Algorithm 782: Codes for rank-revealing QR factorizations of dense matrices

This article describes a suite of codes as well as associated testing and t iming drivers for computing rank-revealing QR (RRQR) factorizations of dens e matrices. The main contribution is an efficient block algorithm for appro ximating an RRQR factorization, employing a windowed version of the commonl y used Golub pivoting strategy and improved versions of the RRQR algorithms for triangular matrices originally Suggested by Chandrasekaran and Ipsen a nd by Pan and Tang, respectively. We highlight usage and features of these codes.