Improving with Hybrid Feature Selection in Software Defect Prediction

Improving with Hybrid Feature Selection in Software Defect Prediction

Software defect prediction (SDP) is used to identify defects in software modules that can be a challenge in software development. This research focuses on the problems that occur in Particle Swarm Optimization (PSO), such as the problem of noisy attributes, high-dimensional data, and premature conve...

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Bibliographic Details
Main Authors: Muhammad Yoga Adha Pratama, Rudy Herteno, Mohammad Reza Faisal, Radityo Adi Nugroho, Friska Abadi
Format: Article
Language:English
Published: Department of Informatics, UIN Sunan Gunung Djati Bandung 2024-04-01
Series:JOIN: Jurnal Online Informatika
Subjects:
software defect prediction
particle swarm optimization
feature selection
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naive bayes
Online Access:https://join.if.uinsgd.ac.id/index.php/join/article/view/1307
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