I went straight to regex and said we could just compile each pattern and run them all.
Start by clarifying requirements and constraints, then propose a trie-based solution that handles wildcards efficiently. Explain how to traverse the trie while tracking the longest match and tie-breaking by list order. Discuss trade-offs between preprocessing time, query time, and memory usage.
Pro tip: Mention that you can preprocess patterns into a trie with wildcard transitions, and during matching, use BFS/DFS to explore all possible paths, keeping track of the best match. This shows you understand both algorithmic efficiency and practical implementation details.
Ask about input size, pattern length, number of patterns, and expected query frequency to determine if preprocessing is beneficial.
Propose a trie (prefix tree) where each node represents a character, and wildcard '*' is handled as a special transition that can match any substring.
Traverse the trie with the input string, exploring all possible paths when encountering '*', and track the longest match and its value, using list order for ties.
Discuss time and space complexity: preprocessing O(total pattern length), query time potentially exponential in worst case but optimizable with memoization or dynamic programming.
Compare with brute-force matching, mention memoization to avoid redundant states, and consider alternative approaches like regex or dynamic programming.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.