Unit 8 Session 1 Advanced (Click for link to problem statements)
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?
HAPPY CASE
Input: Binary tree with nodes [7, 6, 0, 5, 1]
Output: 7
Explanation: The largest pearl has a size of 7.
EDGE CASE
Input: Binary tree with nodes [1, 0, 1]
Output: 1
Explanation: The largest pearl has a size of 1.
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.
For Tree Maximum problems, we want to consider the following approaches:
Plan the solution with appropriate visualizations and pseudocode.
General Idea: Traverse the tree recursively, comparing the values of each node to find the maximum.
1) If the current node is None, return a very small value (negative infinity).
2) Recursively find the maximum value in the left subtree.
3) Recursively find the maximum value in the right subtree.
4) Return the maximum of the current node's value, the maximum value in the left subtree, and the maximum value in the right subtree.
⚠️ Common Mistakes
Implement the code to solve the algorithm.
class TreeNode:
def __init__(self, value, left=None, right=None):
self.val = value
self.left = left
self.right = right
def find_largest_pearl(root):
if root is None:
return float('-inf')
# Recursively find the maximum value in the left and right subtrees
left_max = find_largest_pearl(root.left)
right_max = find_largest_pearl(root.right)
# Return the maximum value found
return max(root.val, left_max, right_max)
Review the code by running specific example(s) and recording values (watchlist) of your code's variables along the way.
Test with the examples given:
- Input 1: Binary tree with nodes [7, 6, 0, 5, 1]
- Expected Output: 7
- Input 2: Binary tree with nodes [1, 0, 1]
- Expected Output: 1
Evaluate the performance of your algorithm and state any strong/weak or future potential work.
Assume N
represents the number of nodes in the binary tree.
O(N)
because the algorithm needs to visit each node in the tree.O(H)
where H
is the height of the tree, due to the recursive call stack.