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I am trying to find max value of an array, firstly i am shorting my array min to max after that i am using array[array.length-1] Is this logic efficient in large arrays?

public static int findMax(int[] array){


    int max = array[array.length-1];

    return max;
}//end method
share|improve this question
The best find max algorithm on an array is an iteration with O(n). To get any better you need to be using a more efficient data structure than a straight array, like a self balancing binary tree or any of a number of other data structures which maintain a form of ordering for you. or you can always memoize the max. –  Jimmy Hoffa Nov 24 '12 at 21:15
May not be efficient for the computer, but in terms of SLOC and maintainability it's pretty good compared to the suggested alternates.... –  mattnz Nov 25 '12 at 2:57

2 Answers 2

up vote 1 down vote accepted

No it's not.


That line alone has an O(nlogn) running time. It can result in as many iterations as n, where n is the number of elements in the array, multiplied by log base 2 of n.

It would be much faster to just iterate through the array once.

public static int findMax(int[] array) {
    int indexOfMax = 0;
    for (i=1; i < array.length; i++) {
        if (array[i] > array[indexOfMax] {
            indexOfMax = i;
    return indexOfMax

That has a maximum running time as O(n).

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-1 For gross misrepresentation of big O. First off, when discussing sorting algorithms, n is (usually) the number of comparisons, not the number of iterations through the array. Also, O(n log n) does not mean "as many as n times log_2 n", it means "For some constants c, b: the number is less than c * n * log_b n (for all n > some constant N_0)". It might as well be 5 * n * log_9(n) for n > 1000. –  delnan Nov 24 '12 at 23:19
@delnan: I would not call his claim of O(n log n) running time to be a 'gross misrepresentation of big O'. This is exactly the sort of stuff big O is used for, and he cited it properly. –  whatsisname Nov 25 '12 at 6:49
Delnan is correct. However, my intention was to simplify things for the OP, who clearly has no CS education at all. And for an implementation of a library sort function, the base of the logarithm will invariably be 2. –  user16764 Nov 25 '12 at 8:50
@whatsisname He cited the right complexity but then interpreted it completely wrong. That doesn't help OP either, it just spreads misconceptions. I agree that my formulation is probably not useful for beginners. A more correct explanation that's even simpler is that it'll generally perform more work (than an O(n) algorithm) and is hence slower. –  delnan Nov 25 '12 at 12:19
Delnan, honestly. Just edit the answer if you think you can improve it. –  user16764 Nov 25 '12 at 18:45

Cleaner implementation of the accepted answer:

public static int findMax(int[] array) {

    // TODO: Take appropriate action if the array is empty.

    int max_value = Integer.MIN_VALUE;

    for ( int value : array ) {
        if ( value > max_value ) {
            max_value = value;

    return max_value;
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