Fault Prediction Modeling for the Prediction of Number of Software Faults

• Κύριοι συγγραφείς: Rathore, Santosh Singh (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut), Kumar, Sandeep (http://id.loc.gov/vocabulary/relators/aut)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Singapore : Springer Singapore : Imprint: Springer, 2019.
• Έκδοση: 1st ed. 2019.
• Σειρά: SpringerBriefs in Computer Science,
• Θέματα: Software engineering.; Computer industry.; Software Engineering.; The Computer Industry.

 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. . 

 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.