Problem Statement

Design and implement a Trie (also known as a Prefix Tree). A trie is a tree-like data structure that stores a dynamic set of strings, and is particularly useful for searching for words with a given prefix.

Implement the Solution class:

• Solution() Initializes the object.
• void insert(word) Inserts word into the trie, making it available for future searches.
• bool search(word) Checks if the word exists in the trie.
• bool startsWith(word) Checks if any word in the trie starts with the given prefix.

Examples

1. Example 1:

   • Input:
     • Trie operations: ["Trie", "insert", "search", "startsWith"]
     • Arguments: [[], ["apple"], ["apple"], ["app"]]
   • Expected Output: [-1, -1, 1, 1]
   • Justification: After inserting "apple", "apple" exists in the Trie. There is also a word that starts with "app", which is "apple".

2. Example 2:

   • Input:
     • Trie operations: ["Trie", "insert", "search", "startsWith", "search"]
     • Arguments: [[], ["banana"], ["apple"], ["ban"], ["banana"]]
   • Expected Output: [-1, -1, 0, 1, 1]
   • Justification: After inserting "banana", "apple" does not exist in the Trie but a word that starts with "ban", which is "banana", does exist.

3. Example 3:

   • Input:
     • Trie operations: ["Trie", "insert", "search", "startsWith", "startsWith"]
     • Arguments: [[], ["grape"], ["grape"], ["grap"], ["gr"]]
   • Expected Output: [-1, -1, 1, 1, 1]
   • Justification: After inserting "grape", "grape" exists in the Trie. There are words that start with "grap" and "gr", which is "grape".

Constraints:

• 1 <= word.length, prefix.length <= 2000
• word and prefix consist only of lowercase English letters.
• At most 3 * 10⁴ calls in total will be made to insert, search, and startsWith.

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