← Roblox Interview Insights

Roblox·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say
Jun 2026

Summary

Roblox software engineer round focused on a single meaty coding problem around program trace reconstruction. Pretty systems-flavored for what felt like a standard technical screen, and the follow-up pushed into parsing flexibility which I wasn't fully ready for.

Questions Asked (1)

Q1

Given a stream of function-entry and function-exit events from a running program, reconstruct the call stack. You need to parse the trace input, maintain the active stack, and be able to report the current stack state at any point.

Algorithms & Data StructuresSystem DesignTechnical Trade-offs
Author's notes

My first instinct was just a plain stack with push on entry and pop on exit, which is correct but I spent too long explaining it before writing any code.

Create a free account to read the full note

AI HintsAI Generated

Suggested Approach

Start by clarifying the input format and requirements, then design a solution using a stack data structure to track function calls. Explain how to parse events, push on entry, pop on exit, and report the current stack. Discuss time and space complexity, and consider edge cases like mismatched events.

Pro tip: Mention that you would validate the trace for consistency (e.g., exit without matching entry) and discuss how this approach scales to large traces or real-time processing, showing awareness of production concerns.

1. Clarify requirements and input format

Ask about the event format (e.g., JSON, CSV), whether events are well-formed, and what 'report' entails (e.g., print, return list). Confirm if multiple stacks or threads are involved.

2. Design the data structure and algorithm

Use a stack (LIFO) to maintain active calls. On entry, push the function name; on exit, pop. For reporting, return a copy of the stack or its size.

3. Handle edge cases and errors

Check for exit events without matching entry (underflow) and entry events without exit (incomplete trace). Decide whether to ignore, log, or throw errors.

4. Analyze complexity and scalability

Each event is O(1) time; space is O(depth of stack). For large traces, consider streaming processing to avoid storing all events.

5. Discuss extensions and trade-offs

Mention how to handle multiple threads (separate stacks), recursion depth limits, or adding timestamps for profiling. Compare stack vs. tree representation.

Key Points to Mention

  • Use of stack data structure for LIFO order of function calls
  • Parsing input efficiently, possibly line-by-line for large streams
  • Handling mismatched events (exit without entry) gracefully
  • Time complexity O(n) for n events, space O(d) for max depth d
  • Reporting current stack state by returning a copy or printing
  • Potential for real-time monitoring and integration with profilers

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