{"title":"从 CTL 自动生成功能覆盖模型","authors":"Shireesh Verma, I. Harris, Kiran Ramineni","doi":"10.1109/HLDVT.2007.4392806","DOIUrl":null,"url":null,"abstract":"Functional coverage models which measure the sufficiency of test stimuli are essential to the verification process. A key source of difficulty in their deployment emanates from the manual and imprecise nature of their development process and the lack of a sound measure of their quality. A functional coverage model can be considered complete only if it accurately reflects the behavior of the Design under Verification (DUV) as described in the specification. We present a method to automatically generate coverage models from a formal CTL description of design properties. Experimental results show that the functional coverage models generated using our technique correlate well with the detection of randomly injected errors into a design.","PeriodicalId":339324,"journal":{"name":"2007 IEEE International High Level Design Validation and Test Workshop","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Automatic generation of functional coverage models from CTL\",\"authors\":\"Shireesh Verma, I. Harris, Kiran Ramineni\",\"doi\":\"10.1109/HLDVT.2007.4392806\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Functional coverage models which measure the sufficiency of test stimuli are essential to the verification process. A key source of difficulty in their deployment emanates from the manual and imprecise nature of their development process and the lack of a sound measure of their quality. A functional coverage model can be considered complete only if it accurately reflects the behavior of the Design under Verification (DUV) as described in the specification. We present a method to automatically generate coverage models from a formal CTL description of design properties. Experimental results show that the functional coverage models generated using our technique correlate well with the detection of randomly injected errors into a design.\",\"PeriodicalId\":339324,\"journal\":{\"name\":\"2007 IEEE International High Level Design Validation and Test Workshop\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-11-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 IEEE International High Level Design Validation and Test Workshop\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HLDVT.2007.4392806\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 IEEE International High Level Design Validation and Test Workshop","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HLDVT.2007.4392806","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Automatic generation of functional coverage models from CTL
Functional coverage models which measure the sufficiency of test stimuli are essential to the verification process. A key source of difficulty in their deployment emanates from the manual and imprecise nature of their development process and the lack of a sound measure of their quality. A functional coverage model can be considered complete only if it accurately reflects the behavior of the Design under Verification (DUV) as described in the specification. We present a method to automatically generate coverage models from a formal CTL description of design properties. Experimental results show that the functional coverage models generated using our technique correlate well with the detection of randomly injected errors into a design.