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DSA Javaprogramming~5 mins

BST Delete Operation in DSA Java - Time & Space Complexity

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Time Complexity: BST Delete Operation
O(h)
Understanding Time Complexity

We want to understand how long it takes to remove a value from 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.

public TreeNode deleteNode(TreeNode root, int key) {
    if (root == null) return null;
    if (key < root.val) {
        root.left = deleteNode(root.left, key);
    } else if (key > root.val) {
        root.right = deleteNode(root.right, key);
    } else {
        if (root.left == null) return root.right;
        else if (root.right == null) return root.left;
        TreeNode minNode = findMin(root.right);
        root.val = minNode.val;
        root.right = deleteNode(root.right, minNode.val);
    }
    return root;
}

private TreeNode findMin(TreeNode node) {
    while (node.left != null) node = node.left;
    return node;
}

This code removes a node with a given key from a BST, adjusting the tree to keep its order.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

  • Primary operation: Recursive calls to find the node to delete and to adjust the tree.
  • How many times: At most once per level of the tree, moving down from root to leaf.
  • Additional operation: The findMin method loops down the left children to find the smallest node in the right subtree.
How Execution Grows With Input

As the tree grows, the number of steps depends on the tree's height.

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

Pattern observation: The steps grow roughly with the height of the tree, which can be much smaller than the total nodes if the tree is balanced.

Final Time Complexity

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

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

Common Mistake

[X] Wrong: "Deleting a node always takes time proportional to the total number of nodes (O(n))."

[OK] Correct: The delete operation only travels down one path from root to leaf, so it depends on the tree height, not all nodes.

Interview Connect

Understanding how tree height affects delete time helps you explain efficiency clearly and shows you know how data structure shape impacts performance.

Self-Check

"What if the BST is always perfectly balanced? How would that change the time complexity of delete?"

Practice

(1/5)
1. What happens when you delete a leaf node (a node with no children) from a Binary Search Tree (BST)?
easy
A. The node is simply removed and its parent's pointer is set to null.
B. The entire tree is restructured to maintain balance.
C. The node is replaced by its in-order predecessor.
D. The node is replaced by its in-order successor.

Solution

  1. Step 1: Understand leaf node deletion

    A leaf node has no children, so removing it does not affect other nodes.
  2. Step 2: Effect on parent pointer

    The parent's pointer to this node is set to null, effectively removing the node.
  3. Final Answer:

    The node is simply removed and its parent's pointer is set to null. -> Option A
  4. Quick Check:

    Leaf node deletion = remove node and set parent's pointer null [OK]
Hint: Leaf node deletion just removes the node, no restructuring needed [OK]
Common Mistakes:
  • Thinking the tree needs full restructuring
  • Replacing leaf node with predecessor or successor
  • Confusing leaf node deletion with internal node deletion
2. Which of the following is the correct Java method signature for deleting a node with a given key from a BST?
easy
A. public boolean deleteNode(int key)
B. public void deleteNode(int key)
C. public int deleteNode(Node root, int key)
D. public Node deleteNode(Node root, int key)

Solution

  1. Step 1: Understand BST delete method signature

    The method usually takes the root node and the key to delete, returning the updated root.
  2. Step 2: Match method signature

    public Node deleteNode(Node root, int key) matches: it takes Node root and int key, returns Node (updated root).
  3. Final Answer:

    public Node deleteNode(Node root, int key) -> Option D
  4. Quick Check:

    Delete method returns updated root node [OK]
Hint: Delete method returns updated root node after deletion [OK]
Common Mistakes:
  • Using void return type instead of Node
  • Not passing root node as parameter
  • Returning boolean or int instead of Node
3. Given the BST below, what is the in-order traversal after deleting the node with value 10?
       15
      /  \
    10    20
   /  \     \
  8   12    25
medium
A. [8, 12, 15, 20, 25, 10]
B. [8, 12, 15, 20, 25]
C. [8, 12, 15, 20]
D. [8, 10, 12, 15, 20, 25]

Solution

  1. Step 1: Delete node 10 from BST

    Node 10 has two children (8 and 12). Replace it with its in-order successor (12) and delete 12.
  2. Step 2: Perform in-order traversal after deletion

    In-order traversal visits nodes in ascending order: 8, 12, 15, 20, 25.
  3. Final Answer:

    [8, 12, 15, 20, 25] -> Option B
  4. Quick Check:

    In-order after deleting 10 = [8, 12, 15, 20, 25] [OK]
Hint: Replace deleted node with in-order successor for two children case [OK]
Common Mistakes:
  • Not replacing node 10 correctly
  • Including deleted node 10 in traversal
  • Confusing in-order successor with predecessor
4. Consider this Java method snippet for deleting a node from a BST:
public Node deleteNode(Node root, int key) {
    if (root == null) return root;
    if (key < root.val) root.left = deleteNode(root.left, key);
    else if (key > root.val) root.right = deleteNode(root.right, key);
    else {
        if (root.left == null) return root.right;
        else if (root.right == null) return root.left;
        Node temp = minValueNode(root.right);
        root.val = temp.val;
        root.right = deleteNode(root.right, key);
    }
    return root;
}

private Node minValueNode(Node node) {
    Node current = node;
    while (current.left != null) current = current.left;
    return current;
}
What is the bug in this code?
medium
A. The recursive call to deleteNode uses key instead of temp.val.
B. The method does not handle the case when root is null.
C. The method minValueNode should return the maximum value node instead.
D. The method does not update root.left or root.right correctly.

Solution

  1. Step 1: Analyze recursive delete call after replacement

    After replacing root.val with temp.val (in-order successor), the successor must be deleted from the right subtree using temp.val.
  2. Step 2: Identify the bug

    The recursive call uses key (original value) instead of temp.val. Since key < values in right subtree, it won't correctly delete the successor.
  3. Step 3: Check other options

    A is wrong (minValueNode finds successor correctly). B is wrong (null root handled). D is wrong (updates via recursion).
  4. Final Answer:

    The recursive call to deleteNode uses key instead of temp.val. -> Option A
  5. Quick Check:

    Recursive call must use temp.val [OK]
Hint: Check recursive calls carefully for correct key usage [OK]
Common Mistakes:
  • Thinking minValueNode should find max value
  • Confusing key and temp.val in recursive call
  • Missing base case for null root
5. You have a BST with nodes: 30, 20, 40, 10, 25, 35, 50. You delete node 20. Which of the following is the correct BST in-order traversal after deletion?
hard
A. [10, 25, 30, 40, 50]
B. [10, 20, 25, 30, 35, 40, 50]
C. [10, 25, 30, 35, 40, 50]
D. [25, 30, 35, 40, 50]

Solution

  1. Step 1: Identify node 20's children

    Node 20 has two children: 10 (left) and 25 (right).
  2. Step 2: Delete node 20 by replacing with in-order successor

    In-order successor is 25. Replace 20 with 25, then delete node 25.
  3. Step 3: Perform in-order traversal

    Traversal order: 10, 25, 30, 35, 40, 50.
  4. Final Answer:

    [10, 25, 30, 35, 40, 50] -> Option C
  5. Quick Check:

    In-order after deleting 20 = [10, 25, 30, 35, 40, 50] [OK]
Hint: Replace deleted node with in-order successor for two children case [OK]
Common Mistakes:
  • Leaving deleted node 20 in traversal
  • Removing in-order successor node incorrectly
  • Confusing in-order predecessor with successor
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