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Median of the two sorted arrays.

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…

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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


IR-PLAYBOOK-RCE
HIGH
SOC Incident Playbook: Remote Code Execution (RCE) Defense
1-Click Detection Engineering: Sigma & YARA Rules
SOC Ready
title: Detect Exploitation - Median of the two sorted arrays.
id: f32e34af-9e00-47d6-be15-51dd23eb2344
status: experimental
description: Automatisch generierte SIEM-Erkennungsregel basierend auf CTI Intelligence
references:
  - https://tsecurity.de/
author: iShareStuff CTI Automated Detection Engine
date: 2026-09-23
logsource:
  category: network_connection
  product: any
detection:
  selection:
      CommandLine|contains:
        - 'exploit'
  condition: selection
falsepositives:
  - Legitime administrative Zugriffe oder Penetrationstests
level: high
tags:
  - attack.initial_access
rule CTI_Threat_Indicator {
    meta:
        author = "iShareStuff CTI Automated Detection Engine"
        date = "2026-09-23"
        description = "YARA Signature for "
    strings:
        $str = "Median of the two sorted array" ascii wide
    condition:
        any of them
}
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