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/* Searching in a string. -*- coding: utf-8 -*-
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Copyright (C) 2005-2017 Free Software Foundation, Inc.
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Written by Bruno Haible <bruno@clisp.org>, 2005.
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This program is free software: you can redistribute it and/or modify
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it under the terms of the GNU General Public License as published by
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the Free Software Foundation; either version 3 of the License, or
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(at your option) any later version.
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This program is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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GNU General Public License for more details.
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You should have received a copy of the GNU General Public License
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along with this program. If not, see <http://www.gnu.org/licenses/>. */
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#include <config.h>
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/* Specification. */
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#include <string.h>
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#include <stdbool.h>
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#include <stddef.h> /* for NULL, in case a nonstandard string.h lacks it */
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#include "malloca.h"
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#include "mbuiter.h"
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/* Knuth-Morris-Pratt algorithm. */
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#define UNIT unsigned char
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#define CANON_ELEMENT(c) c
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#include "str-kmp.h"
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/* Knuth-Morris-Pratt algorithm.
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See http://en.wikipedia.org/wiki/Knuth-Morris-Pratt_algorithm
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Return a boolean indicating success:
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Return true and set *RESULTP if the search was completed.
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Return false if it was aborted because not enough memory was available. */
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static bool
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knuth_morris_pratt_multibyte (const char *haystack, const char *needle,
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const char **resultp)
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{
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size_t m = mbslen (needle);
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mbchar_t *needle_mbchars;
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size_t *table;
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/* Allocate room for needle_mbchars and the table. */
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void *memory = nmalloca (m, sizeof (mbchar_t) + sizeof (size_t));
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void *table_memory;
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if (memory == NULL)
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return false;
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needle_mbchars = memory;
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table_memory = needle_mbchars + m;
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table = table_memory;
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/* Fill needle_mbchars. */
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{
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mbui_iterator_t iter;
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size_t j;
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j = 0;
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for (mbui_init (iter, needle); mbui_avail (iter); mbui_advance (iter), j++)
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mb_copy (&needle_mbchars[j], &mbui_cur (iter));
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}
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/* Fill the table.
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For 0 < i < m:
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0 < table[i] <= i is defined such that
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forall 0 < x < table[i]: needle[x..i-1] != needle[0..i-1-x],
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and table[i] is as large as possible with this property.
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This implies:
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1) For 0 < i < m:
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If table[i] < i,
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needle[table[i]..i-1] = needle[0..i-1-table[i]].
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2) For 0 < i < m:
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rhaystack[0..i-1] == needle[0..i-1]
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and exists h, i <= h < m: rhaystack[h] != needle[h]
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implies
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forall 0 <= x < table[i]: rhaystack[x..x+m-1] != needle[0..m-1].
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table[0] remains uninitialized. */
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{
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size_t i, j;
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/* i = 1: Nothing to verify for x = 0. */
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table[1] = 1;
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j = 0;
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for (i = 2; i < m; i++)
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{
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/* Here: j = i-1 - table[i-1].
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The inequality needle[x..i-1] != needle[0..i-1-x] is known to hold
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for x < table[i-1], by induction.
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Furthermore, if j>0: needle[i-1-j..i-2] = needle[0..j-1]. */
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mbchar_t *b = &needle_mbchars[i - 1];
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for (;;)
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{
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/* Invariants: The inequality needle[x..i-1] != needle[0..i-1-x]
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is known to hold for x < i-1-j.
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Furthermore, if j>0: needle[i-1-j..i-2] = needle[0..j-1]. */
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if (mb_equal (*b, needle_mbchars[j]))
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{
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/* Set table[i] := i-1-j. */
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table[i] = i - ++j;
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break;
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}
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/* The inequality needle[x..i-1] != needle[0..i-1-x] also holds
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for x = i-1-j, because
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needle[i-1] != needle[j] = needle[i-1-x]. */
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if (j == 0)
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{
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/* The inequality holds for all possible x. */
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table[i] = i;
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break;
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}
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/* The inequality needle[x..i-1] != needle[0..i-1-x] also holds
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for i-1-j < x < i-1-j+table[j], because for these x:
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needle[x..i-2]
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= needle[x-(i-1-j)..j-1]
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!= needle[0..j-1-(x-(i-1-j))] (by definition of table[j])
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= needle[0..i-2-x],
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hence needle[x..i-1] != needle[0..i-1-x].
