Abstract
The Sort Transform (ST) can significantly speed up the block sorting phase of the Burrows-Wheeler transform (BWT) by sorting only limited order contexts. However, the best result obtained so far for the inverse ST has a time complexity O(Nlogk) and a space complexity O(N), where N and k are the text size and the context order of the transform, respectively. In this paper, we present a novel algorithm that can compute the inverse ST in an O(N) time/space complexity, a linear result independent of k. The main idea behind the design of the linear algorithm is a set of cycle properties of k-order contexts we explored for this work. These newly discovered cycle properties allow us to quickly compute the longest common prefix (LCP) between any pair of adjacent k-order contexts that may belong to two different cycles, leading to the proposed linear inverse ST algorithm.
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Nong, G., Zhang, S., Chan, W.H. (2008). Computing Inverse ST in Linear Complexity. In: Ferragina, P., Landau, G.M. (eds) Combinatorial Pattern Matching. CPM 2008. Lecture Notes in Computer Science, vol 5029. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69068-9_18
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DOI: https://doi.org/10.1007/978-3-540-69068-9_18
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69066-5
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