Design a System for Autocomplete (Trie)

To design this system, I would start by defining a TrieNode structure where each node contains a hash map of children characters, a boolean flag indicating if a word ends here, and a list to store frequent completions. First, we initialize the root. When inserting a word, we traverse character by character, creating new nodes as needed. Crucially, at every node along the path, we append the current word to a local list of suggestions, limiting this list to the top five most frequent entries to manage memory. For the query phase, given a prefix like 'tes', we traverse down the Trie. If we reach a null pointer, we return empty. Otherwise, we perform a DFS from the last valid node. During this DFS, we collect all words marked as complete. To ensure efficiency, we use a min-heap of size k to keep only the top suggestions based on frequency or lexicographical order. This approach ensures that insertion is proportional to the word length and queries are efficient, providing instant feedback similar to what users expect in Tesla's infotainment search bar.