Software Defect Prediction Using Heterogeneous Ensemble Classification Based on Segmented Patterns

Software Defect Prediction Using Heterogeneous Ensemble Classification Based on Segmented Patterns

Software defect prediction is a promising approach aiming to improve software quality and testing efficiency by providing timely identification of defect-prone software modules before the actual testing process begins. These prediction results help software developers to effectively allocate their l...

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Bibliographic Details
Main Authors: Hamad Alsawalqah, Neveen Hijazi, Mohammed Eshtay, Hossam Faris, Ahmed Al Radaideh, Ibrahim Aljarah, Yazan Alshamaileh
Format: Article
Language:English
Published: MDPI AG 2020-03-01
Series:Applied Sciences
Subjects:
software defect prediction
ensembles
clustering
segmentation
classification
Online Access:https://www.mdpi.com/2076-3417/10/5/1745

Internet

https://www.mdpi.com/2076-3417/10/5/1745

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