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Floor and Ceil in BST in DSA Python - Time & Space Complexity

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Time Complexity: Floor and Ceil in BST
O(h)
Understanding Time Complexity

We want to know how long it takes to find the floor or ceil of a value in a Binary Search Tree (BST).

Specifically, how the time grows as the tree gets bigger.

Scenario Under Consideration

Analyze the time complexity of the following code snippet.


def floor_in_bst(root, key):
    floor_val = None
    while root:
        if root.val == key:
            return root.val
        elif root.val > key:
            root = root.left
        else:
            floor_val = root.val
            root = root.right
    return floor_val

This code finds the floor value (largest value <= key) in a BST by traversing from root down.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

  • Primary operation: Traversing down the BST nodes from root to leaf.
  • How many times: At most once per level of the tree, until a leaf or exact match is found.
How Execution Grows With Input

Each step moves down one level in the tree, so the number of steps depends on the tree height.

Input Size (n)Approx. Operations (steps down tree)
10Up to 4 (if balanced)
100Up to 7 (if balanced)
1000Up to 10 (if balanced)

Pattern observation: In a balanced BST, steps grow slowly (logarithmically) as tree size grows.

Final Time Complexity

Time Complexity: O(h) where h is tree height

This means the time depends on how tall the tree is, not just how many nodes it has.

Common Mistake

[X] Wrong: "Finding floor or ceil always takes O(n) time because we might check every node."

[OK] Correct: In a BST, we skip large parts of the tree by moving left or right, so we only visit nodes along one path, not all nodes.

Interview Connect

Understanding how tree height affects search time helps you explain why balanced trees are important and shows you can analyze real code efficiently.

Self-Check

"What if the BST is not balanced but skewed like a linked list? How would the time complexity change?"

Practice

(1/5)
1. What does the floor of a value in a Binary Search Tree (BST) represent?
easy
A. The greatest value in the BST less than or equal to the given value
B. The smallest value in the BST greater than or equal to the given value
C. The root value of the BST
D. The average of all values in the BST

Solution

  1. Step 1: Understand the floor concept in BST

    The floor of a value is the largest value in the BST that is less than or equal to the given value.
  2. Step 2: Compare with other options

    The ceil is the smallest value greater than or equal to the given value, so The smallest value in the BST greater than or equal to the given value is incorrect. Options C and D do not relate to floor.
  3. Final Answer:

    The greatest value in the BST less than or equal to the given value -> Option A
  4. Quick Check:

    Floor = greatest ≤ value [OK]
Hint: Floor is largest value ≤ target in BST [OK]
Common Mistakes:
  • Confusing floor with ceil
  • Thinking floor is the smallest value
  • Assuming floor is always the root
2. Which of the following is the correct Python function signature to find the ceil of a value in a BST node?
easy
A. def ceil_find(value, root):
B. def find_ceil(root, value):
C. def findCeil(value):
D. def ceil(root):

Solution

  1. Step 1: Check common parameter order for BST functions

    Functions usually take the root node first, then the value to search for.
  2. Step 2: Validate each option

    def find_ceil(root, value): matches this order and naming convention. Options B, C, and D either have wrong parameter order or missing parameters.
  3. Final Answer:

    def find_ceil(root, value): -> Option B
  4. Quick Check:

    Function(root, value) is standard [OK]
Hint: Root node first, then value in function parameters [OK]
Common Mistakes:
  • Swapping parameter order
  • Missing one parameter
  • Using unclear function names
3. Given the BST below and value = 14, what is the floor of 14?

       15
      /  \
     10   20
    /  \    \
   8   12    25
medium
A. 14
B. 15
C. 12
D. 10

Solution

  1. Step 1: Locate values less than or equal to 14 in BST

    Values ≤ 14 are 10, 8, 12. 15 and above are greater.
  2. Step 2: Find the greatest among these

    The greatest value ≤ 14 is 12.
  3. Final Answer:

    12 -> Option C
  4. Quick Check:

    Floor(14) = 12 [OK]
Hint: Floor ≤ value, pick largest from left subtree [OK]
Common Mistakes:
  • Choosing 15 which is greater than 14
  • Assuming floor equals the value if not present
  • Picking smallest value instead of largest ≤ value
4. Consider this buggy Python code to find ceil in BST:

def find_ceil(root, value):
    if root is None:
        return None
    if root.val == value:
        return root.val
    if root.val < value:
        return find_ceil(root.right, value)
    else:
        ceil = find_ceil(root.left, value)
        return ceil if ceil is not None else root.val
What is the main error?
medium
A. It should check for None before recursion
B. It should return root.val when root.val == value
C. It should recurse on root.right when root.val > value
D. It should recurse on root.right when root.val < value

Solution

  1. Step 1: Analyze recursion direction for ceil

    If root.val < value, ceil must be in right subtree, so recurse on root.right.
  2. Step 2: Identify incorrect recursion

    Code incorrectly recurses on root.left when root.val < value, which is wrong.
  3. Final Answer:

    It should recurse on root.right when root.val < value -> Option D
  4. Quick Check:

    Ceil search goes right if root.val < value [OK]
Hint: Go right if node value < target for ceil [OK]
Common Mistakes:
  • Recursing left instead of right
  • Confusing floor and ceil logic
  • Not handling None cases properly
5. You have a BST with values [5, 10, 15, 20, 25]. You want to find the floor and ceil of 17. Which pair is correct?
hard
A. Floor = 15, Ceil = 20
B. Floor = 20, Ceil = 25
C. Floor = 10, Ceil = 15
D. Floor = 17, Ceil = 17

Solution

  1. Step 1: Identify floor of 17 in BST

    Floor is greatest value ≤ 17. Values ≤ 17 are 5, 10, 15. Greatest is 15.
  2. Step 2: Identify ceil of 17 in BST

    Ceil is smallest value ≥ 17. Values ≥ 17 are 20, 25. Smallest is 20.
  3. Final Answer:

    Floor = 15, Ceil = 20 -> Option A
  4. Quick Check:

    Floor ≤ 17 = 15, Ceil ≥ 17 = 20 [OK]
Hint: Floor ≤ value, ceil ≥ value in sorted BST [OK]
Common Mistakes:
  • Choosing floor or ceil outside BST values
  • Assuming floor or ceil equals the value if not present
  • Mixing floor and ceil values
Recommended

Ready to prove it?

Pass the test and this pattern moves unknown strong while earning +1 Grip toward your certificate.

10 questions~5 mineasy hard