Understanding the Replace Linked List Problem on LeetCode

Are you ready to tackle the challenge of the “Replace Linked List” problem on LeetCode? This problem is a classic example of a linked list manipulation task that can help you sharpen your coding skills. In this article, I’ll guide you through the problem, its requirements, and various approaches to solve it. Let’s dive in!

Problem Description

The “Replace Linked List” problem on LeetCode requires you to replace the value of each node in a linked list with the sum of the next two nodes. If there is no next node, the value of the current node should be set to 0. The task is to modify the linked list in-place and return the head of the modified list.

Approach 1: Iterative Solution

The iterative approach is straightforward. You’ll traverse the linked list, updating each node’s value with the sum of the next two nodes. Here’s a step-by-step guide to implementing this approach:

1. Check if the head of the linked list is null. If it is, return null.
2. Initialize two pointers, `prev` and `curr`, to the head of the linked list.
3. While `curr` is not null and `curr.next` is not null:
1. Set `curr.val` to `curr.next.val + curr.next.next.val`.
2. Move `prev` to `curr` and `curr` to `curr.next.next`.
4. Set `curr.val` to 0 if `curr.next` is null.
5. Return the head of the modified linked list.

Approach 2: Recursive Solution

The recursive approach is a bit more complex but can be a fun way to challenge your problem-solving skills. The idea is to recursively call the function to replace the value of the next two nodes, then backtrack to update the current node’s value. Here’s how you can implement this approach:

1. Define a helper function, `replace`, that takes a node as an argument.
2. Check if the node is null or if the next node is null. If either condition is true, return the node.
3. Recursively call the `replace` function on the next node.
4. Set the current node’s value to the sum of the next two nodes’ values.
5. Return the node.

Finally, call the `replace` function on the head of the linked list and return the modified list.

Time and Space Complexity

The time complexity for both the iterative and recursive solutions is O(n), where n is the number of nodes in the linked list. This is because you need to traverse the entire list once. The space complexity for the iterative solution is O(1), as you’re modifying the list in-place. However, the recursive solution has a space complexity of O(n) due to the function call stack.

Example

Let’s consider the following linked list: 1 -> 2 -> 3 -> 4 -> 5. After applying the “Replace Linked List” problem, the list should become: 3 -> 5 -> 8 -> 9 -> 0.

Conclusion

Now that you’ve learned about the “Replace Linked List” problem on LeetCode, you should be well-equipped to tackle it. Both the iterative and recursive approaches have their pros and cons, so choose the one that suits your coding style. Happy coding!