bc4519eda7
From-SVN: r245404
301 lines
8.9 KiB
C
301 lines
8.9 KiB
C
/* Find near-matches for strings.
|
|
Copyright (C) 2015-2017 Free Software Foundation, Inc.
|
|
|
|
This file is part of GCC.
|
|
|
|
GCC 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 3, or (at your option) any later
|
|
version.
|
|
|
|
GCC 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 General Public License
|
|
for more details.
|
|
|
|
You should have received a copy of the GNU General Public License
|
|
along with GCC; see the file COPYING3. If not see
|
|
<http://www.gnu.org/licenses/>. */
|
|
|
|
#include "config.h"
|
|
#include "system.h"
|
|
#include "coretypes.h"
|
|
#include "tm.h"
|
|
#include "tree.h"
|
|
#include "spellcheck.h"
|
|
#include "selftest.h"
|
|
|
|
/* The Levenshtein distance is an "edit-distance": the minimal
|
|
number of one-character insertions, removals or substitutions
|
|
that are needed to change one string into another.
|
|
|
|
This implementation uses the Wagner-Fischer algorithm. */
|
|
|
|
edit_distance_t
|
|
levenshtein_distance (const char *s, int len_s,
|
|
const char *t, int len_t)
|
|
{
|
|
const bool debug = false;
|
|
|
|
if (debug)
|
|
{
|
|
printf ("s: \"%s\" (len_s=%i)\n", s, len_s);
|
|
printf ("t: \"%s\" (len_t=%i)\n", t, len_t);
|
|
}
|
|
|
|
if (len_s == 0)
|
|
return len_t;
|
|
if (len_t == 0)
|
|
return len_s;
|
|
|
|
/* We effectively build a matrix where each (i, j) contains the
|
|
Levenshtein distance between the prefix strings s[0:j]
|
|
and t[0:i].
|
|
Rather than actually build an (len_t + 1) * (len_s + 1) matrix,
|
|
we simply keep track of the last row, v0 and a new row, v1,
|
|
which avoids an (len_t + 1) * (len_s + 1) allocation and memory accesses
|
|
in favor of two (len_s + 1) allocations. These could potentially be
|
|
statically-allocated if we impose a maximum length on the
|
|
strings of interest. */
|
|
edit_distance_t *v0 = new edit_distance_t[len_s + 1];
|
|
edit_distance_t *v1 = new edit_distance_t[len_s + 1];
|
|
|
|
/* The first row is for the case of an empty target string, which
|
|
we can reach by deleting every character in the source string. */
|
|
for (int i = 0; i < len_s + 1; i++)
|
|
v0[i] = i;
|
|
|
|
/* Build successive rows. */
|
|
for (int i = 0; i < len_t; i++)
|
|
{
|
|
if (debug)
|
|
{
|
|
printf ("i:%i v0 = ", i);
|
|
for (int j = 0; j < len_s + 1; j++)
|
|
printf ("%i ", v0[j]);
|
|
printf ("\n");
|
|
}
|
|
|
|
/* The initial column is for the case of an empty source string; we
|
|
can reach prefixes of the target string of length i
|
|
by inserting i characters. */
|
|
v1[0] = i + 1;
|
|
|
|
/* Build the rest of the row by considering neighbors to
|
|
the north, west and northwest. */
|
|
for (int j = 0; j < len_s; j++)
|
|
{
|
|
edit_distance_t cost = (s[j] == t[i] ? 0 : 1);
|
|
edit_distance_t deletion = v1[j] + 1;
|
|
edit_distance_t insertion = v0[j + 1] + 1;
|
|
edit_distance_t substitution = v0[j] + cost;
|
|
edit_distance_t cheapest = MIN (deletion, insertion);
|
|
cheapest = MIN (cheapest, substitution);
|
|
v1[j + 1] = cheapest;
|
|
}
|
|
|
|
/* Prepare to move on to next row. */
|
|
for (int j = 0; j < len_s + 1; j++)
|
|
v0[j] = v1[j];
|
|
}
|
|
|
|
if (debug)
|
|
{
|
|
printf ("final v1 = ");
|
|
for (int j = 0; j < len_s + 1; j++)
|
|
printf ("%i ", v1[j]);
|
|
printf ("\n");
|
|
}
|
|
|
|
edit_distance_t result = v1[len_s];
|
|
delete[] v0;
|
|
delete[] v1;
|
|
return result;
|
|
}
|
|
|
|
/* Calculate Levenshtein distance between two nil-terminated strings. */
|
|
|
|
edit_distance_t
|
|
levenshtein_distance (const char *s, const char *t)
|
|
{
|
|
return levenshtein_distance (s, strlen (s), t, strlen (t));
|
|
}
|
|
|
|
/* Given TARGET, a non-NULL string, and CANDIDATES, a non-NULL ptr to
|
|
an autovec of non-NULL strings, determine which element within
|
|
CANDIDATES has the lowest edit distance to TARGET. If there are
|
|
multiple elements with the same minimal distance, the first in the
|
|
vector wins.
