At senior and staff levels, many technical interviews include a code walkthrough: you are given a piece of code and asked to explain what it does, find issues, or reason about its behavior. Most candidates are underprepared for this — not because they can't read code, but because they've never practiced explaining it under pressure.
When an interviewer asks you to explain code, they are not checking whether you can read syntax. They are checking three things: do you understand what the code actually does at a meaningful level of abstraction? Do you notice things that matter — edge cases, performance characteristics, design decisions? And can you communicate it clearly to someone who hasn't read the code?
Candidates who fail code walkthroughs almost never fail because they misread a line. They fail because they narrate instead of explain — reading the code back to the interviewer word by word, which demonstrates decoding, not comprehension. The goal is to make the interviewer feel they now understand the code better than before you spoke.
The most common mistake in a code walkthrough is starting at line 1 and reading to the end. This produces a narration, not an explanation. An interviewer listening to line-by-line narration learns nothing about your comprehension — they already know what the code does.
Start with the what: 'This function takes a list of transactions and returns the running balance after applying each one, handling negative balances by clamping to zero.' One sentence that captures the purpose. Then go deeper into how it achieves that, and what it gets wrong or right.
Think-aloud is a method from cognitive science research: you verbalize your reasoning in real time as you perform a task. In software engineering research it is used to study how developers actually read code — what they notice, what they skip, what confuses them. In an interview, it is your most powerful tool.
The difference between a candidate who thinks silently and then gives an answer, versus one who verbalizes the reasoning as it develops, is significant. Verbalizing forces you to commit to intermediate conclusions — 'this function seems to be building a cache key, and if that is right then...' — which gives the interviewer something to react to and redirect. It also prevents the most common failure mode: spending five minutes reading in silence, then giving a wrong answer with no path to correction.
The insight dimension is where candidates separate themselves. Any developer can describe the happy path. The question is: what happens when the input is empty? What happens when the value overflows? What happens if the dependency throws?
Train yourself to ask these questions systematically after summarizing each function: what inputs would break this? What assumptions are embedded here that are not validated? What would happen if this ran concurrently? You do not need to answer all of them in depth — naming them shows awareness.
Senior engineers are expected to reason about code quality, not just correctness. If you see an O(n²) loop where an O(n) solution exists, say so. If you see a design that would not scale, note it. If you see defensive code that handles a case the rest of the codebase probably never triggers, mention the assumption.
This does not mean criticizing the code — it means demonstrating that you think about code in multiple dimensions simultaneously. Good interviewers reward candidates who can hold correctness, performance, and maintainability in mind at the same time.
Most interview prep materials use toy code: simple, clean, purpose-built for the exercise. Real codebases are messier — inconsistent naming, mixed abstractions, implicit dependencies. Practicing with real code closes the gap between preparation and the actual interview.
The highest-leverage practice is to read a piece of real code you did not write, write a full explanation of it, and then get feedback on that explanation. Not feedback on whether you identified the bug — feedback on whether your explanation was accurate, complete, clear, and insightful. That feedback loop, repeated deliberately, is what builds interview-level code reading skill.