
The given problem requires us to transform a binary tree into a flattened "linked list" using the same TreeNode class structure. In this flattened structure, every node's left child pointer will be null, and the right child pointer will point to the next node in the sequence that mimics the order of a pre-order traversal of the binary tree. Pre-order traversal is a depth-first strategy where we visit the root node first, followed by the left subtree, and finally the right subtree. This transformation must effectively turn the binary tree into a linear sequence of nodes, consistent with the pre-order visitation order.
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[0, 2000].-100 <= Node.val <= 100The challenge is straightforward yet requires a careful manipulation of tree nodes to achieve the desired linked list format. Here is a step-by-step explanation of a potential approach:
Start at the root of the binary tree. If the tree is empty (i.e., the root is null), there is nothing to flatten, so we simply return.
As we need to flatten the tree to resemble a pre-order traversal, we will follow the root-left-right order in our approach.
Initiate the transformation at the root and traverse the tree. Use an iterative or recursive method to process each node:
null.This can be either implemented recursively, where the recursive function ensures after processing a node, it directly connects to the next node in pre-order, or iteratively using a stack to mimic the recursive stack and manage the order of nodes manually.
Care should be taken at each node to:
null.The given C++ code defines a method flattenTree within a Solution class to convert a binary tree into a flattened linked list. The transformation adheres to these rules: it places each node to the right of its previous node, effectively turning the tree into a right-skewed linked list in the same order as a pre-order traversal.
Here's a simplified breakdown of how the code works:
This method does not return any value as it modifies the tree in place. The algorithm implicitly handles the tree flattening without needing any additional memory for storage, which makes it space-efficient with a time complexity that, generally speaking, is O(n), where n is the number of nodes in the tree. This is because it processes each node in the tree exactly once.
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