首页|期刊导航|哈尔滨工业大学学报（英文版）|Elevating Software Defect Prediction Performance Through an Optimized GA-DT and PSO-ACO Hybrid Approach

Elevating Software Defect Prediction Performance Through an Optimized GA-DT and PSO-ACO Hybrid Approach

Chennappan R Mathumathi E

哈尔滨工业大学学报（英文版）2025，Vol.32Issue(3)：66-74,9.

哈尔滨工业大学学报（英文版）2025，Vol.32Issue(3)：66-74,9.DOI:10.11916/j.issn.1005-9113.2024016

Elevating Software Defect Prediction Performance Through an Optimized GA-DT and PSO-ACO Hybrid Approach

Chennappan R ¹Mathumathi E¹

作者信息

1. Department of Computer Applications,Karpagam Academy of Higher Education,Tamil Nadu 641021,India
折叠

摘要

关键词

software quality/particle swarm optimization/ant colony optimization

Key words

software quality/particle swarm optimization/ant colony optimization

分类

计算机与自动化

引用本文复制引用

Chennappan R,Mathumathi E..Elevating Software Defect Prediction Performance Through an Optimized GA-DT and PSO-ACO Hybrid Approach[J].哈尔滨工业大学学报（英文版）,2025,32(3):66-74,9.

哈尔滨工业大学学报（英文版）

ISSN：1005-9113

访问量0

下载量0

段落导航