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2019 | Buch

Introduction Kapitel lesen Erstes Kapitel lesen

Fault Prediction Modeling for the Prediction of Number of Software Faults

verfasst von: Dr. Santosh Singh Rathore, Dr. Sandeep Kumar

Verlag: Springer Singapore

Buchreihe : SpringerBriefs in Computer Science

Enthalten in: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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Über dieses Buch

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.

Inhaltsverzeichnis

Frontmatter
Chapter 1. Introduction
Abstract
In today’s world, software is the key element for the functionality of almost all engineered and automated systems. Due to this evolution, reliability and quality of software systems become crucial for the successful functioning of day-to-day operations.
Santosh Singh Rathore, Sandeep Kumar
Chapter 2. Techniques Used for the Prediction of Number of Faults
Abstract
Prediction of number of faults refers to the process of estimating/predicting a potential number of faults that can occur in each given software module [41]. A software module can be a class for object-oriented software, file for traditional software or any other independent component having a bunch of code bundles together.
Santosh Singh Rathore, Sandeep Kumar
Chapter 3. Homogeneous Ensemble Methods for the Prediction of Number of Faults
Abstract
Software testing is intended to find bugs/faults that can occur in the software components currently under development. Software fault prediction (SFP) helps in achieving this goal by predicting the probability of fault occurrence in the software modules before the testing phase.
Santosh Singh Rathore, Sandeep Kumar
Chapter 4. Linear Rule Based Ensemble Methods for the Prediction of Number of Faults
Abstract
Software fault prediction models are highly influenced by the use of learning techniques and characteristics of fault datasets.
Santosh Singh Rathore, Sandeep Kumar
Chapter 5. Nonlinear Rule Based Ensemble Methods for the Prediction of Number of Faults
Abstract
In the previous chapter, we explored the use of linear rule based ensemble methods for the number of faults prediction. In that work, we used four different ensemble methods, each of them combines the outputs of base learners in a linear form. Results of experimental analysis showed that a stable and accurate fault prediction performance could be achieved using linear rule based ensemble methods. However, these ensemble methods capture only the weighted contributions of base learners and combine them in linear way, which may sometimes suffers from the linearity error problem of fitting in a straight line (Fox in Regression diagnostics: an introduction. Sage, 1991 [1]).
Santosh Singh Rathore, Sandeep Kumar
Chapter 6. Conclusions
Abstract
This chapter concludes the book. The book primarily aimed to present fault prediction modeling for the prediction of number of faults in software systems. It covered details of regression and ensemble methods used for the prediction of number of faults. Further, evaluation of different homogeneous and heterogeneous ensemble methods was presented. The work presented in this book could be advantageous to the new researchers and software practitioners in terms of selecting the appropriate technique/methods when predicting number of faults.
Santosh Singh Rathore, Sandeep Kumar
Backmatter
Metadaten
Titel
Fault Prediction Modeling for the Prediction of Number of Software Faults
verfasst von
Dr. Santosh Singh Rathore
Dr. Sandeep Kumar
Copyright-Jahr
2019
Verlag
Springer Singapore
Electronic ISBN
978-981-13-7131-8
Print ISBN
978-981-13-7130-1
DOI
https://doi.org/10.1007/978-981-13-7131-8