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This approach uses recursion to evaluate the binary boolean tree. Starting from the root, recursively evaluate the left and right children of each node. If a node is a leaf, return its boolean value. If a node is non-leaf, apply the boolean operation defined by its value on its children's evaluations (OR for 2, AND for 3).
Time Complexity: O(n) where n is the number of nodes, since we need to visit each node once.
Space Complexity: O(h) where h is the height of the tree, due to the recursion stack.
1function TreeNode(val, left, right) {
2 this.val = (val===undefined ? 0 : val)
3 this.left = (left===undefined ? null : left)
4 this.right = (right===undefined ? null : right)
5}
6
7var evaluateTree = function(root) {
8 if (!root.left && !root.right)
9 return root.val === 1;
10 let left = evaluateTree(root.left);
11 let right = evaluateTree(root.right);
12 return root.val === 2 ? left || right : left && right;
13};Javascript code makes use of recursion to evaluate the tree, examining leaf and non-leaf nodes for computing boolean logic operations, following a depth-first traversal method.
This method employs an iterative approach using a stack to emulate the recursive behavior. By performing a depth-first traversal, it uses a stack to track nodes and their processed children, evaluating each in line with the tree's logic operations.
Time Complexity: O(n), as all nodes are processed.
Space Complexity: O(n), given the stack memory employment.
1
In Java, this iterative method uses a stack to perform depth-first traversal, determining each node's evaluation directly or post-child-processing. Logical calculations are performed at each non-leaf node based on stored child results.