A Fine-Grained Defect Prediction Method Based on Drift-Immune Graph Neural Networks

The primary goal of software defect prediction (SDP) is to pinpoint code modules that are likely to contain defects, thereby enabling software quality assurance teams to strategically allocate their resources and manpower. Wi... | Find, read and cite all the research you need on Tech Science Press

Authors

Publication Details

Journal
Computers, materials & continua/Computers, materials & continua (Print)
Published
2024-12-11
DOI
https://doi.org/10.32604/cmc.2024.057697
Citations
1
Primary Topic
Industrial Vision Systems and Defect Detection
Type
article
Field-Weighted Citation Impact
0.35

Funders

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article

A Fine-Grained Defect Prediction Method Based on Drift-Immune Graph Neural Networks

Guangdong Zeng, Fengyu Yang, Fa Zhong, Xiaohui Wei
1 citations
Computers, materials & continua/Computers, materials & continua (Print)
Industrial Vision Systems and Defect Detection
0.35
article

A Fine-Grained Defect Prediction Method Based on Drift-Immune Graph Neural Networks

Guangdong Zeng, Fengyu Yang, Fa Zhong, Xiaohui Wei
article en
1 citations

Abstract

The primary goal of software defect prediction (SDP) is to pinpoint code modules that are likely to contain defects, thereby enabling software quality assurance teams to strategically allocate their resources and manpower. Wi... | Find, read and cite all the research you need on Tech Science Press

Computers, materials & continua/Computers, materials & continua (Print)Vol. 82(2)
National Natural Science Foundation of China
Zero hunger
Openalex Percentile: Top 33%
Industrial Vision Systems and Defect Detection
0.35
DOIOpen Access PDFOpenAlex
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A Fine-Grained Defect Prediction Method Based on Drift-Immune Graph Neural Networks — Guangdong Zeng, Fengyu Yang, et al. · Computers, materials & continua/Computers, materials & continua (Print) (2024) | TGRS Research Map | TGRS