{"title":"A comparative analysis of ant colony optimization for its applications into software testing","authors":"Prashant Vats, Manju Mandot, A. Gosain","doi":"10.1109/CIPECH.2014.7019110","DOIUrl":null,"url":null,"abstract":"Ant Colony Optimization are metaheuristic algorithms that uses the search based algorithms as their base. It applies the natural phenomenon of finding the best possible path by the Ants that is covering the minimum distance from the food source to the ant colony, which will be followed by the rest of the ants, resulting into the optimized path. This phenomenon can be applied to provide optimized solutions to solve some complex computational problems. In this paper, we have carried out a review for the applications of the Ant colony Optimization algorithms in context to various level of the Software Testing, thus proving their worth in providing solutions to the various aspects of the Software Testing.","PeriodicalId":170027,"journal":{"name":"2014 Innovative Applications of Computational Intelligence on Power, Energy and Controls with their impact on Humanity (CIPECH)","volume":"192 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 Innovative Applications of Computational Intelligence on Power, Energy and Controls with their impact on Humanity (CIPECH)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIPECH.2014.7019110","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Ant Colony Optimization are metaheuristic algorithms that uses the search based algorithms as their base. It applies the natural phenomenon of finding the best possible path by the Ants that is covering the minimum distance from the food source to the ant colony, which will be followed by the rest of the ants, resulting into the optimized path. This phenomenon can be applied to provide optimized solutions to solve some complex computational problems. In this paper, we have carried out a review for the applications of the Ant colony Optimization algorithms in context to various level of the Software Testing, thus proving their worth in providing solutions to the various aspects of the Software Testing.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
