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portada Intelligent Software Defect Prediction
Type
Physical Book
Author
Publisher
Language
English
Pages
205
Format
Hardcover
Dimensions
23.4x15.6x1.4 cm
Weight
0.49 kg.
ISBN13
9789819928415
Categories

Intelligent Software Defect Prediction

Baowen Xu (Author) · Xiao-Yuan Jing (Author) · Haowen Chen (Author) · Springer · Hardcover

Intelligent Software Defect Prediction - Jing, Xiao-Yuan ; Chen, Haowen ; Xu, Baowen

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Synopsis "Intelligent Software Defect Prediction"

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 thesetheoretical 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.

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