Gdsxor comparsion with machine learning to classify changes

A system, comprising:

• a memory;
• and
• a processor coupled to the memory and configured to classify changes between graphic design system (GDS) files using a machine learning (ML) model according to a process that includes:
• inputting a first GDS file and a second GDS file into a graphic design system exclusive or (GDSXOR) comparator to generate a differences file, wherein the differences file includes a plurality of changes between the first GDS file and a second GDS file;
• using the ML model to process changes in the differences file, wherein the ML model evaluates each change and outputs a probability that a change is at least one of expected or unexpected;
• and
• comparing the probability to a threshold and classifying the change as at least one of expected or unexpected in response to the threshold being met;
• and
• a visualization system having a visualization interface configured to display the change in response to the threshold not being met and to receive a manual classification from a user that classifies the change as at least one of expected or unexpected, wherein displaying the change includes displaying two cells in a single window highlighting the change.