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Furthermore
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needle[i-1-j+table[j]..i-2]
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= needle[table[j]..j-1]
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= needle[0..j-1-table[j]] (by definition of table[j]). */
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j = j - table[j];
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}
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/* Here: j = i - table[i]. */
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}
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}
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/* Search, using the table to accelerate the processing. */
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{
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size_t j;
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mbui_iterator_t rhaystack;
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mbui_iterator_t phaystack;
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*resultp = NULL;
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j = 0;
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mbui_init (rhaystack, haystack);
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mbui_init (phaystack, haystack);
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/* Invariant: phaystack = rhaystack + j. */
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while (mbui_avail (phaystack))
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if (mb_equal (needle_mbchars[j], mbui_cur (phaystack)))
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{
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j++;
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mbui_advance (phaystack);
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if (j == m)
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{
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/* The entire needle has been found. */
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*resultp = mbui_cur_ptr (rhaystack);
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break;
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}
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}
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else if (j > 0)
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{
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/* Found a match of needle[0..j-1], mismatch at needle[j]. */
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size_t count = table[j];
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j -= count;
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for (; count > 0; count--)
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{
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if (!mbui_avail (rhaystack))
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abort ();
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mbui_advance (rhaystack);
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}
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}
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else
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{
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/* Found a mismatch at needle[0] already. */
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if (!mbui_avail (rhaystack))
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abort ();
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mbui_advance (rhaystack);
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mbui_advance (phaystack);
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}
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}
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freea (memory);
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return true;
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}
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/* Find the first occurrence of the character string NEEDLE in the character
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string HAYSTACK. Return NULL if NEEDLE is not found in HAYSTACK. */
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char *
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mbsstr (const char *haystack, const char *needle)
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{
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/* Be careful not to look at the entire extent of haystack or needle
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until needed. This is useful because of these two cases:
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- haystack may be very long, and a match of needle found early,
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- needle may be very long, and not even a short initial segment of
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needle may be found in haystack. */
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if (MB_CUR_MAX > 1)
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{
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mbui_iterator_t iter_needle;
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mbui_init (iter_needle, needle);
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if (mbui_avail (iter_needle))
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{
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/* Minimizing the worst-case complexity:
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Let n = mbslen(haystack), m = mbslen(needle).
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The na誰ve algorithm is O(n*m) worst-case.
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The Knuth-Morris-Pratt algorithm is O(n) worst-case but it needs a
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memory allocation.
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To achieve linear complexity and yet amortize the cost of the
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memory allocation, we activate the Knuth-Morris-Pratt algorithm
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only once the na誰ve algorithm has already run for some time; more
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precisely, when
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- the outer loop count is >= 10,
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- the average number of comparisons per outer loop is >= 5,
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- the total number of comparisons is >= m.
