Approach
Understanding Input and Output: Identify the input as an array of product names and a search word. The goal is to find names that match the prefix of the search word at each character input.
Building Suggestions: For each character typed, filter the product names based on the current prefix formed by the search word.
Sorting and Limiting Results: Sort the filtered results lexicographically and limit the output to three suggestions.
Key Points
Prefix Matching: Ensure the suggestions start with the characters typed in the search word.
Lexicographical Order: Always sort the results to return the smallest names first.
Dynamic Response: Provide an updated list of suggestions at each character input.
Standard Response
Tips & Variations
Common Mistakes to Avoid:
Failing to sort the product list initially can result in incorrect suggestions.
Not updating the prefix correctly with each character input will lead to inaccurate matches.
Alternative Ways to Answer:
Use a Trie data structure for more efficient prefix searching if handling a large dataset.
Role-Specific Variations:
Technical Roles: Emphasize the efficiency of your algorithm, perhaps discussing time complexity.
Creative Roles: Focus on the user experience and how intuitive the search feature is.
Follow-Up Questions
How would you modify your solution if the product list is extremely large?
Can you explain how you would implement this using a Trie?
What edge cases did you consider while developing your solution?