hi monks, here comes another implementation of the Levenshtein Distance; a distance metric which measures the similarities of strings.

Info and some other implementations can be found at Levenshtein distance: calculating similarity of strings.

At the moment I need to compare two sets of strings where each set consists of approximately 2000 strings, which means approximataley 3-4 million measurements. Thus I wrote this code, in which I tried to minimize the memory usage, to make it more efficient. 

sub ldist {
    my @s = split //, shift;
    my @t = split //, shift;

    return scalar @t if scalar @s == 0;
    return scalar @s if scalar @t == 0;

    my (@prevColumn, @currColumn);

    @prevColumn = 0..scalar(@t);

    for my $s (0..$#s) {
        @currColumn = ( $s + 1 );
        for my $t (0..$#t) {
            push @currColumn, min(
                $currColumn[$t] + 1
                , $prevColumn[$t+1] + 1
                , $prevColumn[$t] + ($s[$s] eq $t[$t] ? 0 : 1)
            );
        }
        @prevColumn = @currColumn;
    }

    pop @currColumn
}

sub min {
    my $min = shift;

    for (@_) {
        $min = $_ if $_ < $min;
    }

    $min;
}

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In reply to measuring the similarity between strings by mayaTheCat

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