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You are given the root
of a full binary tree with the following properties:
0
or 1
, where 0
represents False
and 1
represents True
.2
or 3
, where 2
represents the boolean OR
and 3
represents the boolean AND
.The evaluation of a node is as follows:
True
or False
.Return the boolean result of evaluating the root
node.
A full binary tree is a binary tree where each node has either 0
or 2
children.
A leaf node is a node that has zero children.
Example 1:
Input: root = [2,1,3,null,null,0,1]
Output: true
Explanation: The above diagram illustrates the evaluation process.
The AND node evaluates to False AND True = False.
The OR node evaluates to True OR False = True.
The root node evaluates to True, so we return true.
Example 2:
Input: root = [0]
Output: false
Explanation: The root node is a leaf node and it evaluates to false, so we return false.
Constraints:
[1, 1000]
.0 <= Node.val <= 3
0
or 2
children.0
or 1
.2
or 3
.public boolean evaluateTree(TreeNode root) {
if(root.val == 0) return false;
if(root.val == 1) return true;
boolean l = evaluateTree(root.left);
boolean r = evaluateTree(root.right);
return root.val==2 ? l|r : l&r;
}
bool evaluateTree(TreeNode* n) {
switch(n->val) {
case 0:
case 1:
return n->val;
case 2:
return evaluateTree(n->left) || evaluateTree(n->right);
default:
return evaluateTree(n->left) && evaluateTree(n->right);
}
}
class Solution:
def evaluateTree(self, root: Optional[TreeNode]) -> bool:
def recur(node):
if not node.left and not node.right: #leaf node
return True if node.val == 1 else False
left = recur(node.left)
right = recur(node.right)
if node.val == 2: #if node is or
return left or right
if node.val == 3: #if node is and
return left and right
return recur(root)
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