Faster Algorithms for Computing Longest Common Increasing Subsequences

  • Gerth Stølting Brodal
  • Kanela Kaligosi
  • Irit Katriel
  • Martin Kutz
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4009)


We present algorithms for finding a longest common increasing subsequence of two or more input sequences. For two sequences of lengths m and n, where mn, we present an algorithm with an output-dependent expected running time of \(O((m+n\ell) \log\log \sigma + {\ensuremath{\mathit{Sort}}})\) and O(m) space, where ℓ is the length of an LCIS, σ is the size of the alphabet, and \({\ensuremath{\mathit{Sort}}}\) is the time to sort each input sequence. For k≥3 length-n sequences we present an algorithm which improves the previous best bound by more than a factor k for many inputs. In both cases, our algorithms are conceptually quite simple but rely on existing sophisticated data structures. Finally, we introduce the problem of longest common weakly-increasing (or non-decreasing) subsequences (LCWIS), for which we present an O(m+nlogn)-time algorithm for the 3-letter alphabet case. For the extensively studied longest common subsequence problem, comparable speedups have not been achieved for small alphabets.


Input Sequence Longe Common Subsequence Longe Common Subsequence Close Split Longe Common Subsequence Problem 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Gerth Stølting Brodal
    • 1
  • Kanela Kaligosi
    • 2
  • Irit Katriel
    • 1
  • Martin Kutz
    • 2
  1. 1.BRICSUniversity of AarhusÅrhusDenmark
  2. 2.Max-Plank-Institut für InformatikSaarbrückenGermany

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