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For example, one might wish to find all occurrences of a "word" despite it having alternate spellings, prefixes or suffixes, etc. Another more complex type of search is regular expression searching, where the user constructs a pattern of characters or other symbols, and any match to the pattern should fulfill the search.
IS:/xxx/;999:/yyy/ insert the string /yyy/ before the next 999 occurrences of /xxx/ RS:/xxx/;999:/yyy/ replace the next 999 occurrences of the string /xxx/ with /yyy/ DS:/xxx/;999 delete the next 999 occurrences of the string /xxx/ Lastly, the commands can be further modified with V to turn on verify mode and with O to specify nth occurrence ...
If n is greater than the length of the string then most implementations return the whole string (exceptions exist – see code examples). Note that for variable-length encodings such as UTF-8, UTF-16 or Shift-JIS, it can be necessary to remove string positions at the end, in order to avoid invalid strings.
The Boyer–Moore algorithm searches for occurrences of P in T by performing explicit character comparisons at different alignments. Instead of a brute-force search of all alignments (of which there are n − m + 1 {\displaystyle n-m+1} ), Boyer–Moore uses information gained by preprocessing P to skip as many alignments as possible.
Map all occurrences of a, e, i, o, u, y, h, w. to zero(0) Replace all consonants (include the first letter) with digits as in [2.] above. Replace all adjacent same digits with one digit, and then remove all the zero (0) digits; If the saved letter's digit is the same as the resulting first digit, remove the digit (keep the letter).
For example, String.class can be used instead of doing new String().getClass(). continue Used to resume program execution at the end of the current loop body. If followed by a label, continue resumes execution at the end of the enclosing labeled loop body. default
In computer science, the Knuth–Morris–Pratt algorithm (or KMP algorithm) is a string-searching algorithm that searches for occurrences of a "word" W within a main "text string" S by employing the observation that when a mismatch occurs, the word itself embodies sufficient information to determine where the next match could begin, thus bypassing re-examination of previously matched characters.
We assume all the substrings have a fixed length m. A naïve way to search for k patterns is to repeat a single-pattern search taking O(n+m) time, totaling in O((n+m)k) time. In contrast, the above algorithm can find all k patterns in O(n+km) expected time, assuming that a hash table check works in O(1) expected time.