Enhanced Binary Moth Flame Optimization as a Feature Selection Algorithm to Predict Software Fault Prediction

Enhanced Binary Moth Flame Optimization as a Feature Selection Algorithm to Predict Software Fault Prediction

Software fault prediction (SFP) is a complex problem that meets developers in the software development life cycle. Collecting data from real software projects, either while the development life cycle or after lunch the product, is not a simple task, and the collected data may suffer from imbalance d...

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Bibliographic Details
Main Authors: Iyad Tumar, Yousef Hassouneh, Hamza Turabieh, Thaer Thaher
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Software fault prediction
feature selection
binary moth flame optimization
adaptive synthetic sampling
classification
Online Access:https://ieeexplore.ieee.org/document/8950456/

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