81,143 research outputs found

    String Matching with Variable Length Gaps

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    We consider string matching with variable length gaps. Given a string TT and a pattern PP consisting of strings separated by variable length gaps (arbitrary strings of length in a specified range), the problem is to find all ending positions of substrings in TT that match PP. This problem is a basic primitive in computational biology applications. Let mm and nn be the lengths of PP and TT, respectively, and let kk be the number of strings in PP. We present a new algorithm achieving time O(nlogk+m+α)O(n\log k + m +\alpha) and space O(m+A)O(m + A), where AA is the sum of the lower bounds of the lengths of the gaps in PP and α\alpha is the total number of occurrences of the strings in PP within TT. Compared to the previous results this bound essentially achieves the best known time and space complexities simultaneously. Consequently, our algorithm obtains the best known bounds for almost all combinations of mm, nn, kk, AA, and α\alpha. Our algorithm is surprisingly simple and straightforward to implement. We also present algorithms for finding and encoding the positions of all strings in PP for every match of the pattern.Comment: draft of full version, extended abstract at SPIRE 201

    Covering Problems for Partial Words and for Indeterminate Strings

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    We consider the problem of computing a shortest solid cover of an indeterminate string. An indeterminate string may contain non-solid symbols, each of which specifies a subset of the alphabet that could be present at the corresponding position. We also consider covering partial words, which are a special case of indeterminate strings where each non-solid symbol is a don't care symbol. We prove that indeterminate string covering problem and partial word covering problem are NP-complete for binary alphabet and show that both problems are fixed-parameter tractable with respect to kk, the number of non-solid symbols. For the indeterminate string covering problem we obtain a 2O(klogk)+nkO(1)2^{O(k \log k)} + n k^{O(1)}-time algorithm. For the partial word covering problem we obtain a 2O(klogk)+nkO(1)2^{O(\sqrt{k}\log k)} + nk^{O(1)}-time algorithm. We prove that, unless the Exponential Time Hypothesis is false, no 2o(k)nO(1)2^{o(\sqrt{k})} n^{O(1)}-time solution exists for either problem, which shows that our algorithm for this case is close to optimal. We also present an algorithm for both problems which is feasible in practice.Comment: full version (simplified and corrected); preliminary version appeared at ISAAC 2014; 14 pages, 4 figure

    Sublinear Space Algorithms for the Longest Common Substring Problem

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    Given mm documents of total length nn, we consider the problem of finding a longest string common to at least d2d \geq 2 of the documents. This problem is known as the \emph{longest common substring (LCS) problem} and has a classic O(n)O(n) space and O(n)O(n) time solution (Weiner [FOCS'73], Hui [CPM'92]). However, the use of linear space is impractical in many applications. In this paper we show that for any trade-off parameter 1τn1 \leq \tau \leq n, the LCS problem can be solved in O(τ)O(\tau) space and O(n2/τ)O(n^2/\tau) time, thus providing the first smooth deterministic time-space trade-off from constant to linear space. The result uses a new and very simple algorithm, which computes a τ\tau-additive approximation to the LCS in O(n2/τ)O(n^2/\tau) time and O(1)O(1) space. We also show a time-space trade-off lower bound for deterministic branching programs, which implies that any deterministic RAM algorithm solving the LCS problem on documents from a sufficiently large alphabet in O(τ)O(\tau) space must use Ω(nlog(n/(τlogn))/loglog(n/(τlogn))\Omega(n\sqrt{\log(n/(\tau\log n))/\log\log(n/(\tau\log n)}) time.Comment: Accepted to 22nd European Symposium on Algorithm

    Linear Algorithm for Conservative Degenerate Pattern Matching

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    A degenerate symbol x* over an alphabet A is a non-empty subset of A, and a sequence of such symbols is a degenerate string. A degenerate string is said to be conservative if its number of non-solid symbols is upper-bounded by a fixed positive constant k. We consider here the matching problem of conservative degenerate strings and present the first linear-time algorithm that can find, for given degenerate strings P* and T* of total length n containing k non-solid symbols in total, the occurrences of P* in T* in O(nk) time
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