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        <identifier>oai:drops-oai.dagstuhl.de:17702</identifier>
        <datestamp>2024-03-06T11:00:21Z</datestamp>
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          <dc:title>Dynamic Data Structures for Parameterized String Problems</dc:title>
          <dc:creator>Olkowski, Jędrzej</dc:creator>
          <dc:creator>Pilipczuk, Michał</dc:creator>
          <dc:creator>Rychlicki, Mateusz</dc:creator>
          <dc:creator>Węgrzycki, Karol</dc:creator>
          <dc:creator>Zych-Pawlewicz, Anna</dc:creator>
          <dc:subject>Parameterized algorithms</dc:subject>
          <dc:subject>Dynamic data structures</dc:subject>
          <dc:subject>String problems</dc:subject>
          <dc:subject>Closest String</dc:subject>
          <dc:subject>Edit Distance</dc:subject>
          <dc:subject>Disjoint Factors</dc:subject>
          <dc:subject>Predecessor problem</dc:subject>
          <dc:description>We revisit classic string problems considered in the area of parameterized complexity, and study them through the lens of dynamic data structures. That is, instead of asking for a static algorithm that solves the given instance efficiently, our goal is to design a data structure that efficiently maintains a solution, or reports a lack thereof, upon updates in the instance.&#13;
We first consider the CLOSEST STRING problem, for which we design randomized dynamic data structures with amortized update times d^𝒪(d) and |Σ|^𝒪(d), respectively, where Σ is the alphabet and d is the assumed bound on the maximum distance. These are obtained by combining known static approaches to CLOSEST STRING with color-coding.&#13;
Next, we note that from a result of Frandsen et al. [J. ACM'97] one can easily infer a meta-theorem that provides dynamic data structures for parameterized string problems with worst-case update time of the form 𝒪_k(log log n), where k is the parameter in question and n is the length of the string. We showcase the utility of this meta-theorem by giving such data structures for problems DISJOINT FACTORS and EDIT DISTANCE. We also give explicit data structures for these problems, with worst-case update times 𝒪(k 2^k log log n) and 𝒪(k²log log n), respectively. Finally, we discuss how a lower bound methodology introduced by Amarilli et al. [ICALP'21] can be used to show that obtaining update time 𝒪(f(k)) for DISJOINT FACTORS and EDIT DISTANCE is unlikely already for a constant value of the parameter k.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Jędrzej Olkowski and Michał Pilipczuk and Mateusz Rychlicki and Karol Węgrzycki and Anna Zych-Pawlewicz</dc:contributor>
          <dc:date>2023</dc:date>
          <dc:relation>Is Part Of LIPIcs, Volume 254, 40th International Symposium on Theoretical Aspects of Computer Science (STACS 2023)</dc:relation>
          <dc:type>InProceedings</dc:type>
          <dc:type>Text</dc:type>
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          <dc:identifier>doi:10.4230/LIPIcs.STACS.2023.50</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-177026</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.STACS.2023.50</dc:identifier>
          <dc:language>eng</dc:language>
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