First, clarify the problem: a jammed string is formed by repeating each character of the original word one or more times. Then, design a data structure that indexes dictionary words by their run-length encoded signature (character and count) to enable fast queries. For each query, compute its signature and use the index to retrieve candidate words, verifying matches efficiently.
Pro tip: Emphasize that the run-length encoding of the query must exactly match the run-length encoding of the word in terms of character sequence, but the counts in the query must be greater than or equal to the counts in the word. This insight allows you to quickly eliminate impossible matches like 'banana' vs 'hheelllo' because the character sequences differ.
Confirm that the jammed string is produced by repeating each character of the original word one or more times, and that the dictionary is static. Discuss potential constraints like dictionary size, query frequency, and memory limits.
Define that a word matches a query if their run-length encoded sequences have the same characters in the same order, and for each character, the query's count is >= the word's count. This condition is necessary and sufficient.
Compute the run-length encoding for each dictionary word and build an index keyed by the character sequence (e.g., 'helo' for 'hello'). Store the count vectors for each word under its key.
For a query, compute its run-length encoding. Use the character sequence as a key to retrieve candidate words from the index. For each candidate, check if the query's counts are >= the word's counts. Return all matches.
Discuss time and space complexity: preprocessing O(total characters in dictionary), query O(length of query + number of candidates). Consider edge cases like empty strings, single-character words, and queries with no matches.
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