InterSystems·Software Engineer·Technical Phone Screen·Intermediate

Intermediate

Jun 2026

Summary

InterSystems software engineer interview where they hand you a chunk of their own real code and ask you to tear it apart. Not a leetcode grind, more like a code review session with someone watching over your shoulder.

Questions Asked (1)

You are given a snippet of real code from the interviewer's codebase. Walk through it, identify any bugs or design issues, propose fixes, and reason through edge cases. The interviewer will give hints if you get stuck.

Root Cause AnalysisTechnical Trade-offsSystem Design

Author's notes

This format tripped me up more than I expected.

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AI HintsAI Generated

Suggested Approach

Start by restating the code's purpose and walking through its logic line by line, verbalizing your assumptions. Identify bugs and design issues as you go, then propose concrete fixes and discuss edge cases and trade-offs. Engage with the interviewer's hints to show collaboration and adaptability.

Pro tip: Treat the interviewer as a teammate: ask clarifying questions about requirements and constraints before diving into fixes. This demonstrates real-world engineering maturity and often reveals hidden expectations.

1. Understand and Restate

Briefly summarize what the code is supposed to do and its context. Ask clarifying questions if anything is ambiguous.

2. Walk Through Logic

Trace the code line by line, explaining the flow and state changes. Note any assumptions you're making about inputs or environment.

3. Identify Issues

Point out bugs (e.g., off-by-one, null dereference) and design problems (e.g., poor naming, lack of error handling). Prioritize by severity.

4. Propose Fixes

Suggest specific code changes or refactors for each issue. Explain why the fix works and any trade-offs involved.

5. Analyze Edge Cases

Discuss edge cases (empty input, large data, concurrency) and how the fixes handle them. Consider testing strategies.

Key Points to Mention

Correctness: off-by-one errors, null/undefined handling, type mismatches
Design: separation of concerns, modularity, naming, error handling
Performance: time/space complexity, unnecessary allocations, caching
Edge cases: empty inputs, boundary values, concurrent access, failure modes
Testing: unit tests, property-based tests, mocking dependencies
Trade-offs: simplicity vs. flexibility, readability vs. performance

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