基于主成分分析的任务规划系统软件缺陷预测方法  

Research on Mission Planning Software Defect Prediction Algorithm Based on Principal Components Analysis

作　　者：孙文川[1] 庄锦程 吴延军[1] 刘磊 SUN Wenchuan;ZHUANG Jincheng;WU Yanjun;LIU Lei(No.91550 Troops of PLA,Dalian 116023)

机构地区：[1]91550部队,大连116023

出　　处：《舰船电子工程》2025年第1期158-162,共5页Ship Electronic Engineering

摘　　要：软件缺陷预测技术可以用于对软件功能性能故障风险的预测,对于对指导软件测试过程、提升软件质量有着重要的意义。以任务规划系统软件研制评测过程中暴露的设计缺陷为先验信息。对软件缺陷对应功能模块及其影响等级进行分类,采用主成分分析方法对造成软件缺陷的主要功能模块进行定位,为明确任务规划系统软件功能性能测试重点提供指导。Software defect prediction technology can be used to predict the existence of software defects and to direct the soft⁃ware testing process.It is very important to improve the software performance and quality.Based on the fault information of software testing accumulated during development,the software functional modules and fault impact level are classified.Then the main reason of software defect modules are found though principal component analysis(PCA),which can provide guidance for the software test⁃ing.

关 键 词：任务规划系统 软件缺陷 主成分分析 缺陷预测 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]