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SEM review samples of bright field inspection results can be one or more orders of magnitude smaller than the defect count. Because of this, there is a risk of the sample set not adequately representing the actual yield risk of the defect population, especially if systematic defects are present. Furthermore, SEM review based on this method is often inefficient due to "SEM non-visual", nuisance defects, or dummy fill patterns dominating the sample Pareto. The quality of the defect Pareto can be significantly improved using design based binning, or DBB. DBB couples layout information from design data with the relative location of each detected defect. This enables binning by key features of the pattern geometry surrounding the defect, thus providing more information about the yield risk of that defect. This paper describes the various components of DBB technology, and shows examples of improving SEM review efficiency by employing DBB to effectively bin out nuisance and other systematic defect types.