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But we try it only once. If the memory allocation attempt failed,
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we don't retry it. */
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bool try_kmp = true;
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size_t outer_loop_count = 0;
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size_t comparison_count = 0;
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size_t last_ccount = 0; /* last comparison count */
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mbui_iterator_t iter_needle_last_ccount; /* = needle + last_ccount */
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mbui_iterator_t iter_haystack;
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mbui_init (iter_needle_last_ccount, needle);
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mbui_init (iter_haystack, haystack);
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for (;; mbui_advance (iter_haystack))
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{
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if (!mbui_avail (iter_haystack))
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/* No match. */
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return NULL;
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/* See whether it's advisable to use an asymptotically faster
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algorithm. */
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if (try_kmp
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&& outer_loop_count >= 10
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&& comparison_count >= 5 * outer_loop_count)
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{
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/* See if needle + comparison_count now reaches the end of
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needle. */
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size_t count = comparison_count - last_ccount;
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for (;
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count > 0 && mbui_avail (iter_needle_last_ccount);
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count--)
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mbui_advance (iter_needle_last_ccount);
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last_ccount = comparison_count;
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if (!mbui_avail (iter_needle_last_ccount))
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{
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/* Try the Knuth-Morris-Pratt algorithm. */
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const char *result;
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bool success =
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knuth_morris_pratt_multibyte (haystack, needle,
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&result);
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if (success)
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return (char *) result;
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try_kmp = false;
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}
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}
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outer_loop_count++;
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comparison_count++;
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if (mb_equal (mbui_cur (iter_haystack), mbui_cur (iter_needle)))
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/* The first character matches. */
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{
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mbui_iterator_t rhaystack;
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mbui_iterator_t rneedle;
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memcpy (&rhaystack, &iter_haystack, sizeof (mbui_iterator_t));
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mbui_advance (rhaystack);
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mbui_init (rneedle, needle);
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if (!mbui_avail (rneedle))
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abort ();
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mbui_advance (rneedle);
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for (;; mbui_advance (rhaystack), mbui_advance (rneedle))
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{
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if (!mbui_avail (rneedle))
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/* Found a match. */
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return (char *) mbui_cur_ptr (iter_haystack);
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if (!mbui_avail (rhaystack))
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/* No match. */
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return NULL;
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comparison_count++;
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if (!mb_equal (mbui_cur (rhaystack), mbui_cur (rneedle)))
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/* Nothing in this round. */
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break;
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}
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Packit |
33f14e |
}
|
|
Packit |
33f14e |
}
|
|
Packit |
33f14e |
}
|
|
Packit |
33f14e |
else
|
|
Packit |
33f14e |
return (char *) haystack;
|
|
Packit |
33f14e |
}
|
|
Packit |
33f14e |
else
|
|
Packit |
33f14e |
{
|
|
Packit |
33f14e |
if (*needle != '\0')
|
|
Packit |
33f14e |
{
|
|
Packit |
33f14e |
/* Minimizing the worst-case complexity:
|
|
Packit |
33f14e |
Let n = strlen(haystack), m = strlen(needle).
|
|
Packit |
33f14e |
The na誰ve algorithm is O(n*m) worst-case.
|
|
Packit |
33f14e |
The Knuth-Morris-Pratt algorithm is O(n) worst-case but it needs a
|
|
Packit |
33f14e |
memory allocation.
|
|
Packit |
33f14e |
To achieve linear complexity and yet amortize the cost of the
|
|
Packit |
33f14e |
memory allocation, we activate the Knuth-Morris-Pratt algorithm
|
|
Packit |
33f14e |
only once the na誰ve algorithm has already run for some time; more
|
|
Packit |
33f14e |
precisely, when
|
|
Packit |
33f14e |
- the outer loop count is >= 10,
|
|
Packit |
33f14e |
- the average number of comparisons per outer loop is >= 5,
|
|
Packit |
33f14e |
- the total number of comparisons is >= m.
