摘要
IncreasingICdensitiesnecessitatediagnosismethodologieswithenhanceddefectlocatingcapabilities.YetthecomputationaleffortexpendedinextractingdiagnosticinformationandthestringentstoragerequirementsconstitutemajorconcernsduetothetremendousnumberoffaultsintypicalICs.Inthispaper,weproposeanRT-leveldiagnosismethodologycapableofrespondingtothesechallenges.Intheproposedscheme,diagnosticinformationiscomputedonagroupedfaulteffectbasis,enhancingboththestorageandthecomputationalaspects.Thefaulteffectgroupingcriteriaareidentifiedbasedonamodulestructureanalysis,improvingthepropagationabilityofthediagnosticinformationthroughRTmodules.Experimentalresultsshowthattheproposedmethodologyprovidessuperiorspeed-upsandsignificantdiagnosticinformationcompressionatnosacrificeindiagnosticresolution,comparedtotheexistinggate-leveldiagnosisapproaches.
出版日期
2005年02月12日（中国期刊网平台首次上网日期，不代表论文的发表时间）