|
|
|
|
If more than half of the letters were misspelled, the suggestion is
|
|
likely to be meaningless, so return NULL for this case. */
|
|
|
|
const char *
|
|
find_closest_string (const char *target,
|
|
const auto_vec<const char *> *candidates)
|
|
{
|
|
gcc_assert (target);
|
|
gcc_assert (candidates);
|
|
|
|
int i;
|
|
const char *candidate;
|
|
best_match<const char *, const char *> bm (target);
|
|
FOR_EACH_VEC_ELT (*candidates, i, candidate)
|
|
{
|
|
gcc_assert (candidate);
|
|
bm.consider (candidate);
|
|
}
|
|
|
|
return bm.get_best_meaningful_candidate ();
|
|
}
|
|
|
|
#if CHECKING_P
|
|
|
|
namespace selftest {
|
|
|
|
/* Selftests. */
|
|
|
|
/* Verify that the levenshtein_distance (A, B) equals the expected
|
|
value. */
|
|
|
|
static void
|
|
levenshtein_distance_unit_test_oneway (const char *a, const char *b,
|
|
edit_distance_t expected)
|
|
{
|
|
edit_distance_t actual = levenshtein_distance (a, b);
|
|
ASSERT_EQ (actual, expected);
|
|
}
|
|
|
|
/* Verify that both
|
|
levenshtein_distance (A, B)
|
|
and
|
|
levenshtein_distance (B, A)
|
|
equal the expected value, to ensure that the function is symmetric. */
|
|
|
|
static void
|
|
levenshtein_distance_unit_test (const char *a, const char *b,
|
|
edit_distance_t expected)
|
|
{
|
|
levenshtein_distance_unit_test_oneway (a, b, expected);
|
|
levenshtein_distance_unit_test_oneway (b, a, expected);
|
|
}
|
|
|
|
/* Verify that find_closest_string is sane. */
|
|
|
|
static void
|
|
test_find_closest_string ()
|
|
{
|
|
auto_vec<const char *> candidates;
|
|
|
|
/* Verify that it can handle an empty vec. */
|
|
ASSERT_EQ (NULL, find_closest_string ("", &candidates));
|
|
|
|
/* Verify that it works sanely for non-empty vecs. */
|
|
candidates.safe_push ("apple");
|
|
candidates.safe_push ("banana");
|
|
candidates.safe_push ("cherry");
|
|
|
|
ASSERT_STREQ ("apple", find_closest_string ("app", &candidates));
|
|
ASSERT_STREQ ("banana", find_closest_string ("banyan", &candidates));
|
|
ASSERT_STREQ ("cherry", find_closest_string ("berry", &candidates));
|
|
ASSERT_EQ (NULL, find_closest_string ("not like the others", &candidates));
|
|
|
|
/* The order of the vec can matter, but it should not matter for these
|
|
inputs. */
|
|
candidates.truncate (0);
|
|
candidates.safe_push ("cherry");
|
|
candidates.safe_push ("banana");
|
|
candidates.safe_push ("apple");
|
|
ASSERT_STREQ ("apple", find_closest_string ("app", &candidates));
|
|
ASSERT_STREQ ("banana", find_closest_string ("banyan", &candidates));
|
|
ASSERT_STREQ ("cherry", find_closest_string ("berry", &candidates));
|
|
ASSERT_EQ (NULL, find_closest_string ("not like the others", &candidates));
|
|
|
|
/* If the goal string somehow makes it into the candidate list, offering
