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  2. Longest common substring - Wikipedia

    en.wikipedia.org/wiki/Longest_common_substring

    One can find the lengths and starting positions of the longest common substrings of and in (+) time with the help of a generalized suffix tree. A faster algorithm can be achieved in the word RAM model of computation if the size σ {\displaystyle \sigma } of the input alphabet is in 2 o ( log ⁡ ( n + m ) ) {\displaystyle 2^{o\left({\sqrt {\log ...

  3. Longest repeated substring problem - Wikipedia

    en.wikipedia.org/wiki/Longest_repeated_substring...

    In computer science, the longest repeated substring problem is the problem of finding the longest substring of a string that occurs at least twice. This problem can be solved in linear time and space Θ ( n ) {\displaystyle \Theta (n)} by building a suffix tree for the string (with a special end-of-string symbol like '$' appended), and finding ...

  4. Boyer–Moore–Horspool algorithm - Wikipedia

    en.wikipedia.org/wiki/Boyer–Moore–Horspool...

    The algorithm trades space for time in order to obtain an average-case complexity of O(n) on random text, although it has O(nm) in the worst case, where the length of the pattern is m and the length of the search string is n.

  5. Suffix tree - Wikipedia

    en.wikipedia.org/wiki/Suffix_tree

    String search, in O(m) complexity, where m is the length of the sub-string (but with initial O(n) time required to build the suffix tree for the string) Finding the longest repeated substring; Finding the longest common substring; Finding the longest palindrome in a string

  6. LCP array - Wikipedia

    en.wikipedia.org/wiki/LCP_array

    The longest repeated substring problem for a string of length can be solved in () time using both the suffix array and the LCP array. It is sufficient to perform a linear scan through the LCP array in order to find its maximum value v m a x {\displaystyle v_{max}} and the corresponding index i {\displaystyle i} where v m a x {\displaystyle v ...

  7. Time complexity - Wikipedia

    en.wikipedia.org/wiki/Time_complexity

    [1]: 226 Since this function is generally difficult to compute exactly, and the running time for small inputs is usually not consequential, one commonly focuses on the behavior of the complexity when the input size increases—that is, the asymptotic behavior of the complexity. Therefore, the time complexity is commonly expressed using big O ...

  8. Longest palindromic substring - Wikipedia

    en.wikipedia.org/wiki/Longest_palindromic_substring

    Longest Palindromic Substring Part II., 2011-11-20, archived from the original on 2018-12-08. A description of Manacher’s algorithm for finding the longest palindromic substring in linear time. Akalin, Fred (2007-11-28), Finding the longest palindromic substring in linear time. An explanation and Python implementation of Manacher's linear ...

  9. Best, worst and average case - Wikipedia

    en.wikipedia.org/wiki/Best,_worst_and_average_case

    Also, when implemented with the "shortest first" policy, the worst-case space complexity is instead bounded by O(log(n)). Heapsort has O(n) time when all elements are the same. Heapify takes O(n) time and then removing elements from the heap is O(1) time for each of the n elements. The run time grows to O(nlog(n)) if all elements must be distinct.