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authorThomas Graf <tgraf@suug.ch>2005-06-23 23:58:37 -0400
committerDavid S. Miller <davem@davemloft.net>2005-06-23 23:58:37 -0400
commitdf3fb93ad9ec0b20c785c0ad82d42d159a1af272 (patch)
treee29ba25f55cb77e24310999a949b433e98d7656e /lib/ts_kmp.c
parent2de4ff7bd658c97fb357efa3095a509674dacb5a (diff)
[LIB]: Knuth-Morris-Pratt textsearch algorithm
Implements a linear-time string-matching algorithm due to Knuth, Morris, and Pratt [1]. Their algorithm avoids the explicit computation of the transition function DELTA altogether. Its matching time is O(n), for n being length(text), using just an auxiliary function PI[1..m], for m being length(pattern), precomputed from the pattern in time O(m). The array PI allows the transition function DELTA to be computed efficiently "on the fly" as needed. Roughly speaking, for any state "q" = 0,1,...,m and any character "a" in SIGMA, the value PI["q"] contains the information that is independent of "a" and is needed to compute DELTA("q", "a") [2]. Since the array PI has only m entries, whereas DELTA has O(m|SIGMA|) entries, we save a factor of |SIGMA| in the preprocessing time by computing PI rather than DELTA. [1] Cormen, Leiserson, Rivest, Stein Introdcution to Algorithms, 2nd Edition, MIT Press [2] See finite automation theory Signed-off-by: Thomas Graf <tgraf@suug.ch> Signed-off-by: David S. Miller <davem@davemloft.net>
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diff --git a/lib/ts_kmp.c b/lib/ts_kmp.c
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1/*
2 * lib/ts_kmp.c Knuth-Morris-Pratt text search implementation
3 *
4 * This program is free software; you can redistribute it and/or
5 * modify it under the terms of the GNU General Public License
6 * as published by the Free Software Foundation; either version
7 * 2 of the License, or (at your option) any later version.
8 *
9 * Authors: Thomas Graf <tgraf@suug.ch>
10 *
11 * ==========================================================================
12 *
13 * Implements a linear-time string-matching algorithm due to Knuth,
14 * Morris, and Pratt [1]. Their algorithm avoids the explicit
15 * computation of the transition function DELTA altogether. Its
16 * matching time is O(n), for n being length(text), using just an
17 * auxiliary function PI[1..m], for m being length(pattern),
18 * precomputed from the pattern in time O(m). The array PI allows
19 * the transition function DELTA to be computed efficiently
20 * "on the fly" as needed. Roughly speaking, for any state
21 * "q" = 0,1,...,m and any character "a" in SIGMA, the value
22 * PI["q"] contains the information that is independent of "a" and
23 * is needed to compute DELTA("q", "a") [2]. Since the array PI
24 * has only m entries, whereas DELTA has O(m|SIGMA|) entries, we
25 * save a factor of |SIGMA| in the preprocessing time by computing
26 * PI rather than DELTA.
27 *
28 * [1] Cormen, Leiserson, Rivest, Stein
29 * Introdcution to Algorithms, 2nd Edition, MIT Press
30 * [2] See finite automation theory
31 */
32
33#include <linux/config.h>
34#include <linux/module.h>
35#include <linux/types.h>
36#include <linux/string.h>
37#include <linux/textsearch.h>
38
39struct ts_kmp
40{
41 u8 * pattern;
42 unsigned int pattern_len;
43 unsigned int prefix_tbl[0];
44};
45
46static unsigned int kmp_find(struct ts_config *conf, struct ts_state *state)
47{
48 struct ts_kmp *kmp = ts_config_priv(conf);
49 unsigned int i, q = 0, text_len, consumed = state->offset;
50 const u8 *text;
51
52 for (;;) {
53 text_len = conf->get_next_block(consumed, &text, conf, state);
54
55 if (unlikely(text_len == 0))
56 break;
57
58 for (i = 0; i < text_len; i++) {
59 while (q > 0 && kmp->pattern[q] != text[i])
60 q = kmp->prefix_tbl[q - 1];
61 if (kmp->pattern[q] == text[i])
62 q++;
63 if (unlikely(q == kmp->pattern_len)) {
64 state->offset = consumed + i + 1;
65 return state->offset - kmp->pattern_len;
66 }
67 }
68
69 consumed += text_len;
70 }
71
72 return UINT_MAX;
73}
74
75static inline void compute_prefix_tbl(const u8 *pattern, unsigned int len,
76 unsigned int *prefix_tbl)
77{
78 unsigned int k, q;
79
80 for (k = 0, q = 1; q < len; q++) {
81 while (k > 0 && pattern[k] != pattern[q])
82 k = prefix_tbl[k-1];
83 if (pattern[k] == pattern[q])
84 k++;
85 prefix_tbl[q] = k;
86 }
87}
88
89static struct ts_config *kmp_init(const void *pattern, unsigned int len,
90 int gfp_mask)
91{
92 struct ts_config *conf;
93 struct ts_kmp *kmp;
94 unsigned int prefix_tbl_len = len * sizeof(unsigned int);
95 size_t priv_size = sizeof(*kmp) + len + prefix_tbl_len;
96
97 conf = alloc_ts_config(priv_size, gfp_mask);
98 if (IS_ERR(conf))
99 return conf;
100
101 kmp = ts_config_priv(conf);
102 kmp->pattern_len = len;
103 compute_prefix_tbl(pattern, len, kmp->prefix_tbl);
104 kmp->pattern = (u8 *) kmp->prefix_tbl + prefix_tbl_len;
105 memcpy(kmp->pattern, pattern, len);
106
107 return conf;
108}
109
110static void *kmp_get_pattern(struct ts_config *conf)
111{
112 struct ts_kmp *kmp = ts_config_priv(conf);
113 return kmp->pattern;
114}
115
116static unsigned int kmp_get_pattern_len(struct ts_config *conf)
117{
118 struct ts_kmp *kmp = ts_config_priv(conf);
119 return kmp->pattern_len;
120}
121
122static struct ts_ops kmp_ops = {
123 .name = "kmp",
124 .find = kmp_find,
125 .init = kmp_init,
126 .get_pattern = kmp_get_pattern,
127 .get_pattern_len = kmp_get_pattern_len,
128 .owner = THIS_MODULE,
129 .list = LIST_HEAD_INIT(kmp_ops.list)
130};
131
132static int __init init_kmp(void)
133{
134 return textsearch_register(&kmp_ops);
135}
136
137static void __exit exit_kmp(void)
138{
139 textsearch_unregister(&kmp_ops);
140}
141
142MODULE_LICENSE("GPL");
143
144module_init(init_kmp);
145module_exit(exit_kmp);