Algorithm - Max Sum (Java)

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package chimomo.learning.java.algorithm;

import java.util.Random;

/**
 * @author Created by Chimomo
 */
public final class MaxSum {
    static private int seqStart = 0;
    static private int seqEnd = -1;
    private static Random rand = new Random();

    /**
     * Cubic maximum contiguous sub sequence sum algorithm.
     * seqStart and seqEnd represent the actual best sequence.
     */
    public static int maxSubSum1(int[] a) {
        int maxSum = 0;

        for (int i = 0; i < a.length; i++) {
            for (int j = i; j < a.length; j++) {
                int thisSum = 0;

                for (int k = i; k <= j; k++) {
                    thisSum += a[k];
                }

                if (thisSum > maxSum) {
                    maxSum = thisSum;
                    seqStart = i;
                    seqEnd = j;
                }
            }
        }

        return maxSum;
    }

    /**
     * Quadratic maximum contiguous sub sequence sum algorithm.
     * seqStart and seqEnd represent the actual best sequence.
     */
    public static int maxSubSum2(int[] a) {
        int maxSum = 0;

        for (int i = 0; i < a.length; i++) {
            int thisSum = 0;
            for (int j = i; j < a.length; j++) {
                thisSum += a[j];

                if (thisSum > maxSum) {
                    maxSum = thisSum;
                    seqStart = i;
                    seqEnd = j;
                }
            }
        }

        return maxSum;
    }

    /**
     * Linear-time maximum contiguous sub sequence sum algorithm.
     * seqStart and seqEnd represent the actual best sequence.
     */
    public static int maxSubSum4(int[] a) {
        int maxSum = 0;
        int thisSum = 0;

        for (int i = 0, j = 0; j < a.length; j++) {
            thisSum += a[j];

            if (thisSum > maxSum) {
                maxSum = thisSum;
                seqStart = i;
                seqEnd = j;
            } else if (thisSum < 0) {
                i = j + 1;
                thisSum = 0;
            }
        }

        return maxSum;
    }

    /**
     * Recursive maximum contiguous sub sequence sum algorithm.
     * Finds maximum sum in subarray spanning a[left...right].
     * Does not attempt to maintain actual best sequence.
     */
    private static int maxSumRec(int[] a, int left, int right) {
        int maxLeftBorderSum = 0, maxRightBorderSum = 0;
        int leftBorderSum = 0, rightBorderSum = 0;
        int center = (left + right) / 2;

        // Base case.
        if (left == right) {
            return a[left] > 0 ? a[left] : 0;
        }

        int maxLeftSum = maxSumRec(a, left, center);
        int maxRightSum = maxSumRec(a, center + 1, right);

        for (int i = center; i >= left; i--) {
            leftBorderSum += a[i];
            if (leftBorderSum > maxLeftBorderSum) {
                maxLeftBorderSum = leftBorderSum;
            }
        }

        for (int i = center + 1; i <= right; i++) {
            rightBorderSum += a[i];
            if (rightBorderSum > maxRightBorderSum) {
                maxRightBorderSum = rightBorderSum;
            }
        }

        return max3(maxLeftSum, maxRightSum, maxLeftBorderSum + maxRightBorderSum);
    }

    /**
     * Return maximum of three integers.
     */
    private static int max3(int a, int b, int c) {
        return a > b ? a > c ? a : c : b > c ? b : c;
    }

    /**
     * Driver for divide-and-conquer maximum contiguous sub sequence sum algorithm.
     */
    public static int maxSubSum3(int[] a) {
        return a.length > 0 ? maxSumRec(a, 0, a.length - 1) : 0;
    }

    public static void getTimingInfo(int n, int alg) {
        int[] test = new int[n];
        long startTime = System.currentTimeMillis();
        long totalTime = 0;

        int i;
        for (i = 0; totalTime < 4000; i++) {
            for (int j = 0; j < test.length; j++) {
                test[j] = rand.nextInt(100) - 50;
            }

            switch (alg) {
                case 1:
                    maxSubSum1(test);
                    break;
                case 2:
                    maxSubSum2(test);
                    break;
                case 3:
                    maxSubSum3(test);
                    break;
                case 4:
                    maxSubSum4(test);
                    break;
            }

            totalTime = System.currentTimeMillis() - startTime;
        }

        System.out.print(String.format("\t%12.6f", (totalTime * 1000 / i) / (double) 1000000));
    }

    /**
     * Simple test program.
     */
    public static void main(String[] args) {
        int a[] = {4, -3, 5, -2, -1, 2, 6, -2};
        int maxSum;

        maxSum = maxSubSum1(a);
        System.out.println("Max sum is " + maxSum + "; it goes" + " from " + seqStart + " to " + seqEnd);
        maxSum = maxSubSum2(a);
        System.out.println("Max sum is " + maxSum + "; it goes" + " from " + seqStart + " to " + seqEnd);
        maxSum = maxSubSum3(a);
        System.out.println("Max sum is " + maxSum);
        maxSum = maxSubSum4(a);
        System.out.println("Max sum is " + maxSum + "; it goes" + " from " + seqStart + " to " + seqEnd);

        // Get timing info for each algorithm.
        for (int n = 100; n <= 1000000; n *= 10) {
            System.out.print(String.format("N = %7d", n));

            for (int alg = 1; alg <= 4; alg++) {
                if (alg == 1 && n > 50000) {
                    System.out.print("\t      NA    ");
                    continue;
                }
                getTimingInfo(n, alg);
            }

            System.out.println();
        }
    }
}

/*
Output:
Max sum is 11; it goes from 0 to 6
Max sum is 11; it goes from 0 to 6
Max sum is 11
Max sum is 11; it goes from 0 to 6
N =     100	    0.000058	    0.000003	    0.000003	    0.000001
N =    1000	    0.060757	    0.000209	    0.000034	    0.000014
N =   10000	   61.865000	    0.019362	    0.000366	    0.000138
N =  100000	      NA    	    2.005500	    0.004207	    0.001356
N = 1000000	      NA    	  208.041000	    0.042062	    0.013916

*/