LevenshteinDistance.cs

public static class LevenshteinDistance
{
    /// <summary>
    /// Compute the distance between two strings.
    /// The distance between the strings is defined as the minimum 
    /// number of edits needed to transform one string into the other, 
    /// with the allowable edit operations being insertion, deletion, 
    /// or substitution of a single character.
    /// </summary>
    public static int CalculateDistance(string s, string t)
    {
        int n = s.Length;
        int m = t.Length;
        int[,] d = new int[n + 1, m + 1];

        if (s == t) { return 0; }
        if (n == 0) { return m; }
        if (m == 0) { return n; }

        for (int i = 0; i <= n; d[i, 0] = i++) {}
        for (int i = 0; i <= m; d[0, i] = i++) {}

        for (int i = 1; i <= n; i++)
        {
            for (int j = 1; j <= m; j++)
            {
                int cost = (t[j - 1] == s[i - 1]) ? 0 : 1;
                d[i, j] = Math.Min(Math.Min(d[i - 1, j] + 1, d[i, j - 1] + 1), d[i - 1, j - 1] + cost);
            }
        }
        return d[n, m];
    }

    /// <summary>
    /// Gets the similarity between 2 strings as a fractional value between [0, 1].
    /// </summary>
    /// <returns>
    /// Returns relation scores as a percentage in the [0, 1] range, 
    /// which means that if the score gets a maximum value (equal to 1) 
    /// then the two string are absolutely similar
    /// </returns>
    public static double GetSimilarity(String s1, String s2)
    {
        if (s1 == null || s2 == null)
        {
            return 0d;
        }

        double distance =  CalculateDistance(s1, s2);
        double maxLength = Math.Max(s1.Length, s2.Length);

        if (maxLength == 0d)
        {
            return 1d;
        }
        return 1d - (distance / maxLength);
    }
}