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ShapeCodeBench is a synthetic benchmark for perception-to-program reconstruction where models generate executable drawing programs from raster images, evaluated on metrics like exact match and pixel accuracy. The benchmark is designed to be renewable via seeded RNG, and current models still achieve low exact match rates, indicating room for improvement.