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Find Leftmost Node II
Unit 8 Session 1 (Click for link to problem statements)
Looking for the recursive version of this problem? Go to Find Leftmost Node I
- 💡 Difficulty: Easy
- ⏰ Time to complete: 10 mins
- 🛠️ Topics: Trees, Binary Trees, Iterative Algorithms
Understand what the interviewer is asking for by using test cases and questions about the problem.
- Established a set (2-3) of test cases to verify their own solution later.
- Established a set (1-2) of edge cases to verify their solution handles complexities.
- Have fully understood the problem and have no clarifying questions.
- Have you verified any Time/Space Constraints for this problem?
- Question: What should be returned if the tree is empty?
- Answer: The function should return None if the tree is empty.
HAPPY CASE
Input: TreeNode(1, TreeNode(2, TreeNode(4)), TreeNode(3))
Output: 4
Explanation: The leftmost node in the tree is the node with value 4, achieved by following the left children.
EDGE CASE
Input: TreeNode(1)
Output: 1
Explanation: The tree has only one node, which is also the leftmost node.
Match what this problem looks like to known categories of problems, e.g. Linked List or Dynamic Programming, and strategies or patterns in those categories.
This problem involves a straightforward tree traversal to locate the leftmost node, which aligns with iterative depth-first search methods.
Plan the solution with appropriate visualizations and pseudocode.
General Idea: Iteratively traverse to the leftmost node using a while loop until no left child is available.
1) Start at the root.
2) Use a loop to follow the left child until it no longer exists.
3) Return the value of the node where the loop terminates.
- Not handling the case where the tree is empty, leading to attempts to access attributes of None.
Implement the code to solve the algorithm.
def left_most(root):
"
Return the value of the leftmost node in the binary tree rooted at `root`.
If the tree is empty, return None.
"
if root is None:
return None
# Traverse down to the leftmost child
current = root
while current.left is not None:
current = current.left
return current.val
Review the code by running specific example(s) and recording values (watchlist) of your code's variables along the way.
- Verify with different test cases to ensure the function correctly identifies the leftmost node even in unbalanced trees.
Evaluate the performance of your algorithm and state any strong/weak or future potential work.
-
Time Complexity:
O(n)
in the worst case where n is the height of the tree, particularly if it is skewed to one side. -
Space Complexity:
O(1)
as no additional space is used apart from the input tree structure.