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linktree·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
Jun 2026

Summary

Interviewed for a Software Engineer role at Linktree and got a string parsing problem that looked deceptively straightforward. The camelCase decomposition angle was a nice twist on the usual word-break stuff.

Questions Asked (1)

Q1

Given a dictionary of lowercase words and a variable name string, determine if the variable name is a valid camelCase concatenation of words from the dictionary. The first segment must be all lowercase, and each subsequent word must start with an uppercase letter followed by all lowercase.

Algorithms & Data Structures
Author's notes

My first instinct was just word break DP and I started coding that before I even registered the camelCase constraint.

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AI HintsAI Generated

Suggested Approach

Clarify the problem constraints and edge cases first, then propose a greedy two-pointer or dynamic programming solution that scans the string while matching dictionary words. Walk through the algorithm with a concrete example, analyze time and space complexity, and discuss potential optimizations or alternative approaches.

Pro tip: Mention that you can use a trie or hash set for O(1) word lookups, and emphasize that the greedy approach works because the camelCase structure forces unique segmentation—no backtracking needed. This shows you understand the problem's inherent constraints.

1. Clarify requirements and edge cases

Ask about dictionary size, word length limits, empty strings, and whether the variable name can be a single word. Confirm that the first segment must be all lowercase and subsequent segments must start with uppercase followed by lowercase.

2. Outline a greedy parsing strategy

Explain that you can scan the string from left to right, identifying segments by uppercase letters. For the first segment, take all leading lowercase letters; for subsequent segments, take an uppercase letter followed by all following lowercase letters until the next uppercase or end.

3. Validate segments against the dictionary

Use a hash set or trie for O(1) lookups. Check each extracted segment against the dictionary; if any segment is not found, return false. If all segments are valid, return true.

4. Analyze complexity and discuss optimizations

State that the time complexity is O(n) where n is the length of the variable name, as each character is processed once. Space complexity is O(m) for the dictionary storage. Mention that a trie could reduce memory if the dictionary is large.

5. Test with examples and edge cases

Walk through examples like 'camelCase' with dictionary ['camel', 'case'] and edge cases like empty string, single word, or invalid segmentation. Confirm the algorithm handles them correctly.

Key Points to Mention

  • Greedy parsing is sufficient because camelCase boundaries are uniquely determined by uppercase letters.
  • Use a hash set or trie for efficient word lookup.
  • Time complexity O(n) and space complexity O(m) for dictionary storage.
  • Handle edge cases: empty string, single word, no valid segmentation.
  • The first segment must be all lowercase; subsequent segments must start with uppercase and be followed by lowercase.
  • Consider if the dictionary contains words that are prefixes of others and how that affects parsing.

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