{"title":"大数据与测试","authors":"A. Gattiker","doi":"10.1109/TEST.2014.7035327","DOIUrl":null,"url":null,"abstract":"Big data is now a ubiquitous part of life — both in test and in many other areas. This talk discusses some of the big problems facing us in test and looks at analogous problems outside of the test domain. It aims to both step back and abstract test-specific problems into general problems and point out similarities and contrasts between test and non-test problems. It also highlights interesting aspects of applying some test-like techniques in non-test settings such as cognitive computing.","PeriodicalId":6403,"journal":{"name":"2007 IEEE International Test Conference","volume":"66 1","pages":"1"},"PeriodicalIF":0.0000,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Big data and test\",\"authors\":\"A. Gattiker\",\"doi\":\"10.1109/TEST.2014.7035327\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Big data is now a ubiquitous part of life — both in test and in many other areas. This talk discusses some of the big problems facing us in test and looks at analogous problems outside of the test domain. It aims to both step back and abstract test-specific problems into general problems and point out similarities and contrasts between test and non-test problems. It also highlights interesting aspects of applying some test-like techniques in non-test settings such as cognitive computing.\",\"PeriodicalId\":6403,\"journal\":{\"name\":\"2007 IEEE International Test Conference\",\"volume\":\"66 1\",\"pages\":\"1\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 IEEE International Test Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TEST.2014.7035327\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 IEEE International Test Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TEST.2014.7035327","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Big data is now a ubiquitous part of life — both in test and in many other areas. This talk discusses some of the big problems facing us in test and looks at analogous problems outside of the test domain. It aims to both step back and abstract test-specific problems into general problems and point out similarities and contrasts between test and non-test problems. It also highlights interesting aspects of applying some test-like techniques in non-test settings such as cognitive computing.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
