DSA Trie & Prefix Tree - Practice Questions 2026

Core Concepts: Here, the focus shifts to primary operations. You will encounter questions regarding standard insertion, searching for exact keys, and the fundamental logic of the "starts with" prefix functionality.

Intermediate Concepts: In this phase, we introduce complexity. You will tackle problems involving word deletion (and the subsequent cleanup of unused nodes), counting occurrences, and handling different character sets beyond lowercase a-z.

Advanced Concepts: This tier explores specialized variations like Compressed Tries (Radix Trees) and Suffix Trees. Questions here involve complex pattern matching and memory-efficient implementations.

Real-world Scenarios: Learn how Tries are applied in industry. This section covers autocomplete systems, IP routing tables, spell checkers, and DNA sequence analysis.

Mixed Revision / Final Test: The ultimate challenge. This comprehensive exam pulls from all previous sections, presenting questions in a randomized format to test your retention and ability to switch between different problem-solving strategies under pressure.

Option 2: 10

Option 3: 26

Option 4: 52

Option 5: Unlimited

Correct Answer: Option 3

Correct Answer Explanation: A standard Trie for English lowercase letters uses an array or hash map of size 26 (a through z) at each node to point to potential child nodes. Therefore, the maximum "out-degree" or branching factor is 26.

Wrong Answers Explanation:

Option 2 is incorrect as it typically applies to a Trie for decimal digits (T9 or numerical systems).

Option 4 is incorrect because it would apply if we were including both lowercase and uppercase letters.

Option 5 is incorrect because computer memory and the defined character set (lowercase English) impose a specific limit of 26.

Option 2: O(log N)

Option 3: O(L * log N)

Option 4: O(L)

Option 5: O(N * L)

Correct Answer: Option 4

Correct Answer Explanation: One of the primary advantages of a Trie is that search time is independent of the number of words (N) stored in the structure. The search time is strictly dependent on the length of the word (L) being searched, as you only need to perform "L" lookups.

Wrong Answers Explanation:

Option 2 is incorrect because this is the complexity of searching in a balanced Binary Search Tree.

Option 3 is incorrect as it is a hybrid complexity that does not apply to standard Trie operations.

Option 5 is incorrect because it would represent the worst-case time for a very inefficient search algorithm.

Option 2: Only if the node has at least one child.

Option 3: Only if the node has no children and is not part of another word.

Option 4: Any node can be deleted as soon as the word search is complete.

Option 5: Nodes are never deleted in a Trie to maintain structure.

Correct Answer: Option 3

Correct Answer Explanation: To avoid breaking the path for other words, a node can only be deleted if it is a leaf (has no children) and is not marked as the end of a different word that happens to be a prefix of the word being deleted.

Wrong Answers Explanation:

Option 2 is incorrect because deleting a node with children would destroy all words branching from that node.

Option 4 is incorrect because it ignores the shared nature of prefixes in a Trie.

Option 5 is incorrect as it describes a memory leak; deletion is a standard operation in dynamic data structures.

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