Day 6 - Clone List with Next and Random.md

Difficulty	Source	Tags
Hard	160 Days of Problem Solving	Linked-List

🚀 Day 6. Clone List with Next and Random 🧠

The problem can be found at the following link: Problem Link

💡 Problem Description:

You are given a special linked list where each node has two pointers:

1. A next pointer pointing to the next node.
2. A random pointer pointing to any random node in the list or NULL.

Your task is to construct a deep copy of the linked list. The copied list should consist of the same number of nodes, and both the next and random pointers in the new list should be correctly set.

🔍 Example Walkthrough:

Input:
LinkedList: 1->2->3->4->5
Pairs: [[1,3],[2,1],[3,5],[4,3],[5,2]]

Output:
True

Explanation:
The copied linked list maintains the same structure:

• Node 1 points to 2 as its next and 3 as its random.
• Node 2 points to 3 as its next and 1 as its random.
• Node 3 points to 4 as its next and 5 as its random.
• Node 4 points to 5 as its next and 3 as its random.
• Node 5 points to NULL as its next and 2 as its random.

Input:
LinkedList: 1->3->5->9
Pairs: [[1,1],[3,4]]
Output:
True

Explanation:

• Node 1 points to itself as its random.
• Node 3 does not have a valid random mapping in the given pairs, so it remains NULL.

Constraints:

• 1 <= number of random pointers <= number of nodes <= 100
• 0 <= node->data <= 1000
• 1 <= a, b <= 100

🎯 My Approach:

Steps:

1. Clone Nodes:

   • Insert cloned nodes between the original nodes. For example, if the list is 1 -> 2 -> 3, after cloning it becomes 1 -> 1' -> 2 -> 2' -> 3 -> 3'.

2. Update Random Pointers:

   • For each cloned node, set its random pointer to point to the cloned version of the random pointer of the original node.

3. Separate the Cloned List:

   • Extract the cloned nodes into a separate list while restoring the original list.

🕒 Time and Auxiliary Space Complexity

• Expected Time Complexity: O(n), where n is the number of nodes in the linked list. We iterate through the list a constant number of times.
• Expected Auxiliary Space Complexity: O(1), as the algorithm uses no extra space apart from variables for iteration.

📝 Solution Code

Code (C++)

class Solution {
public:
    Node* cloneLinkedList(Node* head) {
        if (!head) return nullptr;
        for (Node* t = head; t; t = t->next->next) {
            Node* n = new Node(t->data);
            n->next = t->next;
            t->next = n;
        }
        for (Node* t = head; t; t = t->next->next)
            if (t->random) t->next->random = t->random->next;
        Node* newHead = head->next;
        for (Node* t = head; t; t = t->next) {
            Node* temp = t->next;
            t->next = temp->next;
            if (temp->next) temp->next = temp->next->next;
        }
        return newHead;
    }
};

Code (Java)

class Solution {
    Node cloneLinkedList(Node head) {
        if (head == null) return null;

        for (Node t = head; t != null; t = t.next.next) {
            Node n = new Node(t.data);
            n.next = t.next;
            t.next = n;
        }
        for (Node t = head; t != null; t = t.next.next) {
            if (t.random != null) t.next.random = t.random.next;
        }
        Node newHead = head.next;
        for (Node t = head; t != null; t = t.next) {
            Node temp = t.next;
            t.next = temp.next;
            if (temp.next != null) temp.next = temp.next.next;
        }
        return newHead;
    }
}

Code (Python)

class Solution:
    def cloneLinkedList(self, head):
        if not head:
            return None

        d = {}
        ch = Node(head.data)
        chh = ch
        d[head] = ch

        h = head.next
        while h:
            nn = Node(h.data)
            chh.next = nn
            d[h] = nn
            h = h.next
            chh = nn

        h = head
        chh = ch
        while h:
            if h.random:
                chh.random = d[h.random]
            h = h.next
            chh = chh.next

        return ch

🎯 Contribution and Support:

For discussions, questions, or doubts related to this solution, feel free to connect on LinkedIn: Any Questions. Let’s make this learning journey more collaborative!

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