Deep Copy of Data Structure - A Classic Problem

-
This is actually a classic problem - how to make a deep copy of a data structure? https://leetcode.com/problems/clone-binary-tree-with-random-pointer/

The tree is represented in the same input/output way as normal binary trees where each node is represented as a pair of [val, random_index] where:

  • val: an integer representing Node.val
  • random_index: the index of the node (in the input) where the random pointer points to, or null if it does not point to any node.

You will be given the tree in class Node and you should return the cloned tree in class NodeCopy. NodeCopy class is just a clone of Node class with the same attributes and constructors.

 

Example 1:

Input: root = [[1,null],null,[4,3],[7,0]]
Output: [[1,null],null,[4,3],[7,0]]
Explanation: The original binary tree is [1,null,4,7].
The random pointer of node one is null, so it is represented as [1, null].
The random pointer of node 4 is node 7, so it is represented as [4, 3] where 3 is the index of node 7 in the array representing the tree.
The random pointer of node 7 is node 1, so it is represented as [7, 0] where 0 is the index of node 1 in the array representing the tree.

Example 2:

Input: root = [[1,4],null,[1,0],null,[1,5],[1,5]]
Output: [[1,4],null,[1,0],null,[1,5],[1,5]]
Explanation: The random pointer of a node can be the node itself.

Example 3:

Input: root = [[1,6],[2,5],[3,4],[4,3],[5,2],[6,1],[7,0]]
Output: [[1,6],[2,5],[3,4],[4,3],[5,2],[6,1],[7,0]]

Example 4:

Input: root = []
Output: []

Example 5:

Input: root = [[1,null],null,[2,null],null,[1,null]]
Output: [[1,null],null,[2,null],null,[1,null]]

 

Constraints:

  • The number of nodes in the tree is in the range [0, 1000].
  • Each node's value is between [1, 10^6].
One technique that I find really valuable for this problem is to split it into two parts, and make use of a hash map. Here is the gist of it:
a) As mentioned, have a Hash Map handy
b) Perform a Shallow Copy first. A shallow copy means that you'll make a copy of the initial data structure without worrying about the random pointer. However, as you make a copy, create a map in the hash map between a node in the source data structure to the corresponding node in the target data structure. This can be done with a DFS.
c) Finally, perform a Deep Copy. The deep copy consists of a pre-order DFS using the hash map to map the random pointer.

For the cost, it costs O(2N)-time for {b,c} and O(N)-space for (a). Code is below, and since it is my Birthday today, comes with a pic of me :) Cheers, ACC.



public class Solution
{
    public NodeCopy CopyRandomBinaryTree(Node root)
    {
        if (root == null) return null;

        NodeCopy target = new NodeCopy(root.val);
        Hashtable sourceToTarget = new Hashtable();
        sourceToTarget.Add(root.GetHashCode(), target);

        //Step 1: Shallow copy with hash map
        ShallowCopy(root, target, sourceToTarget);

        //Step 2: deep copy of random node using hash map
        DeepCopy(root, target, sourceToTarget);

        return target;
    }

    private void DeepCopy(Node source,
                            NodeCopy target,
                            Hashtable sourceToTarget)
    {
        if (source == null) return;

        if (source.random != null && sourceToTarget.ContainsKey(source.random.GetHashCode()))
        {
            target.random = (NodeCopy)sourceToTarget[source.random.GetHashCode()];
        }

        DeepCopy(source.left, target.left, sourceToTarget);
        DeepCopy(source.right, target.right, sourceToTarget);
    }

    private void ShallowCopy(Node source,
                                NodeCopy target,
                                Hashtable sourceToTarget)
    {
        if (source == null) return;

        if (source.left != null)
        {
            target.left = new NodeCopy(source.left.val);
            if (!sourceToTarget.ContainsKey(source.left.GetHashCode())) sourceToTarget.Add(source.left.GetHashCode(), target.left);
            ShallowCopy(source.left, target.left, sourceToTarget);
        }
        if (source.right != null)
        {
            target.right = new NodeCopy(source.right.val);
            if (!sourceToTarget.ContainsKey(source.right.GetHashCode())) sourceToTarget.Add(source.right.GetHashCode(), target.right);
            ShallowCopy(source.right, target.right, sourceToTarget);
        }
    }
}

Comments

Post a Comment

Popular posts from this blog

Advent of Code - Day 6, 2024: BFS and FSM

-
Image
To solve this Advent of Code (parts 1 and 2), I used Breadth-First Search (BFS) to keep moving the guard as well as Finite State Machine (FSM) to control the directions. This solves part 1 easily. Part 2 can be solved using the same technique, takes a little longer since you need to try every empty cell, but it eventually does the trick (takes a min or so). Code is down below, cheers, ACC. Day 6 - Advent of Code 2024 using System.IO; using System.Collections; using System; using System.Text; using System.Text.RegularExpressions; using System.ComponentModel.DataAnnotations; Process2(); void Process() { string fileName = "input.txt"; FileInfo fileInfo = new FileInfo(fileName); StreamReader sr = fileInfo.OpenText(); List map = new List (); int startRow = 0; int startCol = 0; while (!sr.EndOfStream) { string line = sr.ReadLine().Trim(); map.Add(new StringBuilder(line)); int indexStart = line.IndexOf('^'); ...
Read more

Golang vs. C#: performance characteristics (simple case study)

-
Image
This is an interesting example to study the performance characteristics of Golang compared to C# for a very particular case (not generalized though).  The same code was written in C# and Golang (literally translated from one to the other). Below you'll be able to see the source code for both. The problem is a simple post-order DFS in a tree-like graph. The code in C# times out (TLE = Time Limited Exceeded). The code in Golang not only works but beats 100% of the other Golang submissions. Take a look the image below: Some potential reasons for the performance gains from Go in this particular example are: 1. Language and Runtime Differences:    Go is compiled directly to machine code, while C# typically runs on a virtual machine (CLR).    Go has a simpler runtime with less overhead compared to the .NET runtime.    Go's garbage collector is designed for low latency, which can lead to better performance in some scenarios. 2. Data Structures:    G...
Read more

Advent of Code - Day 7, 2024: Backtracking and Eval

-
Image
Problem today requires backtracking and eval (evaluating a mathematical expression in the format of a string). Glad that it used a left-2-right evaluation, makes for an easy parsing and not overly complicated evaluation function. Code is down below for parts 1 and 2. Cheers, ACC. Day 7 - Advent of Code 2024 using System.IO; using System.Collections; using System; using System.Text; using System.Text.RegularExpressions; using System.ComponentModel.DataAnnotations; Process2(); void Process() { string fileName = "input.txt"; long retVal = 0; FileInfo fileInfo = new FileInfo(fileName); StreamReader sr = fileInfo.OpenText(); while (!sr.EndOfStream) { string line = sr.ReadLine().Trim(); string[] parts1 = line.Split(':'); long target = Int64.Parse(parts1[0]); string[] numbers = parts1[1].Split(new char[] { ' ' }, StringSplitOptions.RemoveEmptyEntries); if (TryAll1(numbers, target, "", 0)) r...
Read more