function difference(first, second, maxLenDelta) {
        if (maxLenDelta === void 0) { maxLenDelta = 4; }
        var lengthDifference = Math.abs(first.length - second.length);
        // We only compute score if length of the currentWord and length of entry.name are similar.
        if (lengthDifference > maxLenDelta) {
            return 0;
        }
        // Initialize LCS (largest common subsequence) matrix.
        var LCS = [];
        var zeroArray = [];
        var i, j;
        for (i = 0; i < second.length + 1; ++i) {
            zeroArray.push(0);
        }
        for (i = 0; i < first.length + 1; ++i) {
            LCS.push(zeroArray);
        }
        for (i = 1; i < first.length + 1; ++i) {
            for (j = 1; j < second.length + 1; ++j) {
                if (first[i - 1] === second[j - 1]) {
                    LCS[i][j] = LCS[i - 1][j - 1] + 1;
                }
                else {
                    LCS[i][j] = Math.max(LCS[i - 1][j], LCS[i][j - 1]);
                }
            }
        }
        return LCS[first.length][second.length] - Math.sqrt(lengthDifference);
    }
Computes the difference score for two strings. More similar strings have a higher score.
We use largest common subsequence dynamic programming approach but penalize in the end for length differences.
Strings that have a large length difference will get a bad default score 0.
Complexity - both time and space O(first.length * second.length)
Dynamic programming LCS computation http://en.wikipedia.org/wiki/Longest_common_subsequence_problem

@param first a string
@param second a string