Prefix Search Using Trie in DSA Java - Time & Space Complexity

Time Complexity: Prefix Search Using Trie

O(m)

Understanding Time Complexity

We want to understand how fast we can find words that start with a given prefix using a Trie.

How does the search time change as the prefix length or number of words grows?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

class TrieNode {
    TrieNode[] children = new TrieNode[26];
    boolean isWord = false;
}

boolean startsWith(TrieNode root, String prefix) {
    TrieNode node = root;
    for (char c : prefix.toCharArray()) {
        if (node.children[c - 'a'] == null) return false;
        node = node.children[c - 'a'];
    }
    return true;
}
    

This code checks if any word in the Trie starts with the given prefix by following nodes for each prefix character.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: Loop over each character in the prefix string.
• How many times: Exactly once per character in the prefix (length m).

How Execution Grows With Input

The time grows directly with the length of the prefix we search for.

Input Size (prefix length m)	Approx. Operations
10	About 10 checks
100	About 100 checks
1000	About 1000 checks

Pattern observation: The work grows linearly with prefix length, not with total words stored.

Final Time Complexity

Time Complexity: O(m)

This means the search time depends only on how long the prefix is, not on how many words are in the Trie.

Common Mistake

[X] Wrong: "The search time depends on the total number of words stored in the Trie."

[OK] Correct: The search only follows nodes for the prefix characters, so it depends on prefix length, not total words.

Interview Connect

Knowing how prefix search time depends on prefix length helps you explain why Tries are efficient for autocomplete and dictionary lookups.

Self-Check

"What if we changed the Trie to store words with uppercase letters and digits? How would the time complexity change?"

Practice

1. What is the main purpose of using a Trie data structure in prefix search?

easy

A. To efficiently find all words that start with a given prefix

B. To sort words alphabetically

C. To store numbers in sorted order

D. To perform arithmetic operations quickly

Solution

1. Step 1: Understand what prefix search means

   Prefix search means finding all words that start with a certain beginning sequence of letters.

2. Step 2: Understand Trie's role in prefix search

   A Trie stores words in a tree where each node represents a letter, making it easy to find all words sharing the same prefix by traversing the tree.

3. Final Answer:

   To efficiently find all words that start with a given prefix -> Option A

4. Quick Check:

   Prefix search = efficient word lookup [OK]

Hint: Trie nodes represent letters for fast prefix lookup [OK]

Common Mistakes:

• Confusing Trie with sorting data structures
• Thinking Trie is for arithmetic operations
• Assuming Trie stores numbers only

2. Which of the following is the correct way to declare a Trie node class in Java?

easy

A. class TrieNode { int[] children = new int[26]; boolean isEndOfWord; }

B. class TrieNode { char[] children = new char[26]; boolean isEndOfWord; }

C. class TrieNode { String[] children = new String[26]; boolean isEndOfWord; }

D. class TrieNode { TrieNode[] children = new TrieNode[26]; boolean isEndOfWord; }

Solution

1. Step 1: Identify the correct type for children nodes

   Each child should be a reference to another TrieNode, so the array type must be TrieNode[].

2. Step 2: Check the other parts of the class

   Boolean isEndOfWord marks if the node ends a word, which is correct in class TrieNode { TrieNode[] children = new TrieNode[26]; boolean isEndOfWord; }.

3. Final Answer:

   class TrieNode { TrieNode[] children = new TrieNode[26]; boolean isEndOfWord; } -> Option D

4. Quick Check:

   Children are TrieNode references [OK]

Hint: Children array holds TrieNode references, not primitives [OK]

Common Mistakes:

• Using int or char arrays instead of TrieNode array
• Using String array for children
• Forgetting to mark end of word

3. Given the following code snippet, what will be the output?

Trie trie = new Trie();
trie.insert("cat");
trie.insert("car");
trie.insert("dog");
System.out.println(trie.startsWith("ca"));
System.out.println(trie.startsWith("do"));
System.out.println(trie.startsWith("bat"));

medium

A. true
true
false

B. true
false
false

C. false
true
false

D. false
false
true

Solution

1. Step 1: Insert words into the Trie

   Words "cat", "car", and "dog" are inserted, so prefixes "ca" and "do" exist in the Trie.

2. Step 2: Check startsWith results

   startsWith("ca") returns true because "cat" and "car" start with "ca".
   startsWith("do") returns true because "dog" starts with "do".
   startsWith("bat") returns false because no word starts with "bat".

3. Final Answer:

   true true false -> Option A

4. Quick Check:

   Prefix "ca" and "do" found, "bat" not found [OK]

Hint: Check inserted words' prefixes carefully [OK]

Common Mistakes:

• Assuming startsWith returns false if word not complete
• Confusing startsWith with search for whole word
• Mixing up true/false outputs

4. The following Java method is intended to check if a prefix exists in a Trie, but it has a bug. What is the bug?

public boolean startsWith(String prefix) {
    TrieNode node = root;
    for (int i = 0; i <= prefix.length(); i++) {
        char c = prefix.charAt(i);
        if (node.children[c - 'a'] == null) return false;
        node = node.children[c - 'a'];
    }
    return true;
}

medium

A. The root node is not initialized before the loop

B. The loop condition should be < instead of <= to avoid IndexOutOfBoundsException

C. The method should return false at the end instead of true

D. The character indexing is wrong; should use c + 'a'

Solution

1. Step 1: Analyze the for-loop condition

   The loop runs from i = 0 to i <= prefix.length(), which means it tries to access prefix.charAt(prefix.length()), causing an IndexOutOfBoundsException.

2. Step 2: Correct the loop condition

   The loop should run while i < prefix.length() to access valid characters only.

3. Final Answer:

   The loop condition should be < instead of <= to avoid IndexOutOfBoundsException -> Option B

4. Quick Check:

   Loop index must be less than length [OK]

Hint: Loop index must be less than string length [OK]

Common Mistakes:

• Using <= instead of < in loop condition
• Incorrect character arithmetic
• Returning wrong boolean at the end

5. You want to find all words in a Trie that start with the prefix "app". Which approach correctly retrieves all such words?

hard

A. Use a hash map to store all words and filter those starting with "app"

B. Search each word in the Trie individually to check if it starts with "app"

C. Traverse the Trie to the node representing 'p' in "app", then perform a depth-first search collecting all words below

D. Insert "app" as a word and then search for it

Solution

1. Step 1: Locate the prefix node in the Trie

   Traverse the Trie following letters 'a', 'p', 'p' to reach the node representing the last 'p' in "app".

2. Step 2: Collect all words below this node

   Perform a depth-first search (DFS) from this node to find all complete words that start with "app".

3. Final Answer:

   Traverse the Trie to the node representing 'p' in "app", then perform a depth-first search collecting all words below -> Option C

4. Quick Check:

   Prefix node + DFS = all matching words [OK]

Hint: Find prefix node, then DFS to collect words [OK]

Common Mistakes:

• Checking all words instead of using Trie structure
• Using hash map instead of Trie traversal
• Confusing insertion with search