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Median of the two sorted arrays.
Jaspreet singh · 2026-06-22 · via DEV Community

Jaspreet singh

Problem Statement

Given two sorted arrays nums1 and nums2, return the median of the two sorted arrays.

The overall run time complexity should be:

O(log(min(N,M)))


Brute Force Intuition

In an interview, you can explain it like this:

Since both arrays are sorted, we can merge them into a single sorted array and then directly compute the median from the merged array.

Complexity

  • Time Complexity: O(N + M)
  • Space Complexity: O(N + M)

Brute Force Code

int[] merged = new int[n + m];

// Merge both arrays

return median;


Moving Towards the Optimal Approach

Do we really need the merged array?

No.

We only care about:

Left Half
Right Half

such that:

All elements in Left Half
<=
All elements in Right Half

This is where partition-based Binary Search comes in.


Pattern Recognition

Whenever you see:

  • Two Sorted Arrays
  • Median
  • O(log N) expected

Think:

Binary Search on Partition


Key Observation

For total elements:

n + m

Left partition should contain:

(n + m + 1) / 2

elements.

We Binary Search on:

How many elements to take from nums1

Remaining automatically come from nums2.


Optimal Java Solution

class Solution {

    public double findMedianSortedArrays(int[] nums1,
                                         int[] nums2) {

        if (nums1.length > nums2.length)
            return findMedianSortedArrays(nums2, nums1);

        int n1 = nums1.length;
        int n2 = nums2.length;

        int low = 0;
        int high = n1;

        while (low <= high) {

            int cut1 = low + (high - low) / 2;

            int cut2 =
                (n1 + n2 + 1) / 2 - cut1;

            int left1 =
                cut1 == 0 ? Integer.MIN_VALUE
                           : nums1[cut1 - 1];

            int left2 =
                cut2 == 0 ? Integer.MIN_VALUE
                           : nums2[cut2 - 1];

            int right1 =
                cut1 == n1 ? Integer.MAX_VALUE
                            : nums1[cut1];

            int right2 =
                cut2 == n2 ? Integer.MAX_VALUE
                            : nums2[cut2];

            if (left1 <= right2 &&
                left2 <= right1) {

                if ((n1 + n2) % 2 == 0) {

                    return (Math.max(left1, left2)
                          + Math.min(right1, right2))
                          / 2.0;
                }

                return Math.max(left1, left2);
            }

            else if (left1 > right2) {

                high = cut1 - 1;

            } else {

                low = cut1 + 1;
            }
        }

        return 0;
    }
}


Dry Run

Input

nums1 = [1,3]
nums2 = [2]

Total:

3 elements

Need:

2 elements on left side

Partition:

[1] | [3]

[2] |

Check:

left1 <= right2
left2 <= right1

Valid Partition.

Median:

max(1,2)
=
2


Complexity Analysis

Metric Complexity
Time Complexity O(log(min(N,M)))
Space Complexity O(1)

Interview One-Liner

Binary search the partition of the smaller array and ensure all elements on the left side are less than or equal to all elements on the right side.


Pattern Learned

Two Sorted Arrays
+
Median
+
Logarithmic Requirement

=> Binary Search on Partition