Insertion in BST in Data Structures Theory - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to insert a new node in a Binary Search Tree (BST).

Data Structures Theory

if root is None:
    root = [1](key)

Drag options to blanks, or click blank then click option'

ANode

BTree

CBSTNode

DNodeKey

Attempts:

3 left

💡 Hint

Common Mistakes

Using a class name that does not exist like 'Tree' or 'BSTNode'.

Trying to insert the key directly without creating a node.

The insertion starts by creating a new node if the current root is None. The class used to create a node is typically named Node.

2fill in blank

medium

Complete the code to decide where to insert the new key in the BST.

Data Structures Theory

if key < root.key:
    root.left = insert(root.left, [1])

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Aroot.left

Bnew_key

Croot.key

Dkey

Attempts:

3 left

💡 Hint

Common Mistakes

Passing root.key instead of key to the recursive call.

Passing root.left which is a node, not the key.

When inserting in a BST, if the new key is less than the current node's key, we recursively insert it into the left subtree by passing the same key.

3fill in blank

hard

Fix the error in the code to insert the key in the right subtree.

Data Structures Theory

elif key > root.key:
    root.right = insert(root.right, [1])

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Aroot.key

Bkey

Croot.right

Dnew_key

Attempts:

3 left

💡 Hint

Common Mistakes

Passing root.key instead of key.

Passing root.right which is a node, not the key.

To insert the new key in the right subtree, the recursive call must pass the key to insert, not the current node's key or subtree.

4fill in blank

hard

Fill both blanks to complete the insertion function that returns the updated root.

Data Structures Theory

def insert(root, key):
    if root is None:
        return [1](key)
    if key < root.key:
        root.left = insert(root.left, key)
    elif key > root.key:
        root.right = insert(root.right, key)
    else:
        return root
    return [2]

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ANode

Broot

Ckey

Dinsert

Attempts:

3 left

💡 Hint

Common Mistakes

Returning the key instead of the root.

Not returning anything after insertion.

The function creates a new Node if the root is None. After insertion, it returns the root to maintain the tree structure.

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that maps node keys to their depths if depth is greater than 1.

Data Structures Theory

depths = {node.key: depth for node, depth in nodes if depth [1] 1 and node.key [2] [3]

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A>

B!=

CNone

D==

Attempts:

3 left

💡 Hint

Common Mistakes

Using == instead of != for the key check.

Using <= or < instead of > for depth.

The comprehension filters nodes with depth greater than 1 (> 1) and keys not equal to None (!= None).