When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.CPM.2017.20
URN: urn:nbn:de:0030-drops-73335
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Kuboi, Keita ; Fujishige, Yuta ; Inenaga, Shunsuke ; Bannai, Hideo ; Takeda, Masayuki

Faster STR-IC-LCS Computation via RLE

LIPIcs-CPM-2017-20.pdf (0.6 MB)


The constrained LCS problem asks one to find a longest common subsequence of two input strings A and B with some constraints. The STR-IC-LCS problem is a variant of the constrained LCS problem, where the solution must include a given constraint string C as a substring. Given two strings A and B of respective lengths M and N, and a constraint string C of length at most min{M, N}, the best known algorithm for the STR-IC-LCS problem, proposed by Deorowicz (Inf. Process. Lett., 11:423-426, 2012), runs in O(MN) time. In this work, we present an O(mN + nM)-time solution to the STR-IC-LCS problem, where m and n denote the sizes of the run-length encodings of A and B, respectively. Since m <= M and n <= N always hold, our algorithm is always as fast as Deorowicz's algorithm, and is faster when input strings are compressible via RLE.

BibTeX - Entry

  author =	{Keita Kuboi and Yuta Fujishige and Shunsuke Inenaga and Hideo Bannai and Masayuki Takeda},
  title =	{{Faster STR-IC-LCS Computation via RLE}},
  booktitle =	{28th Annual Symposium on Combinatorial Pattern Matching (CPM 2017)},
  pages =	{20:1--20:12},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-039-2},
  ISSN =	{1868-8969},
  year =	{2017},
  volume =	{78},
  editor =	{Juha K{\"a}rkk{\"a}inen and Jakub Radoszewski and Wojciech Rytter},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{},
  URN =		{urn:nbn:de:0030-drops-73335},
  doi =		{10.4230/LIPIcs.CPM.2017.20},
  annote =	{Keywords: longest common subsequence, STR-IC-LCS, run-length encoding}

Keywords: longest common subsequence, STR-IC-LCS, run-length encoding
Seminar: 28th Annual Symposium on Combinatorial Pattern Matching (CPM 2017)
Issue Date: 2017
Date of publication: 28.06.2017

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