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Prefix Tree

Certification: Intermediate Level Accuracy: 0% Submissions: 0 Points: 10

Write a C program to implement a Trie (prefix tree) data structure. A trie is a tree-like data structure that stores a dynamic set of strings, where the keys are usually strings. Implement the Trie class with insert, search, and startsWith operations.

Example 1
    
          
  • Input: 
     Operations: ["insert", "search", "search", "startsWith", "insert", "search"]

     Arguments: [["apple"], ["apple"], ["app"], ["app"], ["app"], ["app"]]
    • 
          
  • Output: [null, true, false, true, null, true]
    • 
          
  • Explanation: 
    • Insert "apple" into the trie. Search for "apple" - returns true (word exists). 
    • Search for "app" - returns false (prefix exists but not as complete word). 
    • Check if any word starts with "app" - returns true. 
    • Insert "app" as a complete word. Search for "app" - returns true (now exists as complete word).
    •
Example 2
    
          
  • Input:

     Operations: ["insert", "insert", "search", "search", "startsWith"]

     Arguments: [["hello"], ["help"], ["hell"], ["hello"], ["hel"]]
    • 
          
  • Output: [null, null, false, true, true]
    • 
          
  • Explanation: 
    • Insert "hello" into the trie. Insert "help" into the trie. 
    • Search for "hell" - returns false (prefix exists but not complete word). 
    • Search for "hello" - returns true (complete word exists). 
    • Check if any word starts with "hel" - returns true.
    •
Constraints
    
          
  • 1 ≤ word.length, prefix.length ≤ 2000
    • 
          
  • word and prefix consist only of lowercase English letters
    • 
          
  • At most 3 * 10^4 calls will be made to insert, search, and startsWith
    • 
          
  • Time Complexity: O(m) for all operations where m is key length
    • 
          
  • Space Complexity: O(ALPHABET_SIZE * N * M) where N is number of keys and M is average length
    •
Trie Goldman SachsPhillips
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Hint
Solution

Solution Hints

    
          
  • Create a TrieNode structure with children array and isEndOfWord flag.
    • 
          
  • Use an array of size 26 for each node to store child pointers (a-z).
    • 
          
  • For insert: traverse the trie creating nodes as needed, mark last node as end of word.
    • 
          
  • For search: traverse the trie following the word path, check if last node is end of word.
    • 
          
  • For startsWith: traverse the trie following the prefix path, return true if path exists.
    • 
          
  • Use character arithmetic (ch - 'a') to get array index for each character.
    •

Steps to solve by this approach:

 Step 1: Define TrieNode structure with children array of size 26 and isEndOfWord boolean.

 Step 2: Implement createNode function to allocate memory and initialize all children to NULL.

 Step 3: For insert operation, traverse character by character creating nodes as needed.

 Step 4: Mark the last node as end of word by setting isEndOfWord to true.

 Step 5: For search operation, traverse the path and check if final node is end of word.

 Step 6: For startsWith operation, just traverse the prefix path without checking isEndOfWord.

 Step 7: Use character arithmetic (ch - 'a') to convert characters to array indices.

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