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/* Searching in a string. -*- coding: utf-8 -*-
Copyright (C) 2005-2022 Free Software Foundation, Inc.
Written by Bruno Haible <bruno@clisp.org>, 2005.
This file is free software: you can redistribute it and/or modify
it under the terms of the GNU Lesser General Public License as
published by the Free Software Foundation, either version 3 of the
License, or (at your option) any later version.
This file is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public License
along with this program. If not, see <https://www.gnu.org/licenses/>. */
#include <config.h>
/* Specification. */
#include <string.h>
#include <stdbool.h>
#include <stddef.h> /* for NULL, in case a nonstandard string.h lacks it */
#include <stdlib.h>
#include "malloca.h"
#include "mbuiter.h"
/* Knuth-Morris-Pratt algorithm. */
#define UNIT unsigned char
#define CANON_ELEMENT(c) c
#include "str-kmp.h"
/* Knuth-Morris-Pratt algorithm.
See https://en.wikipedia.org/wiki/Knuth-Morris-Pratt_algorithm
Return a boolean indicating success:
Return true and set *RESULTP if the search was completed.
Return false if it was aborted because not enough memory was available. */
static bool
knuth_morris_pratt_multibyte (const char *haystack, const char *needle,
const char **resultp)
{
size_t m = mbslen (needle);
mbchar_t *needle_mbchars;
size_t *table;
/* Allocate room for needle_mbchars and the table. */
void *memory = nmalloca (m, sizeof (mbchar_t) + sizeof (size_t));
void *table_memory;
if (memory == NULL)
return false;
needle_mbchars = memory;
table_memory = needle_mbchars + m;
table = table_memory;
/* Fill needle_mbchars. */
{
mbui_iterator_t iter;
size_t j;
j = 0;
for (mbui_init (iter, needle); mbui_avail (iter); mbui_advance (iter), j++)
mb_copy (&needle_mbchars[j], &mbui_cur (iter));
}
/* Fill the table.
For 0 < i < m:
0 < table[i] <= i is defined such that
forall 0 < x < table[i]: needle[x..i-1] != needle[0..i-1-x],
and table[i] is as large as possible with this property.
This implies:
1) For 0 < i < m:
If table[i] < i,
needle[table[i]..i-1] = needle[0..i-1-table[i]].
2) For 0 < i < m:
rhaystack[0..i-1] == needle[0..i-1]
and exists h, i <= h < m: rhaystack[h] != needle[h]
implies
forall 0 <= x < table[i]: rhaystack[x..x+m-1] != needle[0..m-1].
table[0] remains uninitialized. */
{
size_t i, j;
/* i = 1: Nothing to verify for x = 0. */
table[1] = 1;
j = 0;
for (i = 2; i < m; i++)
{
/* Here: j = i-1 - table[i-1].
The inequality needle[x..i-1] != needle[0..i-1-x] is known to hold
for x < table[i-1], by induction.
Furthermore, if j>0: needle[i-1-j..i-2] = needle[0..j-1]. */
mbchar_t *b = &needle_mbchars[i - 1];
for (;;)
{
/* Invariants: The inequality needle[x..i-1] != needle[0..i-1-x]
is known to hold for x < i-1-j.
Furthermore, if j>0: needle[i-1-j..i-2] = needle[0..j-1]. */
if (mb_equal (*b, needle_mbchars[j]))
{
/* Set table[i] := i-1-j. */
table[i] = i - ++j;
break;
}
/* The inequality needle[x..i-1] != needle[0..i-1-x] also holds
for x = i-1-j, because
needle[i-1] != needle[j] = needle[i-1-x]. */
if (j == 0)
{
/* The inequality holds for all possible x. */
table[i] = i;
break;
}
/* The inequality needle[x..i-1] != needle[0..i-1-x] also holds
for i-1-j < x < i-1-j+table[j], because for these x:
needle[x..i-2]
= needle[x-(i-1-j)..j-1]
!= needle[0..j-1-(x-(i-1-j))] (by definition of table[j])
= needle[0..i-2-x],
hence needle[x..i-1] != needle[0..i-1-x].
Furthermore
needle[i-1-j+table[j]..i-2]
= needle[table[j]..j-1]
= needle[0..j-1-table[j]] (by definition of table[j]). */
j = j - table[j];
}
/* Here: j = i - table[i]. */
}
}
/* Search, using the table to accelerate the processing. */
{
size_t j;
mbui_iterator_t rhaystack;
mbui_iterator_t phaystack;
*resultp = NULL;
j = 0;
mbui_init (rhaystack, haystack);
mbui_init (phaystack, haystack);
/* Invariant: phaystack = rhaystack + j. */
while (mbui_avail (phaystack))
if (mb_equal (needle_mbchars[j], mbui_cur (phaystack)))
{
j++;
mbui_advance (phaystack);
if (j == m)
{
/* The entire needle has been found. */
*resultp = mbui_cur_ptr (rhaystack);
break;
}
}
else if (j > 0)
{
/* Found a match of needle[0..j-1], mismatch at needle[j]. */
size_t count = table[j];
j -= count;
for (; count > 0; count--)
{
if (!mbui_avail (rhaystack))
abort ();
mbui_advance (rhaystack);
}
}
else
{
/* Found a mismatch at needle[0] already. */
if (!mbui_avail (rhaystack))
abort ();
mbui_advance (rhaystack);
mbui_advance (phaystack);
}
}
freea (memory);
return true;
}
/* Find the first occurrence of the character string NEEDLE in the character
string HAYSTACK. Return NULL if NEEDLE is not found in HAYSTACK. */
char *
mbsstr (const char *haystack, const char *needle)
{
/* Be careful not to look at the entire extent of haystack or needle
until needed. This is useful because of these two cases:
- haystack may be very long, and a match of needle found early,
- needle may be very long, and not even a short initial segment of
needle may be found in haystack. */
if (MB_CUR_MAX > 1)
{
mbui_iterator_t iter_needle;
mbui_init (iter_needle, needle);
if (mbui_avail (iter_needle))
{
/* Minimizing the worst-case complexity:
Let n = mbslen(haystack), m = mbslen(needle).
