{"title":"使用Voronoi图进行高效和有效的随机测试","authors":"T. Chen, Robert G. Merkel","doi":"10.1109/ASWEC.2006.25","DOIUrl":null,"url":null,"abstract":"Adaptive random testing (ART) is a method for improving the fault-finding effectiveness of random testing. Fixed-size candidate set ART is the most studied variant of this approach. However, existing implementations of FSCS-ART have had substantial selection overhead, with n test cases requiring O(n/sup 2/) time to generate. We describe the use of a geometric data structure known as the Voronoi diagram to reduce this overhead to no worse than O(n/spl radic/n) and, with further optimization, O(nlogn). We demonstrate experimentally that practical improvements in selection overhead can be gained using this improved implementation.","PeriodicalId":285684,"journal":{"name":"Australian Software Engineering Conference (ASWEC'06)","volume":"28 1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"22","resultStr":"{\"title\":\"Efficient and effective random testing using the Voronoi diagram\",\"authors\":\"T. Chen, Robert G. Merkel\",\"doi\":\"10.1109/ASWEC.2006.25\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Adaptive random testing (ART) is a method for improving the fault-finding effectiveness of random testing. Fixed-size candidate set ART is the most studied variant of this approach. However, existing implementations of FSCS-ART have had substantial selection overhead, with n test cases requiring O(n/sup 2/) time to generate. We describe the use of a geometric data structure known as the Voronoi diagram to reduce this overhead to no worse than O(n/spl radic/n) and, with further optimization, O(nlogn). We demonstrate experimentally that practical improvements in selection overhead can be gained using this improved implementation.\",\"PeriodicalId\":285684,\"journal\":{\"name\":\"Australian Software Engineering Conference (ASWEC'06)\",\"volume\":\"28 1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-04-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"22\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Australian Software Engineering Conference (ASWEC'06)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ASWEC.2006.25\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Australian Software Engineering Conference (ASWEC'06)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASWEC.2006.25","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Efficient and effective random testing using the Voronoi diagram
Adaptive random testing (ART) is a method for improving the fault-finding effectiveness of random testing. Fixed-size candidate set ART is the most studied variant of this approach. However, existing implementations of FSCS-ART have had substantial selection overhead, with n test cases requiring O(n/sup 2/) time to generate. We describe the use of a geometric data structure known as the Voronoi diagram to reduce this overhead to no worse than O(n/spl radic/n) and, with further optimization, O(nlogn). We demonstrate experimentally that practical improvements in selection overhead can be gained using this improved implementation.