{"title":"VLSI Circuit Testing Using an Adaptive Optimization Model","authors":"Philip S. Yu, C. M. Krishna, Yann-Hang Lee","doi":"10.1145/37888.37948","DOIUrl":null,"url":null,"abstract":"The purpose of testing is to determine the correctness of the unit under test in come optimal way. One difficulty in meeting the optimality requirement is that the stochastic properties of the unit are usually unknown a priori. For instance, one might not know exactly the yield of a VLSI production line before one tests the chips made as a result. Given the probability of unit failure and the coverage of a test, the optimal test period is easy to obtain. However, the probability of failure is not usually known a priori. We therefore develop an optimal sequential testing strategy which estimates the production yield based on ongoing test results, and then use it to determine the optimal test period.","PeriodicalId":301552,"journal":{"name":"24th ACM/IEEE Design Automation Conference","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1987-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"24th ACM/IEEE Design Automation Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/37888.37948","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The purpose of testing is to determine the correctness of the unit under test in come optimal way. One difficulty in meeting the optimality requirement is that the stochastic properties of the unit are usually unknown a priori. For instance, one might not know exactly the yield of a VLSI production line before one tests the chips made as a result. Given the probability of unit failure and the coverage of a test, the optimal test period is easy to obtain. However, the probability of failure is not usually known a priori. We therefore develop an optimal sequential testing strategy which estimates the production yield based on ongoing test results, and then use it to determine the optimal test period.