On error representation in exact-decisions number types
arXiv:1807.041811 citationsh-index: 2
AI Analysis
For developers of robust geometric algorithms, this provides a comparative analysis of error representation methods, but is primarily a survey with incremental insights.
This work reviews error bound representation in accuracy-driven computation for exact-decisions number types, comparing approaches and highlighting caveats with experimental support.
Accuracy-driven computation is a strategy widely used in exact-decisions number types for robust geometric algorithms. This work provides an overview on the usage of error bounds in accuracy-driven computation, compares different approaches on the representation and computation of these error bounds and points out some caveats. The stated claims are supported by experiments.