[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>

1 files changed, 145 insertions, 0 deletions

diff --git a/lib/ts_kmp.c b/lib/ts_kmp.c
new file mode 100644
index 000000000000..73266b975585
--- /dev/null
+++ b/lib/ts_kmp.c
@@ -0,0 +1,145 @@
+/*
+ * lib/ts_kmp.c		Knuth-Morris-Pratt text search implementation
+ *
+ *		This program is free software; you can redistribute it and/or
+ *		modify it under the terms of the GNU General Public License
+ *		as published by the Free Software Foundation; either version
+ *		2 of the License, or (at your option) any later version.
+ *
+ * Authors:	Thomas Graf <tgraf@suug.ch>
+ *
+ * ==========================================================================
+ * 
+ *   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
+ */
+
+#include <linux/config.h>
+#include <linux/module.h>
+#include <linux/types.h>
+#include <linux/string.h>
+#include <linux/textsearch.h>
+
+struct ts_kmp
+{
+	u8 *		pattern;
+	unsigned int	pattern_len;
+	unsigned int 	prefix_tbl[0];
+};
+
+static unsigned int kmp_find(struct ts_config *conf, struct ts_state *state)
+{
+	struct ts_kmp *kmp = ts_config_priv(conf);
+	unsigned int i, q = 0, text_len, consumed = state->offset;
+	const u8 *text;
+
+	for (;;) {
+		text_len = conf->get_next_block(consumed, &text, conf, state);
+
+		if (unlikely(text_len == 0))
+			break;
+
+		for (i = 0; i < text_len; i++) {
+			while (q > 0 && kmp->pattern[q] != text[i])
+				q = kmp->prefix_tbl[q - 1];
+			if (kmp->pattern[q] == text[i])
+				q++;
+			if (unlikely(q == kmp->pattern_len)) {
+				state->offset = consumed + i + 1;
+				return state->offset - kmp->pattern_len;
+			}
+		}
+
+		consumed += text_len;
+	}
+
+	return UINT_MAX;
+}
+
+static inline void compute_prefix_tbl(const u8 *pattern, unsigned int len,
+				      unsigned int *prefix_tbl)
+{
+	unsigned int k, q;
+
+	for (k = 0, q = 1; q < len; q++) {
+		while (k > 0 && pattern[k] != pattern[q])
+			k = prefix_tbl[k-1];
+		if (pattern[k] == pattern[q])
+			k++;
+		prefix_tbl[q] = k;
+	}
+}
+
+static struct ts_config *kmp_init(const void *pattern, unsigned int len,
+				  int gfp_mask)
+{
+	struct ts_config *conf;
+	struct ts_kmp *kmp;
+	unsigned int prefix_tbl_len = len * sizeof(unsigned int);
+	size_t priv_size = sizeof(*kmp) + len + prefix_tbl_len;
+
+	conf = alloc_ts_config(priv_size, gfp_mask);
+	if (IS_ERR(conf))
+		return conf;
+
+	kmp = ts_config_priv(conf);
+	kmp->pattern_len = len;
+	compute_prefix_tbl(pattern, len, kmp->prefix_tbl);
+	kmp->pattern = (u8 *) kmp->prefix_tbl + prefix_tbl_len;
+	memcpy(kmp->pattern, pattern, len);
+
+	return conf;
+}
+
+static void *kmp_get_pattern(struct ts_config *conf)
+{
+	struct ts_kmp *kmp = ts_config_priv(conf);
+	return kmp->pattern;
+}
+
+static unsigned int kmp_get_pattern_len(struct ts_config *conf)
+{
+	struct ts_kmp *kmp = ts_config_priv(conf);
+	return kmp->pattern_len;
+}
+
+static struct ts_ops kmp_ops = {
+	.name		  = "kmp",
+	.find		  = kmp_find,
+	.init		  = kmp_init,
+	.get_pattern	  = kmp_get_pattern,
+	.get_pattern_len  = kmp_get_pattern_len,
+	.owner		  = THIS_MODULE,
+	.list		  = LIST_HEAD_INIT(kmp_ops.list)
+};
+
+static int __init init_kmp(void)
+{
+	return textsearch_register(&kmp_ops);
+}
+
+static void __exit exit_kmp(void)
+{
+	textsearch_unregister(&kmp_ops);
+}
+
+MODULE_LICENSE("GPL");
+
+module_init(init_kmp);
+module_exit(exit_kmp);