The base logic isn't hard but the edge cases piled up fast.
Clarify the requirements first, especially around case sensitivity, punctuation, and whole-word matching. Then outline a solution that tokenizes the sentence while preserving delimiters, filters out matching words, and reconstructs the sentence. Discuss trade-offs between different approaches (e.g., regex vs. manual parsing) and analyze time/space complexity.
Pro tip: Demonstrate attention to edge cases like punctuation attached to words (e.g., 'hello,' vs 'hello') and discuss how to handle them without breaking the original formatting. Also, mention that using a set for keywords improves lookup efficiency from O(k) to O(1) per word.
Ask about case sensitivity, punctuation handling (e.g., should 'Hello,' match 'hello'?), and whether matching should be whole-word only. Confirm if the output should preserve original spacing and punctuation.
Use a set for the keyword list to enable O(1) lookups. For tokenization, consider using regex to split while preserving delimiters, or manually iterate through the string.
Tokenize the sentence into words and non-word characters (delimiters). For each word, normalize case if needed, strip punctuation for matching, and check against the keyword set. If not a match, keep the original word (with punctuation) in the output.
Consider empty keyword list, empty sentence, multiple spaces, punctuation at start/end of words, and case variations. Ensure the output doesn't have extra spaces or missing punctuation.
Time complexity: O(n + k) where n is sentence length and k is keyword list size (for set construction). Space complexity: O(n) for output. Discuss if regex might be slower due to overhead.
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