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

作　　者：林杨 王炜[1] Lin Yang;Wang Wei(School of Software,Yunnan University,Kunming 650504,Yunnan,China)

机构地区：[1]云南大学软件学院,云南昆明650504

出　　处：《计算机应用与软件》2025年第4期13-20,共8页Computer Applications and Software

基　　金：云南省中青年学术和技术带头人后备人选项目(2019HB104)。

摘　　要：为解决即时软件缺陷预测结果难以解释的问题,基于多项式神经网络的改进模型,提出一种事前可解释的即时软件缺陷预测方法,通过将代码度量元与预测结果之间的因果关系形式化输出为K-G多项式的复合函数,使用标准化回归系数来衡量复合函数中度量元的重要性,分析影响缺陷产生的原因。实验结果表明在平均预测准确率达到0.797的前提下,该方法还具有较好的可解释性。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 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]