Problem solution · Java

Tree of Coprimes

Tree of Coprimes: 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
55 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 Tree of Coprimes, 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

  • 55 lines of Java from the credited upstream file 1766.java.
  • The implementation visibly relies on sequence storage, work queue.
  • 5 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.

Full codeTree of Coprimes · JavaJava
Use this to learn the idea, then write your own version.
class Solution {  public int[] getCoprimes(int[] nums, int[][] edges) {    int[] ans = new int[nums.length];    Arrays.fill(ans, -1);    List<Integer>[] tree = new List[nums.length];    // stacks[i] := (node, depth)s of nodes with value i    Deque<Pair<Integer, Integer>>[] stacks = new Deque[MAX + 1];     for (int i = 0; i < nums.length; ++i)      tree[i] = new ArrayList<>();     for (int i = 1; i <= MAX; ++i)      stacks[i] = new ArrayDeque<>();     for (int[] edge : edges) {      final int u = edge[0];      final int v = edge[1];      tree[u].add(v);      tree[v].add(u);    }     dfs(tree, 0, /*prev=*/-1, /*depth=*/0, nums, stacks, ans);    return ans;  }   private static final int MAX = 50;   private void dfs(List<Integer>[] tree, int u, int prev, int depth, int[] nums,                   Deque<Pair<Integer, Integer>>[] stacks, int[] ans) {    ans[u] = getAncestor(u, stacks, nums);    stacks[nums[u]].push(new Pair<>(u, depth));     for (final int v : tree[u])      if (v != prev)        dfs(tree, v, u, depth + 1, nums, stacks, ans);     stacks[nums[u]].pop();  }   private int getAncestor(int u, Deque<Pair<Integer, Integer>>[] stacks, int[] nums) {    int maxNode = -1;    int maxDepth = -1;    for (int i = 1; i <= MAX; ++i)      if (!stacks[i].isEmpty() && stacks[i].peek().getValue() > maxDepth && gcd(nums[u], i) == 1) {        maxNode = stacks[i].peek().getKey();        maxDepth = stacks[i].peek().getValue();      }    return maxNode;  }   private int gcd(int a, int b) {    return b == 0 ? a : gcd(b, a % b);  }} 

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 ↗