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

/**
 * `levenshtein-rs` - levenshtein
 *
 * MIT licensed.
 *
 * Copyright (c) 2016 Titus Wormer <tituswormer@gmail.com>
 */
pub fn
levenshtein(a: &str, b: &str) -> usize {
  let length_a = a.chars().count();
  let length_b = b.chars().count();
  let mut result = 0;

  /* Shortcut optimizations / degenerate cases. */
  if a == b {
    return result;
  }

  if length_a == 0 {
    return length_b;
  }

  if length_b == 0 {
    return length_a;
  }

  /* Initialize the vector.
   *
   * This is why it’s fast, normally a matrix is used,
   * here we use a single vector. */
  let mut cache: Vec<usize> = vec![0; length_a];
  let mut index_a = 0;
  let mut distance_a;
  let mut distance_b;

  while index_a < length_a {
    index_a = index_a + 1;
    cache[index_a - 1] = index_a;
  }

  /* Loop. */
  for (index_b, code_b) in b.chars().enumerate() {
    result = index_b;
    distance_a = index_b;

    for (index_a, code_a) in a.chars().enumerate() {
      distance_b = if code_a == code_b {
        distance_a
      } else {
        distance_a + 1
      };

      distance_a = cache[index_a];

      result = if distance_a > result {
        if distance_b > result {
          result + 1
        } else {
          distance_b
        }
      } else {
        if distance_b > distance_a {
          distance_a + 1
        } else {
          distance_b
        }
      };

      cache[index_a] = result;
    }
  }

  return result;
}