基于改进鲸鱼优化算法的测试用例自动生成方法

Jing Wang, Weidong Zhao
{"title":"基于改进鲸鱼优化算法的测试用例自动生成方法","authors":"Jing Wang, Weidong Zhao","doi":"10.1145/3461598.3461600","DOIUrl":null,"url":null,"abstract":"∗In view of the slow convergence speed and parameter control of the existing heuristic algorithm in the automatic test case generation, this paper proposed to apply the whale optimization algorithm(Abbreviation: WOA) to the automatic test case generation, and used chaos strategy to improve WOA, and In order to solve the problem that WOA initialization is not uniform and easy to fall into local optimal solution, uses chaos initialization was used instead of random algorithm to initialize the population and solved the problem of uneven distribution of particles, consequently when the optimal value fell into the local optimal solution, the chaos disturbance operation was carried out on the optimal value. Based on this, an automatic test case generation method based on improved whale algorithm was proposed. This method aimed at one path at a time and used the improved whale optimization algorithm to optimize the population and find the optimal value.","PeriodicalId":408426,"journal":{"name":"Proceedings of the 2021 5th International Conference on Intelligent Systems, Metaheuristics & Swarm Intelligence","volume":"224 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Automatic Test Case Generation Method Based on Improved Whale Optimization Algorithm\",\"authors\":\"Jing Wang, Weidong Zhao\",\"doi\":\"10.1145/3461598.3461600\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"∗In view of the slow convergence speed and parameter control of the existing heuristic algorithm in the automatic test case generation, this paper proposed to apply the whale optimization algorithm(Abbreviation: WOA) to the automatic test case generation, and used chaos strategy to improve WOA, and In order to solve the problem that WOA initialization is not uniform and easy to fall into local optimal solution, uses chaos initialization was used instead of random algorithm to initialize the population and solved the problem of uneven distribution of particles, consequently when the optimal value fell into the local optimal solution, the chaos disturbance operation was carried out on the optimal value. Based on this, an automatic test case generation method based on improved whale algorithm was proposed. This method aimed at one path at a time and used the improved whale optimization algorithm to optimize the population and find the optimal value.\",\"PeriodicalId\":408426,\"journal\":{\"name\":\"Proceedings of the 2021 5th International Conference on Intelligent Systems, Metaheuristics & Swarm Intelligence\",\"volume\":\"224 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-04-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2021 5th International Conference on Intelligent Systems, Metaheuristics & Swarm Intelligence\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3461598.3461600\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2021 5th International Conference on Intelligent Systems, Metaheuristics & Swarm Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3461598.3461600","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

鉴于现有启发式算法在自动生成测试用例时收敛速度慢、参数控制不佳,本文提出采用鲸鱼优化算法(简称:whale optimization algorithm)。WOA)自动生成测试用例,并使用混沌策略改善WOA,为了解决这个问题,WOA初始化不均匀,容易陷入局部最优解,使用混沌初始化是用来代替随机算法初始化人口和解决了粒子分布不均的问题,因此当最优值落入局部最优解,进行混沌扰动操作的最优值。在此基础上,提出了一种基于改进鲸鱼算法的测试用例自动生成方法。该方法以每次一条路径为目标,采用改进的鲸鱼优化算法对种群进行优化,找到最优值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatic Test Case Generation Method Based on Improved Whale Optimization Algorithm
∗In view of the slow convergence speed and parameter control of the existing heuristic algorithm in the automatic test case generation, this paper proposed to apply the whale optimization algorithm(Abbreviation: WOA) to the automatic test case generation, and used chaos strategy to improve WOA, and In order to solve the problem that WOA initialization is not uniform and easy to fall into local optimal solution, uses chaos initialization was used instead of random algorithm to initialize the population and solved the problem of uneven distribution of particles, consequently when the optimal value fell into the local optimal solution, the chaos disturbance operation was carried out on the optimal value. Based on this, an automatic test case generation method based on improved whale algorithm was proposed. This method aimed at one path at a time and used the improved whale optimization algorithm to optimize the population and find the optimal value.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信