عنوان

Fault Prediction Modeling for the Prediction of Number of Software Faults /

(Number (ISBN

9789811371318

(Number (ISBN

9789811371325

(Number (ISBN

9789811371332

(Number (ISBN

9811371318

(Number (ISBN

9811371326

(Number (ISBN

9811371334

Erroneous ISBN

9789811371301

Erroneous ISBN

981137130X

Title Proper

Fault Prediction Modeling for the Prediction of Number of Software Faults /

General Material Designation

[Book]

First Statement of Responsibility

Santosh Singh Rathore and Sandeep Kumar.

Place of Publication, Distribution, etc.

Singapore :

Name of Publisher, Distributor, etc.

Springer,

Date of Publication, Distribution, etc.

[2019]

Specific Material Designation and Extent of Item

1 online resource

Series Title

SpringerBriefs in Computer Science

Text of Note

Includes bibliographical references and index.

Text of Note

Intro; Preface; Acknowledgements; Contents; About the Authors; 1 Introduction; 1.1 Software Fault Prediction; 1.2 Classification of Software Faults; 1.3 Advantages of Software Fault Prediction; 1.4 Organization of the Book; 1.5 Summary; References; 2 Techniques Used for the Prediction of Number of Faults; 2.1 Regression Techniques; 2.1.1 Linear Regression; 2.1.2 Logistic Regression; 2.1.3 Ridge Regression; 2.1.4 Polynomial Regression; 2.1.5 Principal Component Regression; 2.1.6 Poisson Regression; 2.1.7 Negative Binomial Regression; 2.1.8 Partial Least Square Regression

Text of Note

2.1.9 Ordinal Regression2.1.10 Quasi-Poisson Regression; 2.1.11 Lasso Regression; 2.1.12 Support Vector Regression; 2.2 Ensemble Methods for Regression; 2.2.1 Homogeneous Ensemble Methods; 2.2.2 Heterogeneous Ensemble Methods; 2.3 State-of-Art of Regression and Ensemble Methods for the Prediction of Number of Faults; 2.4 Performance Evaluation Measures; 2.5 Summary; References; 3 Homogeneous Ensemble Methods for the Prediction of Number of Faults; 3.1 Homogeneous Ensemble Methods; 3.2 Evaluation of Homogeneous Ensemble Methods; 3.2.1 Software Fault Datasets; 3.2.2 Experimental Setup

Text of Note

3.2.3 Experimental Procedure3.2.4 Tools and Techniques Used for Experiment; 3.3 Results and Discussion; 3.3.1 Results of Group-1 for MAE and MRE; 3.3.2 Results of Group-2 for MAE and MRE; 3.3.3 Results of Group-3 for MAE and MRE; 3.3.4 Results of Group-4 for MAE and MRE; 3.3.5 Results of Pred(0.30) for All Groups of Fault Datasets; 3.4 Summary; References; 4 Linear Rule Based Ensemble Methods for the Prediction of Number of Faults; 4.1 Linear Rule Based Heterogeneous Ensemble Methods; 4.2 Evaluation of Linear Rule Based Heterogeneous Ensemble Methods; 4.2.1 Software Fault Datasets

Text of Note

4.2.2 Experimental Setup4.2.3 Experimental Procedure; 4.2.4 Tools and Techniques Used for Experiment; 4.3 Results and Discussion; 4.3.1 Results of Group-1 for MAE and MRE; 4.3.2 Results of Group-2 for MAE and MRE; 4.3.3 Results of Group-3 for MAE and MRE; 4.3.4 Results of Group-4 for MAE and MRE; 4.3.5 Results of Pred(0.30) for All Groups of Fault Datasets; 4.4 Summary; References; 5 Nonlinear Rule Based Ensemble Methods for the Prediction of Number of Faults; 5.1 Nonlinear Rule Based Heterogeneous Ensemble Methods; 5.2 Evaluation of Nonlinear Rule Based Heterogeneous Ensemble Methods

Text of Note

5.2.1 Software Fault Datasets5.2.2 Experimental Setup; 5.2.3 Experimental Procedure; 5.2.4 Nonlinear Learning Technique; 5.2.5 Tools and Techniques Used for Experiment; 5.3 Results and Discussion; 5.3.1 Results of Group-1 for MAE and MRE; 5.3.2 Results of Group-2 for MAE and MRE; 5.3.3 Results of Group-3 for MAE and MRE; 5.3.4 Results of Group-4 for MAE and MRE; 5.3.5 Results of Pred(0.30) for All Groups of Fault Datasets; 5.4 Summary; References; 6 Conclusions; Closing Remarks; Index

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Text of Note

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. --

Source for Acquisition/Subscription Address

Springer Nature

Stock Number

com.springer.onix.9789811371318

Title

Fault Prediction Modeling for the Prediction of Number of Software Faults.

International Standard Book Number

9789811371301

Computer software-- Evaluation.

Computer software-- Reliability.

Computer software-- Testing.

Computer software-- Evaluation.

Computer software-- Reliability.

Computer software-- Testing.

COMPUTERS-- Software Development & Engineering-- Quality Assurance & Testing.

COM-- 051330

UMZ

UMZ

Number

Edition

Class number

Rathore, Santosh Singh.

Kumar, Sandeep.

Date of Transaction

20200823230456.0

Cataloguing Rules (Descriptive Conventions))

pn

Electronic name

[Book]

Y