摘要
缺陷校正可以保证复杂软件源代码的稳定运行,为了提高源代码缺陷校正性能,提出基于人工智能的复杂软件源代码缺陷校正方法。利用语法分析器,建立源代码语言的文本分析树,通过定义源代码语言文本中间转换执行流的延续,分析复杂软件源代码语义。引入人工智能领域的计算机科学技术,计算复杂软件的后验概率,利用模糊矩阵计算源代码缺陷的贴近度,验证复杂软件源代码的程序标注。根据复杂软件源代码的缺陷密度,利用人工智能聚类算法预处理源代码缺陷特征,依据人工智能的数据依赖性分析理论,提取出源代码分区的依赖关系,结合代码转换,实现复杂软件源代码缺陷的校正。仿真结果表明,所研究方法可以提高复杂软件程序的运行效率,并将源代码缺陷校正准确率和召回率提高至90%以上。
Defect correction can ensure the stable operation of source code in complex software.In order to improve the correction performance,a method of correcting the defects of complex software source code was put forward based on artificial intelligence.Firstly,the parser was used to build a text analysis tree of the source code language,and then the semantics of source code in complex software was analyzed by defining the continuation of the execution flow of intermediate conversion of source code language text.Secondly,computer science and technology in the field of artificial intelligence were introduced to calculate the posterior probability of complex software.Meanwhile,the fuzzy matrix was used to calculate the close degree of source code defects,and thus to verify the program labeling of source code.According to the defect density of source code,the characteristics of source code defects were preprocessed by using AI clustering algorithm.Based on the data dependency analysis theory of artificial intelligence,the dependency relationship of source code partition was extracted.Finally,the correction of source code defects in complex software was realized by code conversion.Simulation results show that the proposed method can improve the running efficiency of complex software programs,and improve the correction accuracy and recall of source code to 90%.
作者
刘楷正
乔阳阳
董涛
王丽娟
LIU Kai-zheng;QIAO Yang-yang;DONG Tao;WANG Li-juan(School of Information Engineering,Zhengzhou Technology and Business University,Zhengzhou Henan 451400,China;School of Electric Power,North China University of Water Resources and Electric Power,Zhengzhou Henan 450046,China)
出处
《计算机仿真》
北大核心
2023年第8期389-392,407,共5页
Computer Simulation
基金
河南科技厅2022年度科技攻关项目(222102210122)
教育部高校学生司2022年度供需对接就业育人项目(20220105070)。
关键词
语义分析
人工智能
缺陷校正
源代码
复杂软件
程序标注
Semantic analysis
Artificial intelligence
Correction of defects
Source code
Complex software
Program annotation
