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Returns the position of the start of the last occurrence of substring in string. If the substring is not found most of these routines return an invalid index value – -1 where indexes are 0-based, 0 where they are 1-based – or some value to be interpreted as Boolean FALSE. Related instr
For example, in this table, the substrings at indices 2 to 4 (in red) and indices 6 to 8 (in blue) are a maximal pair, because they contain identical characters (abc), and they have different characters to the left (x at index 1 and y at index 5) and different characters to the right (y at index 5 and w at index 9). Similarly, the substrings at ...
The indices are one-based (meaning the first is number one), inclusive (meaning the indices you specify are included), and may be negative to count from the other end. For example, {{#invoke:string|sub|12345678|2|-3}} → 23456. Not all the legacy substring templates use this numbering scheme, so check the documentation of unfamiliar templates.
The variable z is used to hold the length of the longest common substring found so far. The set ret is used to hold the set of strings which are of length z. The set ret can be saved efficiently by just storing the index i, which is the last character of the longest common substring (of size z) instead of S[(i-z+1)..i].
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 ...
For example, the longest palindromic substring of "bananas" is "anana". The longest palindromic substring is not guaranteed to be unique; for example, in the string "abracadabra", there is no palindromic substring with length greater than three, but there are two palindromic substrings with length three, namely, "aca" and "ada".
T[y 2] is a substring of T with the minimal edit distance to the pattern P. Computing the E(x, y) array takes O(mn) time with the dynamic programming algorithm, while the backwards-working phase takes O(n + m) time. Another recent idea is the similarity join.
The difference between the two algorithms consists in that the optimal string alignment algorithm computes the number of edit operations needed to make the strings equal under the condition that no substring is edited more than once, whereas the second one presents no such restriction. Take for example the edit distance between CA and ABC.