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        <datestamp>2024-03-06T10:55:46Z</datestamp>
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          <dc:title>Fixed-Parameter Sensitivity Oracles</dc:title>
          <dc:creator>Bilò, Davide</dc:creator>
          <dc:creator>Casel, Katrin</dc:creator>
          <dc:creator>Choudhary, Keerti</dc:creator>
          <dc:creator>Cohen, Sarel</dc:creator>
          <dc:creator>Friedrich, Tobias</dc:creator>
          <dc:creator>Lagodzinski, J.A. Gregor</dc:creator>
          <dc:creator>Schirneck, Martin</dc:creator>
          <dc:creator>Wietheger, Simon</dc:creator>
          <dc:subject>data structures</dc:subject>
          <dc:subject>distance preservers</dc:subject>
          <dc:subject>distance sensitivity oracles</dc:subject>
          <dc:subject>fault tolerance</dc:subject>
          <dc:subject>fixed-parameter tractability</dc:subject>
          <dc:subject>k-path</dc:subject>
          <dc:subject>vertex cover</dc:subject>
          <dc:description>We combine ideas from distance sensitivity oracles (DSOs) and fixed-parameter tractability (FPT) to design sensitivity oracles for FPT graph problems. An oracle with sensitivity f for an FPT problem Π on a graph G with parameter k preprocesses G in time O(g(f,k) ⋅ poly(n)). When queried with a set F of at most f edges of G, the oracle reports the answer to the Π - with the same parameter k - on the graph G-F, i.e., G deprived of F. The oracle should answer queries in a time that is significantly faster than merely running the best-known FPT algorithm on G-F from scratch.&#13;
We design sensitivity oracles for the k-Path and the k-Vertex Cover problem. Our first oracle for k-Path has size O(k^{f+1}) and query time O(f min{f, log(f) + k}). We use a technique inspired by the work of Weimann and Yuster [FOCS 2010, TALG 2013] on distance sensitivity problems to reduce the space to O(({f+k}/f)^f ({f+k}/k)^k fk⋅log(n)) at the expense of increasing the query time to O(({f+k}/f)^f ({f+k}/k)^k f min{f,k}⋅log(n)). Both oracles can be modified to handle vertex-failures, but we need to replace k with 2k in all the claimed bounds.&#13;
Regarding k-Vertex Cover, we design three oracles offering different trade-offs between the size and the query time. The first oracle takes O(3^{f+k}) space and has O(2^f) query time, the second one has a size of O(2^{f+k²+k}) and a query time of O(f+k²); finally, the third one takes O(fk+k²) space and can be queried in time O(1.2738^k + f). All our oracles are computable in time (at most) proportional to their size and the time needed to detect a k-path or k-vertex cover, respectively. We also provide an interesting connection between k-Vertex Cover and the fault-tolerant shortest path problem, by giving a DSO of size O(poly(f,k) ⋅ n) with query time in O(poly(f,k)), where k is the size of a vertex cover.&#13;
Following our line of research connecting fault-tolerant FPT and shortest paths problems, we introduce parameterization to the computation of distance preservers. We study the problem, given a directed unweighted graph with a fixed source s and parameters f and k, to construct a polynomial-sized oracle that efficiently reports, for any target vertex v and set F of at most f edges, whether the distance from s to v increases at most by an additive term of k in G-F. The oracle size is O(2^k k²⋅n), while the time needed to answer a query is O(2^k f^ω k^ω), where ω &lt; 2.373 is the matrix multiplication exponent. The second problem we study is about the construction of bounded-stretch fault-tolerant preservers. We construct a subgraph with O(2^{fk+f+k} k ⋅ n) edges that preserves those s-v-distances that do not increase by more than k upon failure of F. This improves significantly over the Õ(f n^{2-1/(2^f)}) bound in the unparameterized case by Bodwin et al. [ICALP 2017].</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Davide Bilò and Katrin Casel and Keerti Choudhary and Sarel Cohen and Tobias Friedrich and J.A. Gregor Lagodzinski and Martin Schirneck and Simon Wietheger</dc:contributor>
          <dc:date>2022</dc:date>
          <dc:relation>Is Part Of LIPIcs, Volume 215, 13th Innovations in Theoretical Computer Science Conference (ITCS 2022)</dc:relation>
          <dc:type>InProceedings</dc:type>
          <dc:type>Text</dc:type>
          <dc:type>doc-type:ResearchArticle</dc:type>
          <dc:type>publishedVersion</dc:type>
          <dc:format>application/pdf</dc:format>
          <dc:identifier>doi:10.4230/LIPIcs.ITCS.2022.23</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-156196</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ITCS.2022.23</dc:identifier>
          <dc:language>eng</dc:language>
          <dc:rights>https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
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