计算机应用与软件2025，Vol.42Issue(4)：13-20,8.DOI:10.3969/j.issn.1000-386x.2025.04.003
一种事前可解释的即时软件缺陷预测方法
AN ANTE-HOC INTERPRETABLE METHOD FOR JUST-IN-TIME SOFTWARE DEFECT PREDICTION
摘要
Abstract
In order to solve the problem that it is difficult to explain the prediction results of just-in-time software defects,based on the improved model of polynomial neural network,an ante-hoc interpretable just-in-time software defect prediction method is proposed.This method formalized the causal relationship between code metric elements and prediction results,and outputted it as a K-G polynomial function.The standardized regression coefficient was used to measure the importance of metric elements to analyze the causes of the defects.The experimental results show that on the premise that the average prediction accuracy reaches 0.797,it has good interpretability at the same time.关键词
多项式神经网络/即时软件缺陷预测/事前可解释性/形式化Key words
Polynomial neural networks/Just-in-time software defect prediction/Ante-hoc interpretability/Formalization分类
计算机与自动化引用本文复制引用
林杨,王炜..一种事前可解释的即时软件缺陷预测方法[J].计算机应用与软件,2025,42(4):13-20,8.基金项目
云南省中青年学术和技术带头人后备人选项目(2019HB104). （2019HB104）
