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          <dc:title>A Unified Algorithm for Accelerating Edit-Distance Computation via Text-Compression</dc:title>
          <dc:creator>Hermelin, Danny</dc:creator>
          <dc:creator>Landau, Gad M.</dc:creator>
          <dc:creator>Landau, Shir</dc:creator>
          <dc:creator>Weimann, Oren</dc:creator>
          <dc:subject>Edit distance</dc:subject>
          <dc:subject>Straight-line Programs</dc:subject>
          <dc:subject>Dynamic programming acceleration via compression</dc:subject>
          <dc:subject>Combinatorial pattern matching</dc:subject>
          <dc:description>The edit distance problem is a classical fundamental problem in computer science in general, and in combinatorial pattern matching in particular. The standard dynamic-programming solution for this problem computes the edit-distance between a pair of strings of total length $O(N)$ in $O(N^2)$ time. To this date, this quadratic upper-bound has never been substantially improved for general strings. However, there are known techniques for breaking this bound in case the strings are known to compress well under a particular compression scheme. The basic idea is to first compress the strings, and then to compute the edit distance between the compressed strings.&#13;
&#13;
As it turns out, practically all known $o(N^2)$ edit-distance algorithms work, in some sense, under the same paradigm described above. It is therefore natural to ask whether there is a single edit-distance algorithm that works for strings which are compressed under any compression scheme. A rephrasing of this question is to ask whether a single algorithm can exploit the compressibility properties of strings under any compression method, even if each string is compressed using a different compression. In this paper we set out to answer this question by using \emph{straight-line programs}. These provide a generic platform for representing many popular compression schemes including the LZ-family, Run-Length Encoding, Byte-Pair Encoding, and dictionary methods.&#13;
&#13;
For two strings of total length $N$ having straight-line program representations of total size $n$, we present an algorithm running in $O(n^{1.4}N^{1.2})$ time for computing the edit-distance of these two strings under any rational scoring function, and an $O(n^{1.34}N^{1.34})$-time algorithm for arbitrary scoring functions. This improves on a recent algorithm of Tiskin that runs in $O(nN^{1.5})$ time, and works only for rational scoring functions.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Danny Hermelin and Gad M. Landau and Shir Landau and Oren Weimann</dc:contributor>
          <dc:date>2009</dc:date>
          <dc:relation>Is Part Of LIPIcs, Volume 3, 26th International Symposium on Theoretical Aspects of Computer Science (2009)</dc:relation>
          <dc:type>InProceedings</dc:type>
          <dc:type>Text</dc:type>
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          <dc:identifier>doi:10.4230/LIPIcs.STACS.2009.1804</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-18040</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.STACS.2009.1804</dc:identifier>
          <dc:language>eng</dc:language>
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