandeep.
Published:	Singapore :Springer Singapore : : 2019.,
Description:	xiii, 78 p. :ill., digital ;24 cm.
[NT 15003449]:	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.
Contained By:	Springer eBooks
Subject:	Computer software - Reliability. -
Online resource:	https://doi.org/10.1007/978-981-13-7131-8
ISBN:	9789811371318

Fault prediction modeling for the prediction of number of software faults
Rathore, Santosh Singh.

Fault prediction modeling for the prediction of number of software faults[electronic resource] /by Santosh Singh Rathore, Sandeep Kumar. - Singapore :Springer Singapore :2019. - xiii, 78 p. :ill., digital ;24 cm. - SpringerBriefs in computer science,2191-5768. - SpringerBriefs in computer science..

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.

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.

ISBN: 9789811371318

Standard No.: 10.1007/978-981-13-7131-8doiSubjects--Topical Terms:

654217
Computer software
--Reliability.

LC Class. No.: QA76.76.R44

Dewey Class. No.: 005.068

Fault prediction modeling for the prediction of number of software faults
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245 1 0 $a Fault prediction modeling for the prediction of number of software faults $h [electronic resource] / $c by Santosh Singh Rathore, Sandeep Kumar.
260 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2019.
300 $a xiii, 78 p. : $b ill., digital ; $c 24 cm.
490 1 $a SpringerBriefs in computer science, $x 2191-5768
505 0 $a 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.
520 $a 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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650 1 4 $a Software Engineering. $3 890874
650 2 4 $a The Computer Industry. $3 895945
700 1 $a Kumar, Sandeep. $3 1305732
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