Wu M.-TKuo C.-SLi J.C.-MNigh CBhargava G.CHIEN-MO LI2022-04-252022-04-25202110893539https://www.scopus.com/inward/record.uri?eid=2-s2.0-85123058895&doi=10.1109%2fITC50571.2021.00034&partnerID=40&md5=1ca0edfd76a7cd7a7f08088a935a9bd0https://scholars.lib.ntu.edu.tw/handle/123456789/607010Volume diagnosis and debug play a key role in identifying systematic test failures caused by manufacturing defectivity, design marginalities, and test overkill. However, diagnosis tools often suffer from poor diagnosis resolution. In this paper, we propose techniques to improve diagnosis resolution by test failure clustering and reorganization. The effectiveness of our techniques is demonstrated on two industrial designs in cutting-edge process nodes and verified by targeted analysis and testing. The number of suspects is reduced by 3.1x and 575.2x on average. The proposed techniques can be implemented using existing commercial diagnosis tools with runtime overheads below 1%. ? 2021 IEEE.diagnosis resolutionsystematic defectvolume diagnosisClusteringsDefectivityDesign marginalitiesDiagnose resolutionDiagnosis toolsReorganisationSystematic defectsSystematic testTest failureVolume diagnosisDefectsconference paper10.1109/ITC50571.2021.000342-s2.0-85123058895