Choosing a technical interview format starts with the work the candidate will actually do. Code review and algorithm exercises answer different questions, and a strong hiring process uses that difference deliberately.
At a Glance
| Question | Code review interview | Algorithm interview |
|---|---|---|
| Primary signal | Reasoning, judgment, communication | Decomposition, correctness, fluency |
| Typical work | Review a realistic change | Build a small solution from scratch |
| Strong differentiator | Prioritization and trade-offs | Data structures and complexity |
| Common risk | Vague or unfair prompts | Memorization and puzzle framing |
| Best fit | Senior and role-specific evaluation | Early-stage screening and shared baselines |
Neither column is a universal ranking. A backend engineer who reviews pull requests every day may provide stronger evidence in a code review round than in a generic graph problem. A candidate who needs a shared baseline for algorithmic fluency may benefit from a constrained exercise.
When Code Review Fits
Code review is a strong choice when the role involves:
- •reviewing pull requests or proposed changes;
- •debugging an existing system rather than starting from zero;
- •making decisions about security, performance, and maintainability;
- •explaining trade-offs to another engineer;
- •working in a language or framework the team already uses.
Give the candidate a bounded change, a short user story, and a clear instruction to explain findings before editing. Ask for one focused refactor after the review. This keeps the exercise connected to real work without turning it into an open-ended debugging session.
When Algorithm Practice Fits
Algorithm practice is useful when the team needs a shared baseline for:
- •problem decomposition;
- •basic data-structure fluency;
- •reasoning about time and space complexity;
- •communicating a solution while tests and edge cases evolve.
Make the prompt small enough to finish in the timebox, state the constraints, and define what a good discussion looks like. The goal is not to reproduce a contest problem; it is to observe how the candidate turns an ambiguous request into a workable plan.
A Balanced Combined Loop
For a role that needs both signals, a 60-minute session can work:
- 10 minutes: Context and clarifying questions.
- 15 minutes: Review a small change and prioritize two or three findings.
- 25 minutes: Implement one focused fix or a small related task.
- 10 minutes: Debrief trade-offs, verification, and what the candidate would do next.
Keep the same rubric for every candidate. Track the evidence separately: review signal, implementation signal, communication, and role-specific knowledge.
Design Principles
- •Give every candidate the same amount of context and time.
- •Prefer a few meaningful flaws over a long list of hidden traps.
- •Explain that there is more than one valid approach.
- •Do not score confident guesses above well-reasoned prioritization.
- •Separate correctness blockers from maintainability suggestions.
- •Give candidates a way to ask questions, just as they would in a real review.
Choose the Right Practice Material
For a review-first loop, start with Code Review Interview Questions and Exercises and the live code review library. For backend and API-heavy roles, use Backend Code Review Interview. For a shared implementation baseline, browse the coding interview problem library.
Whichever format you choose, document the rubric before the session and evaluate the same evidence for every candidate.
Frequently Asked Questions
Is a code review interview better than an algorithm interview?
Neither format is universally better. Code review is closer to everyday engineering work, while algorithm practice can be useful for assessing decomposition and fluency with common data structures. Choose the format that matches the role and the evidence you need.
Can one interview combine both formats?
Yes, but keep each part bounded. A short review round followed by one focused implementation task can provide broader signal without turning the session into an endurance test.
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