Flower Fields - codepath/compsci_guides GitHub Wiki

Unit 8 Session 1 Standard (Click for link to problem statements)

Problem Highlights

• 💡 Difficulty: Easy
• ⏰ Time to complete: 10 mins
• 🛠️ Topics: Binary Tree, Tree Traversal, Recursion

1: U-nderstand

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?

• What is the tree structure, and what values can nodes hold?
  • The tree structure is a binary tree, and each node holds a flower name as a string.
• What should the function return if the tree is empty or the flower is not found?
  • The function should return False if the tree is empty or the flower is not found.

HAPPY CASE
Input: Binary tree with flowers ["Rose", "Lily", "Daisy", "Orchid", "Lilac", "Dahlia"] and target "Lilac"
Output: True
Explanation: The flower "Lilac" exists in the tree.

EDGE CASE
Input: Binary tree with flowers ["Rose", "Lily", "Daisy", "Orchid", "Lilac", "Dahlia"] and target "Hibiscus"
Output: False
Explanation: The flower "Hibiscus" does not exist in the tree.

2: M-atch

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 Search problems, we want to consider the following approaches:

• Binary Tree Traversal: Traverse the tree to search for the target flower.
• Recursion: Use recursion to explore each node and determine if the target flower is present.

3: P-lan

Plan the solution with appropriate visualizations and pseudocode.

General Idea: Traverse the tree recursively to search for the target flower, returning True if found, False otherwise.

1) If the current node is None, return False.
2) If the current node's value matches the target flower, return True.
3) Recursively search the left subtree for the target flower.
4) Recursively search the right subtree for the target flower.
5) Return True if the flower is found in either subtree, otherwise return False.

⚠️ Common Mistakes

• Not correctly handling the case where the tree is empty.
• Failing to return True as soon as the flower is found, leading to unnecessary computations.

4: I-mplement

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_flower(root, flower):
    if root is None:
        return False
    
    # If the current node matches the target flower, return True
    if root.val == flower:
        return True
    
    # Recursively search in the left and right subtrees
    return find_flower(root.left, flower) or find_flower(root.right, flower)

5: R-eview

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 flowers ["Rose", "Lily", "Daisy", "Orchid", "Lilac", "Dahlia"] and target "Lilac"
  • Expected Output: True
  • Input 2: Binary tree with flowers ["Rose", "Lily", "Daisy", "Orchid", "Lilac", "Dahlia"] and target "Hibiscus"
  • Expected Output: False
  • Verify that the outputs match the expected results.

6: E-valuate

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.

• Time Complexity: O(N) because the algorithm may need to visit each node to determine if the flower is present.
• Space Complexity: O(H) where H is the height of the tree, due to the recursive call stack.