Before revision:  The complexities of our enumeration algorithms are O(n \log \log (n/r)) time and  O(r ) words of working space for string length n and RLBWT size r .
After revision:  The complexities of our enumeration algorithms are O(n \log \log (n/r)) time and O(r ) words of working space for string length n and number r of runs in RLBWT, where r is expected to be significantly smaller than n for highly repetitive strings (i.e., strings with many repetitions). Experiments using a benchmark dataset of highly repetitive strings show that the results of r-enum are more space-efficient than the previous results. In addition, we demonstrate the applicability of r-enum to a huge string by performing experiments on a 300-gigabyte string of 100 human genomes .