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Johannes Fischer
Given a string $T[1..n]$, its substring complexity is defined as $δ=\max_k d_k/k$, where $d_k$ is the number of its distinct substrings of length $k$ in $T$. We show how to compute it in $O(n+r\log r)$ time, using only $O(r)$ words of space, where $r$ denotes the number of runs in the Burrows-Wheeler transform.
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Johannes Fischer, Dominik Köppl
We revisit the output-sensitive enumeration of maximal closed substrings (MCSs). Given a string of length $n$ over an integer alphabet, let $k$ denote its number of MCS occurrences. We combine a right-to-left sweep on the string with range-successor queries to obtain all MCSs with two deterministic word-RAM bounds: for any fixed $\varepsilon>0$, we can report all MCSs in $O(n\sqrt{\log n}+k\log^\varepsilon n)$ time using $O(n)$ words of space, or in $O(n\sqrt{\log n}+k\log\log n)$ time using $O(n\log\log n)$ words. Both bounds include preprocessing and report occurrences by their endpoints. In particular, these algorithms improve the known $O(n\log n)$ worst-case time bound for sufficiently small output.
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