统计与决策2024，Vol.40Issue(12)：41-45,5.DOI:10.13546/j.cnki.tjyjc.2024.12.007
一种基于层接近度和分支距离函数的最优个体选择算法
An Optimal Individual Selection Algorithm Based on Layer Proximity and Branch Distance Function
安迎建1
作者信息
- 1. 上海建设管理职业技术学院 智能建筑工程学院,上海 201702
- 折叠
摘要
Abstract
Aiming at the problems existing in the evaluation and selection of the optimal individual at present,and based on the comprehensive analysis of the characteristics of layer proximity and branch distance function,this paper proposes a test case evaluation algorithm with layer proximity and branch distance function combined.The basic idea of this algorithm is to select the individuals with high proximity between the actual execution path and the target path,and then select the individuals with the smallest branch distance in these individuals,so as to obtain the individuals with the best navigation ability.Experiment results show that the proposed algorithm can be used to quickly find test cases,especially for the test case generation of multi-layer nest-ed programs.关键词
层接近度函数/分支距离函数/启发式方法/最优个体生成算法Key words
layer proximity function/branch distance function/heuristic method/optimal individual generation algorithm分类
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安迎建..一种基于层接近度和分支距离函数的最优个体选择算法[J].统计与决策,2024,40(12):41-45,5.
