Trie Node Design and Initialization in DSA Python - Practice Problems & Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of Trie Node Initialization

What is the output of the following code that initializes a Trie node and prints its children keys?

DSA Python

class TrieNode:
    def __init__(self):
        self.children = {}
        self.is_end_of_word = False

node = TrieNode()
print(list(node.children.keys()))

A ['is_end_of_word']

B ['a']

C None

D []

💡 Hint

Think about what keys exist in the children dictionary right after initialization.

The children dictionary is empty when a TrieNode is created, so printing its keys shows an empty list.

❓ Predict Output

intermediate

Check is_end_of_word Flag After Initialization

What is the value of is_end_of_word immediately after creating a new TrieNode?

DSA Python

class TrieNode:
    def __init__(self):
        self.children = {}
        self.is_end_of_word = False

node = TrieNode()
print(node.is_end_of_word)

A True

B None

C False

D Raises AttributeError

💡 Hint

Look at the default value assigned to is_end_of_word in the constructor.

The flag is_end_of_word is set to False when the node is created.

🔧 Debug

advanced

Identify the Error in TrieNode Initialization

What error will this code raise when trying to create a TrieNode?

DSA Python

class TrieNode:
    def __init__(self):
        self.children = []
        self.is_end_of_word = False

node = TrieNode()
print(node.children['a'])

A KeyError: 'a'

B TypeError: list indices must be integers or slices, not str

C AttributeError: 'TrieNode' object has no attribute 'children'

D No error, prints None

💡 Hint

Check the type of children and how it is accessed.

The children attribute is a list, but the code tries to access it with a string key, causing a TypeError.

❓ Predict Output

advanced

Children Dictionary After Adding a Child Node

What is the output after adding a child node for character 'c' to the children dictionary of a TrieNode?

DSA Python

class TrieNode:
    def __init__(self):
        self.children = {}
        self.is_end_of_word = False

node = TrieNode()
node.children['c'] = TrieNode()
print(list(node.children.keys()))

A ['c']

B ['is_end_of_word']

C []

D None

💡 Hint

Think about what keys exist after adding a child node with key 'c'.

After adding a child node with key 'c', the children dictionary contains one key: 'c'.

🧠 Conceptual

expert

Why Use a Dictionary for Children in TrieNode?

Which is the main reason to use a dictionary for the children attribute in a TrieNode instead of a list?

A Dictionaries allow fast lookup by character keys, making insert and search efficient.

B Lists use less memory and are faster for character lookup.

C Dictionaries automatically sort the children nodes alphabetically.

D Lists prevent duplicate child nodes, ensuring unique characters.

💡 Hint

Consider how you find a child node for a given character quickly.

Dictionaries provide O(1) average time complexity for key lookup, which is ideal for checking if a child node exists for a character.

Practice

1. What is the main purpose of a Trie node in a Trie data structure?

easy

A. To store the length of the longest word

B. To store children nodes representing characters and a flag for word end

C. To store the frequency of words in a dictionary

D. To store only the complete words in a list

Solution

1. Step 1: Understand Trie node components

   A Trie node typically holds links to child nodes for each character and a boolean flag to mark if a word ends here.

2. Step 2: Compare options with Trie node purpose

   Only To store children nodes representing characters and a flag for word end correctly describes storing children nodes and a word-end flag, which is essential for Trie functionality.

3. Final Answer:

   To store children nodes representing characters and a flag for word end -> Option B

4. Quick Check:

   Trie node = children + end flag [OK]

Hint: Trie nodes hold children and word-end flags [OK]

Common Mistakes:

• Thinking Trie nodes store whole words directly
• Confusing Trie nodes with hash maps
• Ignoring the word-end flag in nodes

2. Which of the following is the correct way to initialize a Trie node's children in Python for lowercase English letters?

easy

A. children = [0] * 26

B. children = {}

C. children = list('abcdefghijklmnopqrstuvwxyz')

D. children = [None] * 26

Solution

1. Step 1: Understand children initialization for fixed alphabet

   For 26 lowercase letters, children are usually a list of size 26 initialized with None to hold child nodes.

2. Step 2: Evaluate options

   children = [None] * 26 creates a list of 26 None values, suitable for storing child nodes. children = {} uses a dictionary, which is valid but not fixed size. children = [0] * 26 uses zeros, which are not node references. children = list('abcdefghijklmnopqrstuvwxyz') creates a list of characters, not nodes.

3. Final Answer:

   children = [None] * 26 -> Option D

4. Quick Check:

   Fixed-size list with None = children [OK]

Hint: Use list of None for fixed-size children array [OK]

Common Mistakes:

• Using zeros instead of None for children
• Using a string list instead of node references
• Confusing dictionary with fixed-size list

3. What will be the output of this code snippet?

class TrieNode:
    def __init__(self):
        self.children = [None] * 26
        self.is_end = False

node = TrieNode()
print(node.children[0])
print(node.is_end)

medium

A. 0\nFalse

B. None\nTrue

C. None\nFalse

D. Error

Solution

1. Step 1: Analyze TrieNode initialization

   The children list is initialized with 26 None values, so node.children[0] is None. The is_end flag is set to False.

2. Step 2: Check print outputs

   Printing node.children[0] outputs None, and printing node.is_end outputs False.

3. Final Answer:

   None\nFalse -> Option C

4. Quick Check:

   children[0] = None, is_end = False [OK]

Hint: Uninitialized children are None, is_end defaults False [OK]

Common Mistakes:

• Expecting 0 instead of None for children
• Assuming is_end defaults to True
• Thinking code raises error

4. Identify the error in this TrieNode initialization code:

class TrieNode:
    def __init__(self):
        self.children = [False] * 26
        self.is_end = False

medium

A. Children initialized with False instead of None

B. is_end should be True initially

C. Children list size should be 52 for uppercase and lowercase

D. Missing return statement in __init__

Solution

1. Step 1: Check children initialization

   Children should be initialized with None to indicate no child nodes yet. Using False is incorrect because False is a boolean, not a placeholder for a node.

2. Step 2: Verify other parts

   is_end is correctly set to False. The list size 26 is fine for lowercase letters. __init__ does not require a return statement.

3. Final Answer:

   Children initialized with False instead of None -> Option A

4. Quick Check:

   Children must be None, not False [OK]

Hint: Children must be None, not False [OK]

Common Mistakes:

• Confusing False with None for children
• Thinking __init__ needs return
• Assuming is_end should start True

5. You want to design a TrieNode that supports both lowercase and uppercase English letters. How should you initialize the children array?

hard

A. children = [None] * 52

B. children = [None] * 26

C. children = {}

D. children = list('abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ')

Solution

1. Step 1: Determine size for both cases

   Lowercase and uppercase English letters total 26 + 26 = 52 characters, so children array must have 52 slots.

2. Step 2: Choose correct initialization

   children = [None] * 52 creates a list of 52 None values, perfect for indexing each letter. children = [None] * 26 only supports 26 letters. children = {} uses a dictionary, which is flexible but not fixed size. children = list('abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ') creates a list of characters, not nodes.

3. Final Answer:

   children = [None] * 52 -> Option A

4. Quick Check:

   52 slots for uppercase + lowercase [OK]

Hint: Use 52 None slots for both letter cases [OK]

Common Mistakes:

• Using 26 slots for both cases
• Using dictionary instead of list
• Confusing list of chars with node references