The naïve algorithm is O(n*m) worst-case.
The Knuth-Morris-Pratt algorithm is O(n) worst-case but it needs a
memory allocation.
To achieve linear complexity and yet amortize the cost of the
memory allocation, we activate the Knuth-Morris-Pratt algorithm
only once the naïve algorithm has already run for some time; more
precisely, when
- the outer loop count is >= 10,
- the average number of comparisons per outer loop is >= 5,
- the total number of comparisons is >= m.
But we try it only once. If the memory allocation attempt failed,
we don't retry it. */
bool try_kmp = true;
size_t outer_loop_count = 0;
size_t comparison_count = 0;
size_t last_ccount = 0; /* last comparison count */
mbui_iterator_t iter_needle_last_ccount; /* = needle + last_ccount */
mbui_iterator_t iter_haystack;
mbui_init (iter_needle_last_ccount, needle);
mbui_init (iter_haystack, haystack);
for (;; mbui_advance (iter_haystack))
{
if (!mbui_avail (iter_haystack))
/* No match. */
return NULL;
/* See whether it's advisable to use an asymptotically faster
algorithm. */
if (try_kmp
&& outer_loop_count >= 10
&& comparison_count >= 5 * outer_loop_count)
{
/* See if needle + comparison_count now reaches the end of
needle. */
size_t count = comparison_count - last_ccount;
for (;
count > 0 && mbui_avail (iter_needle_last_ccount);
count--)
mbui_advance (iter_needle_last_ccount);
last_ccount = comparison_count;
if (!mbui_avail (iter_needle_last_ccount))
{
/* Try the Knuth-Morris-Pratt algorithm. */
const char *result;
bool success =
knuth_morris_pratt_multibyte (haystack, needle,
&result);
if (success)
return (char *) result;
try_kmp = false;
}
}
outer_loop_count++;
comparison_count++;
if (mb_equal (mbui_cur (iter_haystack), mbui_cur (iter_needle)))
/* The first character matches. */
{
mbui_iterator_t rhaystack;
mbui_iterator_t rneedle;
memcpy (&rhaystack, &iter_haystack, sizeof (mbui_iterator_t));
mbui_advance (rhaystack);
mbui_init (rneedle, needle);
if (!mbui_avail (rneedle))
abort ();
mbui_advance (rneedle);
for (;; mbui_advance (rhaystack), mbui_advance (rneedle))
{
if (!mbui_avail (rneedle))
/* Found a match. */
return (char *) mbui_cur_ptr (iter_haystack);
if (!mbui_avail (rhaystack))
/* No match. */
return NULL;
comparison_count++;
if (!mb_equal (mbui_cur (rhaystack), mbui_cur (rneedle)))
/* Nothing in this round. */
break;
}
}
}
}
else
return (char *) haystack;
}
else
{
if (*needle != '\0')
{
/* Minimizing the worst-case complexity:
Let n = strlen(haystack), m = strlen(needle).
The naïve algorithm is O(n*m) worst-case.
The Knuth-Morris-Pratt algorithm is O(n) worst-case but it needs a
memory allocation.
To achieve linear complexity and yet amortize the cost of the
memory allocation, we activate the Knuth-Morris-Pratt algorithm
only once the naïve algorithm has already run for some time; more
precisely, when
- the outer loop count is >= 10,
- the average number of comparisons per outer loop is >= 5,
- the total number of comparisons is >= m.
But we try it only once. If the memory allocation attempt failed,
we don't retry it. */
bool try_kmp = true;
size_t outer_loop_count = 0;
size_t comparison_count = 0;
size_t last_ccount = 0; /* last comparison count */
const char *needle_last_ccount = needle; /* = needle + last_ccount */
/* Speed up the following searches of needle by caching its first
character. */
char b = *needle++;
for (;; haystack++)
{
if (*haystack == '\0')
/* No match. */
return NULL;
/* See whether it's advisable to use an asymptotically faster
algorithm. */
if (try_kmp
&& outer_loop_count >= 10
&& comparison_count >= 5 * outer_loop_count)
{
/* See if needle + comparison_count now reaches the end of
needle. */
if (needle_last_ccount != NULL)
{
needle_last_ccount +=
strnlen (needle_last_ccount,
comparison_count - last_ccount);
if (*needle_last_ccount == '\0')
needle_last_ccount = NULL;
last_ccount = comparison_count;
}
if (needle_last_ccount == NULL)
{
/* Try the Knuth-Morris-Pratt algorithm. */
const unsigned char *result;
bool success =
knuth_morris_pratt ((const unsigned char *) haystack,
(const unsigned char *) (needle - 1),
strlen (needle - 1),
&result);
if (success)
return (char *) result;
try_kmp = false;
}
}
outer_loop_count++;
comparison_count++;
if (*haystack == b)
/* The first character matches. */
{
const char *rhaystack = haystack + 1;
const char *rneedle = needle;
for (;; rhaystack++, rneedle++)
{
if (*rneedle == '\0')
/* Found a match. */
return (char *) haystack;
if (*rhaystack == '\0')
/* No match. */
return NULL;
comparison_count++;
if (*rhaystack != *rneedle)
/* Nothing in this round. */
break;
}
}
}
}
else
return (char *) haystack;
}
}
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