BST Inorder Predecessor in DSA Python - Time & Space Complexity

Time Complexity: BST Inorder Predecessor

O(h)

Understanding Time Complexity

We want to understand how long it takes to find the inorder predecessor 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 inorder_predecessor(root, node):
    if node.left:
        pred = node.left
        while pred.right:
            pred = pred.right
        return pred
    pred = None
    curr = root
    while curr:
        if node.val <= curr.val:
            curr = curr.left
        else:
            pred = curr
            curr = curr.right
    return pred

This code finds the inorder predecessor of a given node in a BST.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: Traversing down the tree nodes using while loops.
• How many times: At most, one path from root to a leaf or from node's left child down to the rightmost leaf.

How Execution Grows With Input

As the BST grows, the longest path to traverse grows with the tree height.

Input Size (n)	Approx. Operations
10	Up to 4-5 steps (tree height)
100	Up to 7-8 steps
1000	Up to 10-11 steps

Pattern observation: The number of steps grows roughly with the height of the tree, not the total number of nodes.

Final Time Complexity

Time Complexity: O(h)

This means the time depends on the height of the BST, which is the longest path from root to leaf.

Common Mistake

[X] Wrong: "Finding the inorder predecessor always takes O(n) time because we might check all nodes."

[OK] Correct: We only follow one path down the tree, never visiting all nodes, so the time depends on the tree height, not total nodes.

Interview Connect

Understanding this helps you explain how tree structure affects search times, a key skill in many coding challenges.

Self-Check

"What if the BST is balanced vs completely skewed? How would the time complexity change?"

Practice

1. What is the inorder predecessor of a node in a Binary Search Tree (BST)?

easy

A. The node with the largest value smaller than the given node

B. The node with the smallest value larger than the given node

C. The left child of the given node

D. The right child of the given node

Solution

1. Step 1: Understand inorder traversal order

   Inorder traversal visits nodes in ascending order for BST, so predecessor is the previous node in this order.

2. Step 2: Define inorder predecessor

   The inorder predecessor is the node with the largest value smaller than the current node's value.

3. Final Answer:

   The node with the largest value smaller than the given node -> Option A

4. Quick Check:

   Inorder predecessor = largest smaller value [OK]

Hint: Predecessor is just before current node in sorted order [OK]

Common Mistakes:

• Confusing predecessor with successor
• Thinking predecessor is always left child
• Assuming predecessor is the parent node

2. Which of the following Python code snippets correctly finds the inorder predecessor of a node with a left subtree in a BST?

easy

A. temp = node.right
while temp.right:
temp = temp.right
return temp

B. temp = node.right
while temp.left:
temp = temp.left
return temp

C. temp = node.left
while temp.left:
temp = temp.left
return temp

D. temp = node.left
while temp.right:
temp = temp.right
return temp

Solution

1. Step 1: Identify inorder predecessor logic for left subtree

   If node has left child, predecessor is the rightmost node in left subtree.

2. Step 2: Check code correctness

   Code D moves to left child, then goes right as far as possible, correctly finding predecessor.

3. Final Answer:

   Code snippet D correctly finds the inorder predecessor -> Option D

4. Quick Check:

   Left subtree's rightmost node = predecessor [OK]

Hint: Go left once, then right as far as possible [OK]

Common Mistakes:

• Going right subtree instead of left
• Going left repeatedly instead of right in left subtree
• Returning left child directly without traversal

3. Given the BST below and the node with value 15, what is the inorder predecessor?

       20
      /  \
    10    30
      \     \
      15    40

medium

A. 20

B. 15

C. 10

D. None

Solution

1. Step 1: Locate node 15 and check left subtree

   Node 15 has no left child, so predecessor is ancestor smaller than 15.

2. Step 2: Find nearest ancestor smaller than 15

   Ancestor 10 is smaller than 15 and is the closest on path to root.

3. Final Answer:

   10 -> Option C

4. Quick Check:

   Predecessor of 15 is 10 [OK]

Hint: If no left child, go up to smaller ancestor [OK]

Common Mistakes:

• Choosing 20 which is larger
• Choosing node itself as predecessor
• Assuming predecessor is None without checking ancestors

4. The following code attempts to find the inorder predecessor of a node in a BST but has a bug. What is the bug?

def inorder_predecessor(root, node):
    if node.left:
        temp = node.left
        while temp.left:
            temp = temp.left
        return temp
    else:
        predecessor = None
        while root:
            if node.val > root.val:
                predecessor = root
                root = root.right
            else:
                root = root.left
        return predecessor

medium

A. The else block incorrectly updates predecessor

B. The while loop should check temp.right, not temp.left

C. The function does not handle empty tree

D. The function should return None if node has no left child

Solution

1. Step 1: Analyze left subtree traversal

   In left subtree, predecessor is rightmost node, so loop should go right, not left.

2. Step 2: Identify correct traversal direction

   Changing while temp.left to while temp.right fixes the bug.

3. Final Answer:

   The while loop should check temp.right, not temp.left -> Option B

4. Quick Check:

   Predecessor in left subtree = rightmost node [OK]

Hint: Go right in left subtree, not left [OK]

Common Mistakes:

• Looping left instead of right in left subtree
• Ignoring else block logic
• Not returning predecessor correctly

5. You want to find the inorder predecessor of a node in a BST that does NOT have a left child. Which approach correctly finds the predecessor?

hard

A. Traverse from root, track the last node smaller than current node

B. Return the rightmost node in the left subtree

C. Return the parent node if it is smaller than the current node

D. Return the left child of the current node

Solution

1. Step 1: Understand no left child case

   If node has no left child, predecessor is an ancestor smaller than node.

2. Step 2: Use root traversal to track predecessor

   Traverse from root, update predecessor when node value is greater than root's value.

3. Step 3: Return last tracked smaller ancestor

   This gives the inorder predecessor correctly.

4. Final Answer:

   Traverse from root, track the last node smaller than current node -> Option A

5. Quick Check:

   No left child -> track smaller ancestor [OK]

Hint: Track last smaller ancestor from root [OK]

Common Mistakes:

• Returning parent without checking value
• Returning left child when none exists
• Trying to find predecessor in left subtree when none exists