A Deterministic-Statistical Multiple-Defect Diagnosis Methodology
I presented this paper at the VLSI Test Symposium (VTS), 2020.
Authors: Soumya Mittal, Shawn Blanton
Summary: This paper describes a three-phase, physically-aware diagnosis methodology called MD-LearnX to effectively diagnose multiple defects, and in turn, aid in accelerating the design and process development. The first phase identifies a defect that resembles traditional fault models. The second and the third phases utilize the X-fault model and machine learning to identify correct candidates.