compute(sequence1, sequence2, timeout = InfiniteTimeout.instance, equalityScore) {
        if (sequence1.length === 0 || sequence2.length === 0) {
            return DiffAlgorithmResult.trivial(sequence1, sequence2);
        }
        /**
         * lcsLengths.get(i, j): Length of the longest common subsequence of sequence1.substring(0, i + 1) and sequence2.substring(0, j + 1).
         */
        const lcsLengths = new Array2D(sequence1.length, sequence2.length);
        const directions = new Array2D(sequence1.length, sequence2.length);
        const lengths = new Array2D(sequence1.length, sequence2.length);
        // ==== Initializing lcsLengths ====
        for (let s1 = 0; s1 < sequence1.length; s1++) {
            for (let s2 = 0; s2 < sequence2.length; s2++) {
                if (!timeout.isValid()) {
                    return DiffAlgorithmResult.trivialTimedOut(sequence1, sequence2);
                }
                const horizontalLen = s1 === 0 ? 0 : lcsLengths.get(s1 - 1, s2);
                const verticalLen = s2 === 0 ? 0 : lcsLengths.get(s1, s2 - 1);
                let extendedSeqScore;
                if (sequence1.getElement(s1) === sequence2.getElement(s2)) {
                    if (s1 === 0 || s2 === 0) {
                        extendedSeqScore = 0;
                    }
                    else {
                        extendedSeqScore = lcsLengths.get(s1 - 1, s2 - 1);
                    }
                    if (s1 > 0 && s2 > 0 && directions.get(s1 - 1, s2 - 1) === 3) {
                        // Prefer consecutive diagonals
                        extendedSeqScore += lengths.get(s1 - 1, s2 - 1);
                    }
                    extendedSeqScore += (equalityScore ? equalityScore(s1, s2) : 1);
                }
                else {
                    extendedSeqScore = -1;
                }
                const newValue = Math.max(horizontalLen, verticalLen, extendedSeqScore);
                if (newValue === extendedSeqScore) {
                    // Prefer diagonals
                    const prevLen = s1 > 0 && s2 > 0 ? lengths.get(s1 - 1, s2 - 1) : 0;
                    lengths.set(s1, s2, prevLen + 1);
                    directions.set(s1, s2, 3);
                }
                else if (newValue === horizontalLen) {
                    lengths.set(s1, s2, 0);
                    directions.set(s1, s2, 1);
                }
                else if (newValue === verticalLen) {
                    lengths.set(s1, s2, 0);
                    directions.set(s1, s2, 2);
                }
                lcsLengths.set(s1, s2, newValue);
            }
        }
        // ==== Backtracking ====
        const result = [];
        let lastAligningPosS1 = sequence1.length;
        let lastAligningPosS2 = sequence2.length;
        function reportDecreasingAligningPositions(s1, s2) {
            if (s1 + 1 !== lastAligningPosS1 || s2 + 1 !== lastAligningPosS2) {
                result.push(new SequenceDiff(new OffsetRange(s1 + 1, lastAligningPosS1), new OffsetRange(s2 + 1, lastAligningPosS2)));
            }
            lastAligningPosS1 = s1;
            lastAligningPosS2 = s2;
        }
        let s1 = sequence1.length - 1;
        let s2 = sequence2.length - 1;
        while (s1 >= 0 && s2 >= 0) {
            if (directions.get(s1, s2) === 3) {
                reportDecreasingAligningPositions(s1, s2);
                s1--;
                s2--;
            }
            else {
                if (directions.get(s1, s2) === 1) {
                    s1--;
                }
                else {
                    s2--;
                }
            }
        }
        reportDecreasingAligningPositions(-1, -1);
        result.reverse();
        return new DiffAlgorithmResult(result, false);
    }
A O(MN) diffing algorithm that supports a score function.
The algorithm can be improved by processing the 2d array diagonally.