{"title":"当优化的n -检测测试集有偏差时:细胞感知型故障和n -检测卡在ATPG的研究","authors":"Fanchen Zhang, Micah Thornton, Jennifer Dworak","doi":"10.1109/NATW.2014.15","DOIUrl":null,"url":null,"abstract":"Cell-aware faults have previously been proposed to more effectively detect defects within gates. At the same time, n-detect test sets that provide multiple detections of each stuck-at fault are often used to maximize the detection of unmodeled defects. However, n-detect test sets are often not particularly effective at fortuitously detecting all untargeted cell-aware faults. In this paper, we investigate the effectiveness of different types of n-detect ATPG test sets for efficiently detecting difficult cell-aware-type faults and explain why optimizing test sets for n- detect using stuck-at faults while still keeping pattern counts low can actually bias those test sets against the detection of some cell-aware type faults. We then investigate the addition of cell-aware top-off patterns for cell-aware-type faults that are shown to be functionally relevant through good state simulation, allowing such faults to be prioritized when testing resources are limited.","PeriodicalId":283155,"journal":{"name":"2014 IEEE 23rd North Atlantic Test Workshop","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"When Optimized N-Detect Test Sets are Biased: An Investigation of Cell-Aware-Type Faults and N-Detect Stuck-At ATPG\",\"authors\":\"Fanchen Zhang, Micah Thornton, Jennifer Dworak\",\"doi\":\"10.1109/NATW.2014.15\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Cell-aware faults have previously been proposed to more effectively detect defects within gates. At the same time, n-detect test sets that provide multiple detections of each stuck-at fault are often used to maximize the detection of unmodeled defects. However, n-detect test sets are often not particularly effective at fortuitously detecting all untargeted cell-aware faults. In this paper, we investigate the effectiveness of different types of n-detect ATPG test sets for efficiently detecting difficult cell-aware-type faults and explain why optimizing test sets for n- detect using stuck-at faults while still keeping pattern counts low can actually bias those test sets against the detection of some cell-aware type faults. We then investigate the addition of cell-aware top-off patterns for cell-aware-type faults that are shown to be functionally relevant through good state simulation, allowing such faults to be prioritized when testing resources are limited.\",\"PeriodicalId\":283155,\"journal\":{\"name\":\"2014 IEEE 23rd North Atlantic Test Workshop\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-05-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE 23rd North Atlantic Test Workshop\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NATW.2014.15\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE 23rd North Atlantic Test Workshop","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NATW.2014.15","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
When Optimized N-Detect Test Sets are Biased: An Investigation of Cell-Aware-Type Faults and N-Detect Stuck-At ATPG
Cell-aware faults have previously been proposed to more effectively detect defects within gates. At the same time, n-detect test sets that provide multiple detections of each stuck-at fault are often used to maximize the detection of unmodeled defects. However, n-detect test sets are often not particularly effective at fortuitously detecting all untargeted cell-aware faults. In this paper, we investigate the effectiveness of different types of n-detect ATPG test sets for efficiently detecting difficult cell-aware-type faults and explain why optimizing test sets for n- detect using stuck-at faults while still keeping pattern counts low can actually bias those test sets against the detection of some cell-aware type faults. We then investigate the addition of cell-aware top-off patterns for cell-aware-type faults that are shown to be functionally relevant through good state simulation, allowing such faults to be prioritized when testing resources are limited.