{"title":"关于n检测模式集的优化","authors":"Yu Huang","doi":"10.1109/ISQED.2006.94","DOIUrl":null,"url":null,"abstract":"In this paper, we illustrate that the traditional N-detect ATPG is unoptimized in terms of the size of the generated pattern set. The optimization problem is formulated as a minimum covering problem. Integer linear programming (ILP) is applied to obtain an N-detection ATPG pattern set with the minimum number of patterns. A heuristic method is also proposed to obtain sub-optimal solutions efficiently. Experimental results demonstrate that by using the proposed method, the number of N-detection patterns can be reduced by about 18% for N=3 and about 13% for N=5 without compromising N-detection objective","PeriodicalId":138839,"journal":{"name":"7th International Symposium on Quality Electronic Design (ISQED'06)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"31","resultStr":"{\"title\":\"On N-detect pattern set optimization\",\"authors\":\"Yu Huang\",\"doi\":\"10.1109/ISQED.2006.94\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we illustrate that the traditional N-detect ATPG is unoptimized in terms of the size of the generated pattern set. The optimization problem is formulated as a minimum covering problem. Integer linear programming (ILP) is applied to obtain an N-detection ATPG pattern set with the minimum number of patterns. A heuristic method is also proposed to obtain sub-optimal solutions efficiently. Experimental results demonstrate that by using the proposed method, the number of N-detection patterns can be reduced by about 18% for N=3 and about 13% for N=5 without compromising N-detection objective\",\"PeriodicalId\":138839,\"journal\":{\"name\":\"7th International Symposium on Quality Electronic Design (ISQED'06)\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-03-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"31\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"7th International Symposium on Quality Electronic Design (ISQED'06)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISQED.2006.94\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"7th International Symposium on Quality Electronic Design (ISQED'06)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISQED.2006.94","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper, we illustrate that the traditional N-detect ATPG is unoptimized in terms of the size of the generated pattern set. The optimization problem is formulated as a minimum covering problem. Integer linear programming (ILP) is applied to obtain an N-detection ATPG pattern set with the minimum number of patterns. A heuristic method is also proposed to obtain sub-optimal solutions efficiently. Experimental results demonstrate that by using the proposed method, the number of N-detection patterns can be reduced by about 18% for N=3 and about 13% for N=5 without compromising N-detection objective