CPMagical CP Library

Problem solution · Java

Height of Binary Tree After Subtree Removal Queries

Height of Binary Tree After Subtree Removal Queries: a Java 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
37 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 Height of Binary Tree After Subtree Removal Queries, 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

  • 37 lines of Java from the credited upstream file 2458.java.
  • The implementation visibly relies on sequence storage, hash lookup, ordered lookup.
  • 1 loop block 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 codeHeight of Binary Tree After Subtree Removal Queries · JavaJava
Use this to learn the idea, then write your own version.
class Solution {  public int[] treeQueries(TreeNode root, int[] queries) {    int[] ans = new int[queries.length];     dfs(root, 0, 0);     for (int i = 0; i < queries.length; ++i)      ans[i] = valToMaxHeight.get(queries[i]);     return ans;  }   // valToMaxHeight[val] := the maximum height without the node with `val`  private Map<Integer, Integer> valToMaxHeight = new HashMap<>();  // valToHeight[val] := the height of the node with `val`  private Map<Integer, Integer> valToHeight = new HashMap<>();   private int height(TreeNode root) {    if (root == null)      return 0;    if (valToHeight.containsKey(root.val))      return valToHeight.get(root.val);    final int h = 1 + Math.max(height(root.left), height(root.right));    valToHeight.put(root.val, h);    return h;  }   // maxHeight := the maximum height without the current node `root`  private void dfs(TreeNode root, int depth, int maxHeight) {    if (root == null)      return;    valToMaxHeight.put(root.val, maxHeight);    dfs(root.left, depth + 1, Math.max(maxHeight, depth + height(root.right)));    dfs(root.right, depth + 1, Math.max(maxHeight, depth + height(root.left)));  }}

Keep practising

Did this explanation save you time? I'm a Grade 11 student building this free library to make difficult algorithms easier to understand.

Buy me a coffee ↗