{"title":"用统计时序模型诊断时延缺陷","authors":"Angela Krstic, Li-C. Wang, K. Cheng, J. Liou","doi":"10.1109/VTEST.2003.1197672","DOIUrl":null,"url":null,"abstract":"In this paper, we study the problem of delay defect diagnosis based on statistical timing models. We propose a diagnosis algorithm that can effectively utilize statistical timing information based upon single defect assumption. We evaluate its performance and its applicability to single as well as multiple defect scenarios via statistical defect injection and simulation. With a statistical timing analysis framework developed in the past, we demonstrate the new concept in statistical delay defect diagnosis, and discuss experimental results using benchmark circuits.","PeriodicalId":292996,"journal":{"name":"Proceedings. 21st VLSI Test Symposium, 2003.","volume":"86 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"23","resultStr":"{\"title\":\"Diagnosis of delay defects using statistical timing models\",\"authors\":\"Angela Krstic, Li-C. Wang, K. Cheng, J. Liou\",\"doi\":\"10.1109/VTEST.2003.1197672\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we study the problem of delay defect diagnosis based on statistical timing models. We propose a diagnosis algorithm that can effectively utilize statistical timing information based upon single defect assumption. We evaluate its performance and its applicability to single as well as multiple defect scenarios via statistical defect injection and simulation. With a statistical timing analysis framework developed in the past, we demonstrate the new concept in statistical delay defect diagnosis, and discuss experimental results using benchmark circuits.\",\"PeriodicalId\":292996,\"journal\":{\"name\":\"Proceedings. 21st VLSI Test Symposium, 2003.\",\"volume\":\"86 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2003-04-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"23\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings. 21st VLSI Test Symposium, 2003.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/VTEST.2003.1197672\",\"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. 21st VLSI Test Symposium, 2003.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VTEST.2003.1197672","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Diagnosis of delay defects using statistical timing models
In this paper, we study the problem of delay defect diagnosis based on statistical timing models. We propose a diagnosis algorithm that can effectively utilize statistical timing information based upon single defect assumption. We evaluate its performance and its applicability to single as well as multiple defect scenarios via statistical defect injection and simulation. With a statistical timing analysis framework developed in the past, we demonstrate the new concept in statistical delay defect diagnosis, and discuss experimental results using benchmark circuits.