Experimental Evaluation of Structural Filtering as a Tool for Exact and Efficient Geometric Computing ∗

We report on experimental studies and further investigations of structural filtering introduced in [3] as a paradigm for efficient exact geometric computing. In particular, we show that structural filtering can almost completely avoid the overhead of floating-point filters for many fundamental geometric problems. Furthermore we develop new repair strategies that avoid the very bad performance of the simple repair methods presented in the original paper in presence of difficult input data.