14,861 research outputs found
Fast Searching in Packed Strings
Given strings and the (exact) string matching problem is to find all
positions of substrings in matching . The classical Knuth-Morris-Pratt
algorithm [SIAM J. Comput., 1977] solves the string matching problem in linear
time which is optimal if we can only read one character at the time. However,
most strings are stored in a computer in a packed representation with several
characters in a single word, giving us the opportunity to read multiple
characters simultaneously. In this paper we study the worst-case complexity of
string matching on strings given in packed representation. Let be
the lengths and , respectively, and let denote the size of the
alphabet. On a standard unit-cost word-RAM with logarithmic word size we
present an algorithm using time O\left(\frac{n}{\log_\sigma n} + m +
\occ\right). Here \occ is the number of occurrences of in . For this improves the bound of the Knuth-Morris-Pratt algorithm.
Furthermore, if our algorithm is optimal since any
algorithm must spend at least \Omega(\frac{(n+m)\log
\sigma}{\log n} + \occ) = \Omega(\frac{n}{\log_\sigma n} + \occ) time to
read the input and report all occurrences. The result is obtained by a novel
automaton construction based on the Knuth-Morris-Pratt algorithm combined with
a new compact representation of subautomata allowing an optimal
tabulation-based simulation.Comment: To appear in Journal of Discrete Algorithms. Special Issue on CPM
200
Covering Problems for Partial Words and for Indeterminate Strings
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 , the number of
non-solid symbols. For the indeterminate string covering problem we obtain a
-time algorithm. For the partial word covering
problem we obtain a -time algorithm. We
prove that, unless the Exponential Time Hypothesis is false, no
-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
Pattern matching in Lempel-Ziv compressed strings: fast, simple, and deterministic
Countless variants of the Lempel-Ziv compression are widely used in many
real-life applications. This paper is concerned with a natural modification of
the classical pattern matching problem inspired by the popularity of such
compression methods: given an uncompressed pattern s[1..m] and a Lempel-Ziv
representation of a string t[1..N], does s occur in t? Farach and Thorup gave a
randomized O(nlog^2(N/n)+m) time solution for this problem, where n is the size
of the compressed representation of t. We improve their result by developing a
faster and fully deterministic O(nlog(N/n)+m) time algorithm with the same
space complexity. Note that for highly compressible texts, log(N/n) might be of
order n, so for such inputs the improvement is very significant. A (tiny)
fragment of our method can be used to give an asymptotically optimal solution
for the substring hashing problem considered by Farach and Muthukrishnan.Comment: submitte
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