TRIE06 - Editorial

editorial
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Problem Statement - Implementation in Tries

Problem Statement:

Implement the trie data structure as taught in the previous sections.

Approach:

The key idea of this solution is to utilize a Trie data structure to manage and store words efficiently. A Trie is especially useful for prefix-related queries. Here’s how the approach works:

  1. Trie Structure:

    • Each TrieNode contains:
      • An array of children nodes (one for each letter of the alphabet).
      • A boolean flag isEndOfWord to indicate if a node marks the end of a valid word.

  2. Insert Function:

    • The insert function adds a new word to the Trie.
    • It starts from the root and traverses through each character of the word, creating new nodes as needed. At the end of the word, it marks the last node as an end-of-word.

  3. Search Function:

    • The search function checks if a word exists in the Trie.
    • It traverses through the Trie using the characters of the word. If it reaches the end and finds the end-of-word flag set to true, the word exists.

  4. Delete Function:

    • The deleteWord function allows for removing a word from the Trie.
    • It recursively navigates through the Trie and removes nodes if they are not needed (i.e., if they don’t form a prefix of any other word).

  5. Print All Words:

    • The printAllWords function prints all the words stored in the Trie.
    • It uses a recursive helper function to traverse the Trie and builds words character by character.

  6. Main Function:

    • The main function handles user input to execute commands: inserting words, searching for words, deleting words, and printing all stored words.

Time Complexity:

  • Insertion: O(L)

  • Search: O(L)

  • Deletion: O(L)

  • Print All Words: O(N * L) where N is the number of words and L is the average length of the words.

Space Complexity:

  • O(N * L) for storing N words of average length L, since each character can create a node in the Trie.