|
|
Packit |
33f14e |
But we try it only once. If the memory allocation attempt failed,
|
|
Packit |
33f14e |
we don't retry it. */
|
|
Packit |
33f14e |
bool try_kmp = true;
|
|
Packit |
33f14e |
size_t outer_loop_count = 0;
|
|
Packit |
33f14e |
size_t comparison_count = 0;
|
|
Packit |
33f14e |
size_t last_ccount = 0; /* last comparison count */
|
|
Packit |
33f14e |
const char *needle_last_ccount = needle; /* = needle + last_ccount */
|
|
Packit |
33f14e |
|
|
Packit |
33f14e |
/* Speed up the following searches of needle by caching its first
|
|
Packit |
33f14e |
character. */
|
|
Packit |
33f14e |
char b = *needle++;
|
|
Packit |
33f14e |
|
|
Packit |
33f14e |
for (;; haystack++)
|
|
Packit |
33f14e |
{
|
|
Packit |
33f14e |
if (*haystack == '\0')
|
|
Packit |
33f14e |
/* No match. */
|
|
Packit |
33f14e |
return NULL;
|
|
Packit |
33f14e |
|
|
Packit |
33f14e |
/* See whether it's advisable to use an asymptotically faster
|
|
Packit |
33f14e |
algorithm. */
|
|
Packit |
33f14e |
if (try_kmp
|
|
Packit |
33f14e |
&& outer_loop_count >= 10
|
|
Packit |
33f14e |
&& comparison_count >= 5 * outer_loop_count)
|
|
Packit |
33f14e |
{
|
|
Packit |
33f14e |
/* See if needle + comparison_count now reaches the end of
|
|
Packit |
33f14e |
needle. */
|
|
Packit |
33f14e |
if (needle_last_ccount != NULL)
|
|
Packit |
33f14e |
{
|
|
Packit |
33f14e |
needle_last_ccount +=
|
|
Packit |
33f14e |
strnlen (needle_last_ccount,
|
|
Packit |
33f14e |
comparison_count - last_ccount);
|
|
Packit |
33f14e |
if (*needle_last_ccount == '\0')
|
|
Packit |
33f14e |
needle_last_ccount = NULL;
|
|
Packit |
33f14e |
last_ccount = comparison_count;
|
|
Packit |
33f14e |
}
|
|
Packit |
33f14e |
if (needle_last_ccount == NULL)
|
|
Packit |
33f14e |
{
|
|
Packit |
33f14e |
/* Try the Knuth-Morris-Pratt algorithm. */
|
|
Packit |
33f14e |
const unsigned char *result;
|
|
Packit |
33f14e |
bool success =
|
|
Packit |
33f14e |
knuth_morris_pratt ((const unsigned char *) haystack,
|
|
Packit |
33f14e |
(const unsigned char *) (needle - 1),
|
|
Packit |
33f14e |
strlen (needle - 1),
|
|
Packit |
33f14e |
&result);
|
|
Packit |
33f14e |
if (success)
|
|
Packit |
33f14e |
return (char *) result;
|
|
Packit |
33f14e |
try_kmp = false;
|
|
Packit |
33f14e |
}
|
|
Packit |
33f14e |
}
|
|
Packit |
33f14e |
|
|
Packit |
33f14e |
outer_loop_count++;
|
|
Packit |
33f14e |
comparison_count++;
|
|
Packit |
33f14e |
if (*haystack == b)
|
|
Packit |
33f14e |
/* The first character matches. */
|
|
Packit |
33f14e |
{
|
|
Packit |
33f14e |
const char *rhaystack = haystack + 1;
|
|
Packit |
33f14e |
const char *rneedle = needle;
|
|
Packit |
33f14e |
|
|
Packit |
33f14e |
for (;; rhaystack++, rneedle++)
|
|
Packit |
33f14e |
{
|
|
Packit |
33f14e |
if (*rneedle == '\0')
|
|
Packit |
33f14e |
/* Found a match. */
|
|
Packit |
33f14e |
return (char *) haystack;
|
|
Packit |
33f14e |
if (*rhaystack == '\0')
|
|
Packit |
33f14e |
/* No match. */
|
|
Packit |
33f14e |
return NULL;
|
|
Packit |
33f14e |
comparison_count++;
|
|
Packit |
33f14e |
if (*rhaystack != *rneedle)
|
|
Packit |
33f14e |
/* Nothing in this round. */
|
|
Packit |
33f14e |
break;
|
|
Packit |
33f14e |
}
|
|
Packit |
33f14e |
}
|
|
Packit |
33f14e |
}
|
|
Packit |
33f14e |
}
|
|
Packit |
33f14e |
else
|
|
Packit |
33f14e |
return (char *) haystack;
|
|
Packit |
33f14e |
}
|
|
Packit |
33f14e |
}
|