|
|
it as a suggestion will be nonsensical. Verify that we don't offer such
|
|
suggestions. */
|
|
ASSERT_EQ (NULL, find_closest_string ("banana", &candidates));
|
|
}
|
|
|
|
/* Test data for test_metric_conditions. */
|
|
|
|
static const char * const test_data[] = {
|
|
"",
|
|
"foo",
|
|
"food",
|
|
"boo",
|
|
"1234567890123456789012345678901234567890123456789012345678901234567890"
|
|
};
|
|
|
|
/* Verify that levenshtein_distance appears to be a sane distance function,
|
|
i.e. the conditions for being a metric. This is done directly for a
|
|
small set of examples, using test_data above. This is O(N^3) in the size
|
|
of the array, due to the test for the triangle inequality, so we keep the
|
|
array small. */
|
|
|
|
static void
|
|
test_metric_conditions ()
|
|
{
|
|
const int num_test_cases = sizeof (test_data) / sizeof (test_data[0]);
|
|
|
|
for (int i = 0; i < num_test_cases; i++)
|
|
{
|
|
for (int j = 0; j < num_test_cases; j++)
|
|
{
|
|
edit_distance_t dist_ij
|
|
= levenshtein_distance (test_data[i], test_data[j]);
|
|
|
|
/* Identity of indiscernibles: d(i, j) > 0 iff i == j. */
|
|
if (i == j)
|
|
ASSERT_EQ (dist_ij, 0);
|
|
else
|
|
ASSERT_TRUE (dist_ij > 0);
|
|
|
|
/* Symmetry: d(i, j) == d(j, i). */
|
|
edit_distance_t dist_ji
|
|
= levenshtein_distance (test_data[j], test_data[i]);
|
|
ASSERT_EQ (dist_ij, dist_ji);
|
|
|
|
/* Triangle inequality. */
|
|
for (int k = 0; k < num_test_cases; k++)
|
|
{
|
|
edit_distance_t dist_ik
|
|
= levenshtein_distance (test_data[i], test_data[k]);
|
|
edit_distance_t dist_jk
|
|
= levenshtein_distance (test_data[j], test_data[k]);
|
|
ASSERT_TRUE (dist_ik <= dist_ij + dist_jk);
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
/* Verify levenshtein_distance for a variety of pairs of pre-canned
|
|
inputs, comparing against known-good values. */
|
|
|
|
void
|
|
spellcheck_c_tests ()
|
|
{
|
|
levenshtein_distance_unit_test ("", "nonempty", strlen ("nonempty"));
|
|
levenshtein_distance_unit_test ("saturday", "sunday", 3);
|
|
levenshtein_distance_unit_test ("foo", "m_foo", 2);
|
|
levenshtein_distance_unit_test ("hello_world", "HelloWorld", 3);
|
|
levenshtein_distance_unit_test
|
|
("the quick brown fox jumps over the lazy dog", "dog", 40);
|
|
levenshtein_distance_unit_test
|
|
("the quick brown fox jumps over the lazy dog",
|
|
"the quick brown dog jumps over the lazy fox",
|
|
4);
|
|
levenshtein_distance_unit_test
|
|
("Lorem ipsum dolor sit amet, consectetur adipiscing elit,",
|
|
"All your base are belong to us",
|
|
44);
|
|
levenshtein_distance_unit_test ("foo", "FOO", 3);
|
|
|
|
test_find_closest_string ();
|
|
test_metric_conditions ();
|
|
}
|
|
|
|
} // namespace selftest
|
|
|
|
#endif /* #if CHECKING_P */
|