summaryrefslogtreecommitdiff
path: root/lib/mbsstr.c
blob: 03fb7045e31f439fb1fce8ad59a0f198a61a1623 (plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
/* Searching in a string.  -*- coding: utf-8 -*-
   Copyright (C) 2005-2023 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 <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;
    }
}