"Solve the following coding problem in C++. I need...

बनाया गया: 26 जून 2026

का उपयोग करके उत्तर दिया गया GPT-5.5 Thinking द्वारा Chat01

प्रश्न

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"Solve the following coding problem in C++. I need the most optimized solution possible with the lowest time and space complexity. First, analyze the constraints and derive the optimal approach. Avoid brute force and unnecessary data structures. Then provide:

Optimal algorithm explanation (brief).
Time and space complexity.
Clean, concise, competitive-programming style C++17 code.
Use short variable names where readability is not affected.
No redundant comments or extra explanations.
Verify the solution against edge cases and large constraints

विचार

Parsing coding problem for total efficiency

The problem asks to find the total efficiency of a smart array processor from given subarrays. We need to merge the subarrays and calculate how many elements are strictly less than the original element at each index, while ignoring the values that contribute to the new array directly. I'll approach this by handling the subarrays efficiently and iterating over the elements.

Thought for 31s

उत्तर

Optimal algorithm

Each interval [l, r] contributes every index inside it once to the final efficient array.
So for every index j, compute:

cnt[j] = number of pairs covering j

Then:

  • If cnt[i] > 0, index i contributed, so its efficiency is 0.
  • If cnt[i] == 0, efficiency is the total number of elements in efficient strictly smaller than arr[i].

So we need weighted counts by value:

weight[value] = total cnt[j] for all j where arr[j] == value

Then for every uncovered index i, add the prefix sum of weights for values < arr[i].

Complexity

n, m <= 2 * 10^5

Time: O((n + m) log n)
Space: O(n)

C++17 Code

cpp
#include <bits/stdc++.h> using namespace std; long findTotalEfficiency(vector<int> arr, vector<vector<int>> pairs) { int n = arr.size(); vector<long long> diff(n + 1, 0); for (auto &p : pairs) { int l = p[0], r = p[1]; diff[l]++; diff[r + 1]--; } vector<int> vals = arr; sort(vals.begin(), vals.end()); vals.erase(unique(vals.begin(), vals.end()), vals.end()); int k = vals.size(); vector<long long> wt(k, 0); vector<int> uncov; long long cur = 0; for (int i = 0; i < n; i++) { cur += diff[i]; int id = lower_bound(vals.begin(), vals.end(), arr[i]) - vals.begin(); if (cur > 0) wt[id] += cur; else uncov.push_back(arr[i]); } long long pref = 0; for (int i = 0; i < k; i++) { long long x = wt[i]; wt[i] = pref; pref += x; } long long ans = 0; for (int x : uncov) { int id = lower_bound(vals.begin(), vals.end(), x) - vals.begin(); ans += wt[id]; } return ans; }

Edge cases verified

  • All indices covered → answer 0.
  • No index covered → efficient array is empty → answer 0.
  • Duplicate arr values handled correctly because only strictly smaller values are counted.
  • Duplicate intervals handled through coverage count.
  • Large intervals and large m handled using difference array, not brute force.

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