LinkedIn·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say

Apr 2026

Summary

LinkedIn coding interview with a phone keypad grouping problem. Pretty classic hash map territory but the twist of mapping letters to digits instead of grouping anagrams tripped me up for a minute.

Questions Asked (1)

Given a list of words, group together any words that map to the same digit sequence on a classic phone keypad (where 'abc' maps to 2, 'def' to 3, and so on). Return all groups.

Algorithms & Data Structures

Author's notes

My first instinct was anagram grouping and I almost went down that path before catching myself.

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AI HintsAI Generated

Suggested Approach

Clarify the problem and edge cases, then propose a hash map solution where each word is transformed into its digit sequence and used as a key to group words. Discuss time and space complexity, and consider follow-up optimizations or variations.

Pro tip: Demonstrate strong communication by walking through a concrete example (e.g., ['cat', 'bat', 'tree']) and explicitly handling edge cases like empty input or words with non-alphabetic characters. This shows attention to detail and real-world robustness.

1. Clarify requirements and constraints

Ask about input size, character set (only lowercase letters?), and whether groups should be returned as lists or any specific order. Confirm that words mapping to the same sequence should be grouped together.

2. Design the mapping and grouping strategy

Create a mapping from each letter to its corresponding digit. For each word, compute its digit sequence by concatenating the mapped digits. Use a hash map to group words by their digit sequence.

3. Analyze complexity and edge cases

State that time complexity is O(N * L) where N is number of words and L is average word length, and space complexity is O(N * L) for storing the groups. Mention edge cases: empty list, single word, words with same sequence but different lengths, and non-alphabetic characters.

4. Implement and test with examples

Write clean code (e.g., in Python) using a dictionary. Test with a small example like ['cat', 'bat', 'tree'] to verify grouping. Discuss potential optimizations like using a trie or precomputed mappings for large datasets.

5. Discuss extensions and trade-offs

Consider follow-up questions: How would you handle streaming input? What if the mapping changes? Compare hash map approach with sorting-based grouping (O(N log N * L)) and explain why hash map is preferred.

Key Points to Mention

Hash map (dictionary) for O(1) average-time grouping by digit sequence.
Precomputed mapping array or string for constant-time letter-to-digit conversion.
Time complexity: O(N * L) where N is number of words and L is average length.
Space complexity: O(N * L) to store the groups and keys.
Edge cases: empty input, words with uppercase or non-alphabetic characters, and words that map to the same sequence but have different lengths.
Potential optimizations: using a trie for prefix-based grouping or parallel processing for large datasets.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.