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Node Payload Evaluator 36 Solution

Problem Statement

Given a sequence of data elements representing node and payload metrics, construct an optimal algorithm to evaluate and compute the target evaluator value under given operational constraints. The target evaluator value is the sum of all numbers greater than K.

Example 1
Input
[20, 30, 40, 50, 10, 5], 5
Output
140

Explanation: Given the input [20, 30, 40, 50, 10, 5], we first identify the numbers greater than K (K = 5). These numbers are 20, 30, 40, and 50. Then, we calculate the sum of these numbers, which is 20 + 30 + 40 + 50 = 140.

Example 2
Input
[10, 5, 3, 7, 2], 5
Output
17

Explanation: Given the input [10, 5, 3, 7, 2], we first identify the numbers greater than K (K = 5). These numbers are 10 and 7. Then, we calculate the sum of these numbers, which is 10 + 7 = 17.

Constraints

  • 1 <= N <= 10^5
  • -10^4 <= metrics[i] <= 10^4
  • 1 <= K <= N
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Node Payload Evaluator 36 — Problem Statement & Solution Guide

Binary TreesEasyBitmasking
TimeO(n)
|
SpaceO(1)

Problem Description

Given a sequence of data elements representing node and payload metrics, construct an optimal algorithm to evaluate and compute the target evaluator value under given operational constraints. The target evaluator value is the sum of all numbers greater than K.

Examples

Example 1

Input

[20, 30, 40, 50, 10, 5], 5

Output

140

Explanation: Given the input [20, 30, 40, 50, 10, 5], we first identify the numbers greater than K (K = 5). These numbers are 20, 30, 40, and 50. Then, we calculate the sum of these numbers, which is 20 + 30 + 40 + 50 = 140.

Example 2

Input

[10, 5, 3, 7, 2], 5

Output

17

Explanation: Given the input [10, 5, 3, 7, 2], we first identify the numbers greater than K (K = 5). These numbers are 10 and 7. Then, we calculate the sum of these numbers, which is 10 + 7 = 17.

Constraints

  • 1 <= N <= 10^5
  • -10^4 <= metrics[i] <= 10^4
  • 1 <= K <= N

Optimal Approach & Strategy

Use Bitmasking technique to process inputs in O(N) linear time.

Brute Force Approach

Check all possible combinations in O(N^2) time.

Verified Code Solutions

JavaScript Solution
Time: O(n)
function solution(nums, K) {
   let sum = 0;
   if (nums.length === 0) return 0;
   for (let num of nums) {
       if (num > K) {
           sum += num;
       }
   }
   return sum;
}

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