Why isnt this Divide and Conquer AC solution faster than Binary Search?

  • 0

    Isnt this using O(lgN) complexity?

    public int findPeakElementDNC(int[] nums, int lo, int hi ) {
        if ( lo < hi ) {
            int mid = (hi + lo)/2;
            int peakLower = findPeakElementDNC( nums, lo, mid );
            int peakHigher = findPeakElementDNC( nums, mid + 1, hi );
            if ( nums[ peakLower ] < nums[ peakHigher ] ) {
                return peakHigher;
            } else {
                return peakLower;
        } else {
            return lo;

  • 1

    I had a similiar AC solution,

    public class Solution {
    int solve(int[] nums, int l, int r){
        int mid = l+(r-l)/2;
        if(l > r) return -1;
        if(mid == 0)
            if(nums[mid] > nums[mid+1]) return mid;
            else return solve(nums, mid+1, r);
        else if(mid == nums.length-1)
            if(nums[mid] > nums[mid-1]) return mid;
            else return solve(nums, l, mid-1);
        else if(nums[mid] > nums[mid-1] && nums[mid] > nums[mid+1]) return mid;
        else return Math.max(solve(nums, l, mid-1), solve(nums, mid+1, r));
    public int findPeakElement(int[] nums) {
        int n = nums.length;
        if(n == 1) return 0;
        else return solve(nums, 0, nums.length-1);    


    and I also had the same question. Once I thought about it more though I realized this is not an O(logN) solution but it is in fact an O(N) solution. For each of the logN splits we make 2 recursive calls which gives us O(2^(logN)) = O(N). I had to think about it because I was wondering the same thing while thinking about this problem so do correct me if I am wrong anybody.

  • 0

    Yea your right, it is a O(N) solution. I remembered much later that such recursions complexity can be solved by the Master method. You can check the video explaining it here https://www.youtube.com/watch?v=pXED5yrNyMg. The solution is pretty much simple substitution into the formula after that.

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