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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Nelson, J.E. Wing Chiu Tam Blanton, R.D. |
| Copyright Year | 2010 |
| Description | Author affiliation: Center for Silicon System Implementation, Carnegie Mellon University, Pittsburgh, PA 15213, USA (Nelson, J.E.; Wing Chiu Tam; Blanton, R.D.) |
| Abstract | A technique is proposed to automatically predict whether a failing chip has a bridge defect. Logic diagnosis is performed using scan test results to identify candidate nets. Several relevant features of the test data are measured for net pairs that consist of the diagnosis candidates and other nets in close physical proximity. Based on these features, rules are constructed to identify defects that fully exhibit classic bridge behaviors, while the remaining chips are classified using a forest of decision trees. Results indicate that a population of chips failing due to bridges can indeed be extracted with very high accuracy. Finally, the method correctly classifies 41 commercially-fabricated chips that underwent PFA. |
| Starting Page | 1 |
| Ending Page | 10 |
| File Size | 698585 |
| Page Count | 10 |
| File Format | |
| ISBN | 9781424472062 |
| ISSN | 10893539 |
| e-ISBN | 9781424472079 |
| DOI | 10.1109/TEST.2010.5699231 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-11-02 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Bridges Logic gates Bridge circuits Barium Semiconductor device measurement Circuit faults Layout |
| Content Type | Text |
| Resource Type | Article |
| Subject | Applied Mathematics Electrical and Electronic Engineering |
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