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Molocoads·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
May 2026

Summary

Interviewed at Molocoads for a software engineering role and got a string problem that looks deceptively simple until you think about the constraints. The brute force is obvious but won't pass, so knowing your trie fundamentals matters here.

Questions Asked (1)

Q1

Given two lists of strings A and B, pick one string from each list and return the maximum possible length of their longest common prefix.

Algorithms & Data Structures
Author's notes

My first instinct was just brute force every pair and track the max prefix length.

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AI HintsAI Generated

Suggested Approach

Clarify the problem constraints and edge cases, then propose an efficient algorithm. A trie-based approach can find the maximum LCP by inserting all strings from one list and querying with strings from the other, but also consider sorting and binary search as alternatives. Discuss time/space complexity and trade-offs.

Pro tip: Mention that you can optimize by only considering strings that share the first character, and if the lists are large, a trie is more efficient than pairwise comparison. Also, handle empty strings and no common prefix gracefully.

1. Clarify the problem

Ask about constraints: list sizes, string lengths, character set, and whether empty strings are allowed. Confirm that you need the maximum LCP over all pairs (one from each list).

2. Discuss brute force and its complexity

Mention that comparing all pairs takes O(|A|*|B|*L) time, which is inefficient for large inputs. This sets the stage for optimization.

3. Propose efficient approaches

Describe a trie-based solution: insert all strings from the smaller list into a trie, then for each string in the other list, traverse the trie to find the longest common prefix. Alternatively, sort both lists and use binary search or two pointers to find the maximum LCP.

4. Analyze complexity and trade-offs

For trie: O((|A|+|B|)*L) time and O(|A|*L) space. For sorting: O(|A|log|A| + |B|log|B|) time and O(1) extra space. Discuss which is better based on constraints.

5. Handle edge cases and conclude

Cover cases like empty lists, empty strings, no common prefix, and very long strings. Summarize the chosen approach and why it's optimal.

Key Points to Mention

  • Definition of longest common prefix (LCP) and how it applies to pairs of strings.
  • Trie data structure and its use for prefix matching.
  • Time and space complexity analysis for different approaches.
  • Edge cases: empty strings, no common prefix, large input sizes.
  • Optimization: only consider strings with matching first character.
  • Trade-offs between trie and sorting-based approaches.

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