Check strings against dictionary efficiently
Company: Reevo
Role: Software Engineer
Category: Coding & Algorithms
Difficulty: medium
Interview Round: Take-home Project
Given a large dictionary of unique words and a list of query strings, return for each query whether it exists in the dictionary. The dictionary may contain up to 1,000,000 words and the query list up to 100,000 strings. Optimize for many queries and minimal memory overhead. Describe your chosen data structure(s), expected time and space complexity, and how you would handle case sensitivity, Unicode normalization, and duplicate queries.
Quick Answer: This question evaluates skills in efficient membership testing for large datasets, memory-time trade-offs in data structures, and string handling concerns such as case sensitivity and Unicode normalization.
Given a large dictionary of unique words and a list of query strings, return for each query (in order) whether it exists in the dictionary.
Implement `solution(dictionary, queries)` that returns a list of booleans where the i-th element is `true` if `queries[i]` is present in `dictionary`, and `false` otherwise.
The dictionary may contain up to 1,000,000 words and the query list up to 100,000 strings, so optimize for many lookups: build a hash set from the dictionary once (O(N)) and answer each query in expected O(1). Comparison is exact and case-sensitive ('Cat' and 'cat' are distinct).
Example:
dictionary = ["apple", "banana", "cherry"]
queries = ["apple", "grape", "cherry"]
returns [true, false, true]
Constraints
- 0 <= len(dictionary) <= 1,000,000
- All words in dictionary are unique
- 0 <= len(queries) <= 100,000
- Comparison is exact and case-sensitive
- Strings consist of printable characters
Examples
Input: (['apple', 'banana', 'cherry'], ['apple', 'grape', 'cherry'])
Expected Output: [True, False, True]
Explanation: 'apple' and 'cherry' are in the dictionary; 'grape' is not.
Input: ([], ['apple'])
Expected Output: [False]
Explanation: Empty dictionary: no query can match.
Hints
- Build a hash set from the dictionary once so each membership check is expected O(1) instead of scanning the whole list per query.
- Process queries in order and append the boolean result for each — duplicate queries simply produce repeated results.
- Be explicit about case sensitivity: by default exact comparison means 'Cat' != 'cat'. If you needed case-insensitive matching you would normalize (e.g. casefold) both the dictionary and the queries before inserting/looking up.