Yen-An Chen, Chun-Yao Wang, Ching-Yi Huang, Hsiu-Yi Lin
{"title":"一个寄存器传输级可测试性分析器","authors":"Yen-An Chen, Chun-Yao Wang, Ching-Yi Huang, Hsiu-Yi Lin","doi":"10.1109/SOCC.2011.6085107","DOIUrl":null,"url":null,"abstract":"This paper presents a statistic-based method to estimate the testability of a design at Register-Transfer Level. This testability estimation technique is composed of a new proposed high-level design representation and a Monte Carlo simulation which exploits a statistic model to bound the error rate and confidence level of simulation results. The experimental results show that the proposed method can efficiently report more than 60% hard-to-test points of an RL design on average prior to the synthesis task.","PeriodicalId":365422,"journal":{"name":"2011 IEEE International SOC Conference","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2011-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A register-transfer level testability analyzer\",\"authors\":\"Yen-An Chen, Chun-Yao Wang, Ching-Yi Huang, Hsiu-Yi Lin\",\"doi\":\"10.1109/SOCC.2011.6085107\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a statistic-based method to estimate the testability of a design at Register-Transfer Level. This testability estimation technique is composed of a new proposed high-level design representation and a Monte Carlo simulation which exploits a statistic model to bound the error rate and confidence level of simulation results. The experimental results show that the proposed method can efficiently report more than 60% hard-to-test points of an RL design on average prior to the synthesis task.\",\"PeriodicalId\":365422,\"journal\":{\"name\":\"2011 IEEE International SOC Conference\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-11-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 IEEE International SOC Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SOCC.2011.6085107\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE International SOC Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SOCC.2011.6085107","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper presents a statistic-based method to estimate the testability of a design at Register-Transfer Level. This testability estimation technique is composed of a new proposed high-level design representation and a Monte Carlo simulation which exploits a statistic model to bound the error rate and confidence level of simulation results. The experimental results show that the proposed method can efficiently report more than 60% hard-to-test points of an RL design on average prior to the synthesis task.
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