{"title":"基于改进自适应粒子群优化器的软件测试数据自动生成","authors":"Xiao-mei Zhu, Xian-feng Yang","doi":"10.1109/ICCIS.2010.321","DOIUrl":null,"url":null,"abstract":"To advance efficiency of software test data generation automatically, based on traditional particle swarm optimizer (PSO) algorithm, we put forward an improved algorithm (APSO) in which inertia weight is adjusted according to the fitness value of particle. Experiment simulation result shows that APSO not only has better performance than immune genetic algorithm (IGA) but also better than PSO, and has broad application prospect in software test.","PeriodicalId":227848,"journal":{"name":"2010 International Conference on Computational and Information Sciences","volume":"132 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":"{\"title\":\"Software Test Data Generation Automatically Based on Improved Adaptive Particle Swarm Optimizer\",\"authors\":\"Xiao-mei Zhu, Xian-feng Yang\",\"doi\":\"10.1109/ICCIS.2010.321\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To advance efficiency of software test data generation automatically, based on traditional particle swarm optimizer (PSO) algorithm, we put forward an improved algorithm (APSO) in which inertia weight is adjusted according to the fitness value of particle. Experiment simulation result shows that APSO not only has better performance than immune genetic algorithm (IGA) but also better than PSO, and has broad application prospect in software test.\",\"PeriodicalId\":227848,\"journal\":{\"name\":\"2010 International Conference on Computational and Information Sciences\",\"volume\":\"132 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-12-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 International Conference on Computational and Information Sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCIS.2010.321\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Conference on Computational and Information Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCIS.2010.321","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Software Test Data Generation Automatically Based on Improved Adaptive Particle Swarm Optimizer
To advance efficiency of software test data generation automatically, based on traditional particle swarm optimizer (PSO) algorithm, we put forward an improved algorithm (APSO) in which inertia weight is adjusted according to the fitness value of particle. Experiment simulation result shows that APSO not only has better performance than immune genetic algorithm (IGA) but also better than PSO, and has broad application prospect in software test.
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