Biometric Image Discrimination Technologies addresses highly relevant issues to many fundamental concerns of both researchers and practitioners of biometric image discrimination (BID) in biometric applications. This book describes the basic concepts necessary for a good understanding of BID and answers some important introductory questions about BID. ""Biometric Image Discrimination Technologies"" covers the theories which are the foundations of basic BID technologies, while developing new algorithms which are verified to be more effective in biometrics authentication. This book will assist students new to the field and will also be useful to senior researchers in this area.

With the increasing complexity of and dependency on software, software products may suffer from low quality, high prices, be hard to maintain, etc. Software defects usually produce incorrect or unexpected results and behaviors. Accordingly, software defect prediction (SDP) is one of the most active research fields in software engineering and plays an important role in software quality assurance. Based on the results of SDP analyses, developers can subsequently conduct defect localization and repair on the basis of reasonable resource allocation, which helps to reduce their maintenance costs. This book offers a comprehensive picture of the current state of SDP research. More specifically, it introduces a range of machine-learning-based SDP approaches proposed for different scenarios (i.e., WPDP, CPDP, and HDP). In addition, the book shares in-depth insights into current SDP approaches’ performance and lessons learned for future SDP research efforts. We believe these theoretical analyses and emerging challenges will be of considerable interest to all researchers, graduate students, and practitioners who want to gain deeper insights into and/or find new research directions in SDP. It offers a comprehensive introduction to the current state of SDP and detailed descriptions of representative SDP approaches.