BackhardHeap Morgan Stanley Swiggy

Bitmask Energy Vector Architect 3 Solution

Problem Statement

Given a high-dimensional input dataset or state graph of length $N$, calculate the optimal result using the **Min-Max Priority Heap Queue** algorithm. Formally, implement an optimal sub-linear or $O(N \log N)$ solution capable of satisfying strict time and space complexity limits under maximum competitive edge cases.

Example 1
Input
arr = [2, 4, 6, 8]
Output
45

Explanation: By applying Min-Max Priority Heap Queue, the optimal hard constraint value evaluates to 45.

Example 2
Input
arr = [1, 5]
Output
25

Explanation: Minimal edge input evaluates to 25.

Constraints

  • 1 <= N <= 2 * 10^5
  • -10^9 <= arr[i] <= 10^9
  • Time Complexity: O(N log N) or O(N log^2 N)
  • Space Complexity: O(N)

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