297 Serialize and Deserialize Binary Tree
1. Question
Serialization is the process of converting a data structure or object into a sequence of bits so that it can be stored in a file or memory buffer, or transmitted across a network connection link to be reconstructed later in the same or another computer environment.
Design an algorithm to serialize and deserialize a binary tree. There is no restriction on how your serialization/deserialization algorithm should work. You just need to ensure that a binary tree can be serialized to a string and this string can be deserialized to the original tree structure.
For example, you may serialize the following tree
1
/ \
2 3
/ \
4 5
as"[1,2,3,null,null,4,5]"
, just the same as how LeetCode OJ serializes a binary tree. You do not necessarily need to follow this format, so please be creative and come up with different approaches yourself.
2. Implementation
/**
* Definition for a binary tree node.
* public class TreeNode {
* int val;
* TreeNode left;
* TreeNode right;
* TreeNode(int x) { val = x; }
* }
*/
public class Codec {
// Encodes a tree to a single string.
public String serialize(TreeNode root) {
StringBuilder res = new StringBuilder();
convertToString(root, res);
return res.toString();
}
public void convertToString(TreeNode node, StringBuilder res) {
if (node == null) {
res.append("#").append(",");
}
else {
res.append(node.val).append(",");
convertToString(node.left, res);
convertToString(node.right, res);
}
}
// Decodes your encoded data to tree.
public TreeNode deserialize(String data) {
Queue<String> queue = new LinkedList<>();
queue.addAll(Arrays.asList(data.split(",")));
return buildTree(queue);
}
public TreeNode buildTree(Queue<String> queue) {
String val = queue.remove();
if (val.equals("#")) {
return null;
}
TreeNode node = new TreeNode(Integer.valueOf(val));
node.left = buildTree(queue);
node.right = buildTree(queue);
return node;
}
}
// Your Codec object will be instantiated and called as such:
// Codec codec = new Codec();
// codec.deserialize(codec.serialize(root));
3. Time & Space Complexity
时间复杂度O(n), 空间复杂度O(n)
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