Mathur, AmanZufferey, DamienLee, Sung-Hee and Zollmann, Stefanie and Okabe, Makoto and Wünsche, Burkhard2021-10-142021-10-142021978-3-03868-162-5https://doi.org/10.2312/pg.20211396https://diglib.eg.org:443/handle/10.2312/pg20211396Parametric CAD, in conjunction with 3D-printing, is democratizing design and production pipelines. End-users can easily change parameters of publicly available designs, and 3D-print the customized objects. In research and industry, parametric designs are being used to find optimal, or unique final objects. Unfortunately, for most designs, many combinations of parameter values are invalid. Restricting the parameter space of designs to only the valid configurations is a difficult problem. Most publicly available designs do not contain this information. Using ideas from program analysis, we synthesize constraints on parameters of parametric designs. Some constraints are synthesized statically, by exploiting implicit assumptions of the design process. Several others are inferred by evaluating the design on many different samples, and then constructing and solving hypotheses. Our approach is effective at finding constraints on parameter values for a wide variety of parametric designs, with a very small runtime cost, in the order of seconds.Computing methodologiesShape analysis10.2312/pg.2021139675-80