Tree Traversal Postorder Left Right Root in DSA Python - Interactive Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to visit the left subtree first in postorder traversal.

DSA Python

def postorder(node):
    if node is None:
        return
    postorder(node.[1])
    print(node.val, end=' ')

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

Aleft

Bparent

Cright

Droot

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'right' instead of 'left' causes wrong traversal order.

Trying to access 'parent' or 'root' attributes which don't exist.

In postorder traversal, we visit the left subtree first, so we call postorder(node.left).

2fill in blank

medium

Complete the code to visit the right subtree second in postorder traversal.

DSA Python

def postorder(node):
    if node is None:
        return
    postorder(node.left)
    postorder(node.[1])
    print(node.val, end=' ')

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

Aparent

Bright

Croot

Dchild

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'parent' or 'root' instead of 'right' causes errors.

Skipping the right subtree visit.

In postorder traversal, after visiting the left subtree, we visit the right subtree by calling postorder(node.right).

3fill in blank

hard

Fix the error in printing the node value in postorder traversal.

DSA Python

def postorder(node):
    if node is None:
        return
    postorder(node.left)
    postorder(node.right)
    print(node.[1], end=' ')

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

Adata

Bvalue

Cval

Dnode

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'value' or 'data' when the node uses 'val'.

Trying to print the whole node object.

The node's value is stored in val, so we print node.val.

4fill in blank

hard

Fill both blanks to create a dictionary comprehension that maps node values to their depths during postorder traversal.

DSA Python

depth_map = {node.val: [1] for node in nodes if node.[2] is not None}

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

Adepth[node.val] + 1

Bdepth[node.val] - 1

Cleft

Dright

Attempts:

3 left

💡 Hint

Common Mistakes

Using subtraction instead of addition for depth.

Checking the left child instead of the right child.

We map each node's value to its depth plus one, and filter nodes that have a right child (node.right is not None).

5fill in blank

hard

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

DSA Python

result = [1]: [2] for node in nodes if [3] > 0

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

Anode.val.upper()

Bdepth[node.val]

Dnode.val

Attempts:

3 left

💡 Hint

Common Mistakes

Using lowercase values instead of uppercase.

Filtering with incorrect depth condition.

The comprehension maps uppercase node values to their depths, filtering nodes with depth greater than zero.

Practice

1. What is the order of nodes visited in a postorder tree traversal?

easy

A. Root node, Left subtree, Right subtree

B. Right subtree, Left subtree, Root node

C. Root node, Right subtree, Left subtree

D. Left subtree, Right subtree, Root node

Solution

1. Step 1: Understand postorder traversal definition

   Postorder traversal visits nodes in the order: left subtree first, then right subtree, and finally the root node.

2. Step 2: Match the order with options

   Left subtree, Right subtree, Root node matches the order Left, Right, Root exactly.

3. Final Answer:

   Left subtree, Right subtree, Root node -> Option D

4. Quick Check:

   Postorder = Left, Right, Root [OK]

Hint: Remember: postorder ends with the root node [OK]

Common Mistakes:

• Confusing postorder with preorder or inorder
• Visiting root node first instead of last
• Swapping left and right subtree order

2. Which of the following Python function headers correctly defines a postorder traversal method for a binary tree node root?

easy

A. def postorder(root):

B. def preorder(root):

C. def inorder(root):

D. def traverse(root):

Solution

1. Step 1: Identify the function name for postorder traversal

   The function name should clearly indicate postorder traversal, so postorder is correct.

2. Step 2: Check the parameter

   The parameter root is standard for the current node in tree traversal functions.

3. Final Answer:

   def postorder(root): -> Option A

4. Quick Check:

   Function name matches traversal type [OK]

Hint: Function name should match traversal type exactly [OK]

Common Mistakes:

• Using wrong traversal names like preorder or inorder
• Missing the root parameter
• Using generic names that don't specify traversal

3. Given the binary tree:

    1
   / \
  2   3
 / \
4   5

What is the output of the postorder traversal?

medium

A. [4, 5, 2, 3, 1]

B. [1, 3, 2, 4, 5]

C. [2, 4, 5, 3, 1]

D. [4, 2, 5, 3, 1]

Solution

1. Step 1: Traverse left subtree of root (1)

   Left subtree rooted at 2: postorder is left (4), right (5), root (2) -> [4, 5, 2]

2. Step 2: Traverse right subtree of root (1)

   Right subtree rooted at 3 has no children, so postorder is [3]

3. Step 3: Combine left, right, and root

   Full postorder: left subtree [4, 5, 2], right subtree [3], root [1] -> [4, 5, 2, 3, 1]

4. Final Answer:

   [4, 5, 2, 3, 1] -> Option A

5. Quick Check:

   Postorder = Left, Right, Root [OK]

Hint: Visit left subtree fully, then right, then root last [OK]

Common Mistakes:

• Visiting root before children
• Mixing up left and right subtree order
• Listing nodes in preorder or inorder instead

4. The following code attempts a postorder traversal but produces incorrect output. What is the error?

def postorder(root):
    if root:
        print(root.data)
        postorder(root.left)
        postorder(root.right)

medium

A. The left and right subtree calls are swapped

B. The function does not check if root is None

C. The root node is printed before traversing children

D. The function should return a list instead of printing

Solution

1. Step 1: Analyze the order of print and recursive calls

   The code prints root.data first, then traverses left and right subtrees. This is preorder traversal order.

2. Step 2: Identify correct postorder sequence

   Postorder requires visiting left subtree, then right subtree, then printing root last.

3. Final Answer:

   The root node is printed before traversing children -> Option C

4. Quick Check:

   Print after children calls for postorder [OK]

Hint: Print root after left and right calls for postorder [OK]

Common Mistakes:

• Printing root before children (preorder mistake)
• Not handling empty nodes properly
• Swapping left and right subtree calls

5. You want to collect all node values of a binary tree in postorder traversal into a list. Which code snippet correctly implements this?

hard

A. def postorder(root):
result = []
if root:
result.append(root.data)
result += postorder(root.left)
result += postorder(root.right)
return result

B. def postorder(root):
result = []
if root:
result += postorder(root.left)
result += postorder(root.right)
result.append(root.data)
return result

C. def postorder(root):
if root is None:
return []
return [root.data] + postorder(root.left) + postorder(root.right)

D. def postorder(root):
if root is None:
return []
return postorder(root.left) + [root.data] + postorder(root.right)

Solution

1. Step 1: Check the order of appending nodes

   def postorder(root): result = [] if root: result += postorder(root.left) result += postorder(root.right) result.append(root.data) return result appends left subtree results, then right subtree results, then root data last, matching postorder.

2. Step 2: Verify return of combined list

   def postorder(root): result = [] if root: result += postorder(root.left) result += postorder(root.right) result.append(root.data) return result returns the combined list correctly after recursive calls.

3. Final Answer:

   def postorder(root): result = [] if root: result += postorder(root.left) result += postorder(root.right) result.append(root.data) return result -> Option B

4. Quick Check:

   Left + Right + Root order in list [OK]

Hint: Append root after left and right recursive results [OK]

Common Mistakes:

• Appending root before children (preorder)
• Incorrect list concatenation order
• Not returning the combined list properly