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Problem solution · C++

Maximize Sum of Weights after Edge Removals

Maximize Sum of Weights after Edge Removals: a C++ solution using depth-first search. Learn the idea, check the complexity, and read the full code, with credit to walkccc LeetCode Solutions.

Technique
Depth-first search
Source
walkccc LeetCode Solutions
Length
48 lines
Start with the idea.

Try the problem first. If you get stuck, read the approach below, then write your own solution. The full code is at the bottom.

Approach

Depth-first search

For Maximize Sum of Weights after Edge Removals, the implementation follows one branch at a time, making it suitable for components, trees, backtracking, or dependency exploration.

  1. Define the state carried into one recursive or stack frame.
  2. Mark or choose the current state before exploring children.
  3. Combine child results or undo the choice when the branch finishes.

Code notes

  • 48 lines of C++ from the credited upstream file 3367.cpp.
  • The implementation visibly relies on sequence storage, work queue.
  • 3 loop blocks detected, together with recursive traversal.

Complexity

Count unique states for graph traversal; for backtracking, count the branching factor and maximum depth.

Check the problem constraints before deciding whether this complexity will pass.

Source

Code and credit

This code comes from walkccc LeetCode Solutions by P.-Y. Chen (walkccc) and is used under the MIT licence.

Open problem ↗Original source ↗
Full codeMaximize Sum of Weights after Edge Removals · C++C++
Use this to learn the idea, then write your own version.
class Solution { public:  long long maximizeSumOfWeights(vector<vector<int>>& edges, int k) {    const int n = edges.size() + 1;    vector<vector<pair<int, int>>> graph(n);     for (const vector<int>& edge : edges) {      const int u = edge[0];      const int v = edge[1];      const int w = edge[2];      graph[u].emplace_back(v, w);      graph[v].emplace_back(u, w);    }     return dfs(graph, 0, -1, k).second;  }   // Returns  // (the weight sum of the subtree rooted at u with at most k - 1 children,  //  the weight sum of the subtree rooted at u with at most k children).  pair<long, long> dfs(const vector<vector<pair<int, int>>>& graph, int u,                       int prev, int k) {    long weightSum = 0;    priority_queue<long> diffs;     for (const auto& [v, w] : graph[u]) {      if (v == prev)        continue;      const auto [subK1, subK] = dfs(graph, v, u, k);      weightSum += subK;      // If picking (u, v) makes the sum larger, we should pick it.      diffs.push(max(0L, subK1 - subK + w));    }     long topK1 = 0;    long topK = 0;     for (int i = 0; i < k && !diffs.empty(); ++i) {      if (i < k - 1)        topK1 += diffs.top();      topK += diffs.top();      diffs.pop();    }     return {weightSum + topK1, weightSum + topK};  };};

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