國立高雄大學圖資館 |

Language: English

Back

Fault prediction modeling for the pr...

Kumar, Sandeep.

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 faultsby 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.
Contained By:	Springer eBooks
Subject:	Computer softwareReliability.
Online resource:	https://doi.org/10.1007/978-981-13-7131-8
ISBN:	9789811371318$q(electronic bk.)

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$q(electronic bk.)

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

199854
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
LDR:02343nmm a2200337 a 4500 001 554400
003 DE-He213
005 20190403151528.0
006 m d
007 cr nn 008maaau
008 191118s2019 si s 0 eng d
020 $a 9789811371318$q(electronic bk.)
020 $a 9789811371301$q(paper)
024 7 $a 10.1007/978-981-13-7131-8 $2 doi
035 $a 978-981-13-7131-8
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.76.R44
072 7 $a UMZ $2 bicssc
072 7 $a COM051230 $2 bisacsh
072 7 $a UMZ $2 thema
082 0 4 $a 005.068 $2 23
090 $a QA76.76.R44 $b R234 2019
100 1 $a Rathore, Santosh Singh. $3 818716
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.
650 0 $a Computer software $x Reliability. $3 199854
650 0 $a Computer software $x Testing. $3 189355
650 0 $a Computer software $x Evaluation. $3 230892
650 1 4 $a Software Engineering. $3 274511
650 2 4 $a The Computer Industry. $3 285768
700 1 $a Kumar, Sandeep. $3 212735
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
830 0 $a SpringerBriefs in computer science. $3 559641
856 4 0 $u https://doi.org/10.1007/978-981-13-7131-8
950 $a Computer Science (Springer-11645)