Sparsity Preserving Algorithms for Octagons
Programming Languages
2016-12-02 v1 Data Structures and Algorithms
Logic in Computer Science
Abstract
Known algorithms for manipulating octagons do not preserve their sparsity, leading typically to quadratic or cubic time and space complexities even if no relation among variables is known when they are all bounded. In this paper, we present new algorithms, which use and return octagons represented as weakly closed difference bound matrices, preserve the sparsity of their input and have better performance in the case their inputs are sparse. We prove that these algorithms are as precise as the known ones.
Cite
@article{arxiv.1612.00277,
title = {Sparsity Preserving Algorithms for Octagons},
author = {Jacques-Henri Jourdan},
journal= {arXiv preprint arXiv:1612.00277},
year = {2016}
}
Comments
in Isabella Mastroeni. Numerical and symbolic abstract domains, Sep 2016, Edinburgh, United Kingdom. Elsevier, Numerical and symbolic abstract domains, pp.14, 2016