How did you verify the correctness of your work?
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What is this question about
Interviewers ask this to understand whether you treat correctness as something to be proven rather than assumed. They want to see how you matched your verification approach to the risk, ambiguity, and scope of the work, and whether you closed the loop after implementation instead of stopping at "it seemed to work." At higher levels, they also care whether your verification strategy protected other engineers, customers, or the business from subtle failure modes.
Key Insights
- You should not frame verification as just "I tested it." Strong answers show layered thinking: what could go wrong, which checks were appropriate, and how you gained confidence before and after release.
- Don't stop at happy-path validation. Interviewers notice when you mention edge cases, observability, rollback plans, or production checks because that shows you understand correctness under real conditions, not just in development.
- Match the sophistication of your answer to your level. A junior candidate can win with careful personal validation; a staff or manager candidate should show how verification scaled across people, systems, or teams.
What interviewers probe atlevel
Top Priority
A strong answer usually includes more than one way you checked the work, because any single check can miss something.
Good examples
đ˘I wrote a unit test for the logic and also exercised the UI manually, since the bug involved both calculation and display.
đ˘I compared the output before and after the change on a few sample records, and I also asked a teammate to confirm the behavior matched the requirement.
Bad examples
đ´I clicked through the feature myself, and since it worked the first time I considered that enough verification.
đ´I depended on the automated tests already in the project, so once they passed I felt confident the change was correct.
Weak answers rely on one source of confidence; strong answers combine checks that catch different categories of mistakes.
Valuable
Example answers atlevel
Great answers
On a recent bug fix, I changed the logic that calculated shipping cost for small orders. To verify it was correct, I first wrote a couple of tests around the exact cases from the bug report, and then I added edge cases like a zero-dollar order and a value right at the free-shipping threshold. After that, I ran the app locally and checked that the total shown in the UI matched the numbers I calculated by hand. Once it was deployed, I looked at a few real orders in production and confirmed the totals were now correct there too. That gave me confidence I hadn't just fixed the narrow case, but the actual behavior users cared about.
At my last internship, I added a simple admin page that let our support team update a userâs contact information. To make sure it worked, I first tested it with a few made-up accounts in our staging environment and tried both valid and invalid inputs, like empty phone numbers and badly formatted email addresses. I also asked the support lead to walk through the flow with me, because they were the person who would actually use it every day and could tell me if anything felt confusing. After that, I checked the database directly to confirm the changes were saved exactly as expected and that the old values were replaced. I liked this approach because it wasnât just about âdoes the code run,â but about whether the feature was reliable for the people who depended on it.
Poor answers
I usually verify my work by running the feature once before I open the pull request. In this case I clicked through the flow, the page loaded, and the result looked right, so I felt pretty confident it was correct. My reviewer approved it as well, which was another good signal. After that I considered it done and moved on.
Question Timeline
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Early June, 2026
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