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  2. LCP array - Wikipedia

    en.wikipedia.org/wiki/LCP_array

    It stores the lengths of the longest common prefixes (LCPs) between all pairs of consecutive suffixes in a sorted suffix array. For example, if A := [ aab , ab , abaab , b , baab ] is a suffix array, the longest common prefix between A [1] = aab and A [2] = ab is a which has length 1, so H [2] = 1 in the LCP array H .

  3. Longest common subsequence - Wikipedia

    en.wikipedia.org/wiki/Longest_common_subsequence

    It differs from the longest common substring: unlike substrings, subsequences are not required to occupy consecutive positions within the original sequences. The problem of computing longest common subsequences is a classic computer science problem, the basis of data comparison programs such as the diff utility , and has applications in ...

  4. Comparison of programming languages (syntax) - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_programming...

    Like raw strings, there can be any number of equals signs between the square brackets, provided both the opening and closing tags have a matching number of equals signs; this allows nesting as long as nested block comments/raw strings use a different number of equals signs than their enclosing comment: --[[comment --[=[ nested comment ...

  5. String (computer science) - Wikipedia

    en.wikipedia.org/wiki/String_(computer_science)

    A string (or word [23] or expression [24]) over Σ is any finite sequence of symbols from Σ. [25] For example, if Σ = {0, 1}, then 01011 is a string over Σ. The length of a string s is the number of symbols in s (the length of the sequence) and can be any non-negative integer; it is often denoted as |s|.

  6. Longest increasing subsequence - Wikipedia

    en.wikipedia.org/wiki/Longest_increasing_subsequence

    The longest increasing subsequence problem is closely related to the longest common subsequence problem, which has a quadratic time dynamic programming solution: the longest increasing subsequence of a sequence is the longest common subsequence of and , where is the result of sorting.

  7. Skip list - Wikipedia

    en.wikipedia.org/wiki/Skip_list

    () operations, which force us to visit every node in ascending order (such as printing the entire list), provide the opportunity to perform a behind-the-scenes derandomization of the level structure of the skip-list in an optimal way, bringing the skip list to (⁡) search time. (Choose the level of the i'th finite node to be 1 plus the number ...

  8. String operations - Wikipedia

    en.wikipedia.org/wiki/String_operations

    A string homomorphism (often referred to simply as a homomorphism in formal language theory) is a string substitution such that each character is replaced by a single string. That is, f ( a ) = s {\displaystyle f(a)=s} , where s {\displaystyle s} is a string, for each character a {\displaystyle a} .

  9. Integer sequence - Wikipedia

    en.wikipedia.org/wiki/Integer_sequence

    An integer sequence is computable if there exists an algorithm that, given n, calculates a n, for all n > 0. The set of computable integer sequences is countable.The set of all integer sequences is uncountable (with cardinality equal to that of the continuum), and so not all integer sequences are computable.