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Roblox·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
Jun 2026

Summary

Roblox software engineering interview with a parsing and data structure problem. Pretty focused on getting the implementation right under pressure.

Questions Asked (1)

Q1

Given a log of function call and return events, parse the log to reconstruct the active call path at every point in time, then count how many times each distinct call path appears across the entire log and return a mapping of call path to count.

Algorithms & Data StructuresSystem Design
Author's notes

The stack part clicked fast but I fumbled a bit on how to serialize the path for the hash map key.

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AI HintsAI Generated

Suggested Approach

Use a stack to track the active call path, pushing on call events and popping on return events, and record the current path at each event. Then, use a hash map to count the frequency of each distinct path. Clarify the log format and whether paths are represented as sequences of function names or unique call IDs.

Pro tip: Clarify whether the log includes timestamps and if multiple events can occur at the same time; also discuss handling of malformed logs or unmatched returns to demonstrate robustness.

1. Clarify log format and requirements

Ask about the structure of log entries (e.g., call/return, function names, IDs) and whether paths are defined by function names or unique call instances. Confirm the output format and any constraints.

2. Design stack-based parsing

Use a stack to maintain the current call path. On a call event, push the function identifier; on a return event, pop the top. Record the current path after each event.

3. Count path occurrences

Use a hash map to count how many times each distinct path appears. Convert the stack to a string or tuple to use as a key.

4. Handle edge cases

Consider unmatched returns, nested calls, and empty paths. Discuss error handling or assumptions (e.g., log is well-formed).

5. Analyze complexity and optimize

Time complexity is O(n) for n events, but path recording may add overhead. Discuss trade-offs and potential optimizations like incremental hashing.

Key Points to Mention

  • Stack data structure for tracking call hierarchy
  • Hash map for counting path frequencies
  • Time and space complexity analysis
  • Handling of edge cases (unmatched returns, empty log)
  • Representation of call paths (e.g., string concatenation vs. tuple)
  • Potential optimizations for large logs (e.g., incremental hashing)

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