The scenario
Repair cumulative histogram export while preserving weighted totals, finite overflow, and empty-population semantics.
A failure to reason about
Use a small observability scenario to compare the current behavior with the intended service behavior.
Illustrative context for the topic. The exercise’s full requirements arrive in the workspace.
Questions to bring to your review
- Which caller makes the reported behavior visible?
- What focused regression would distinguish the current behavior from the requirement?
- What existing behavior must remain intact after the change?
Skills you will practice
- Observability
- Domain contracts
- Regression testing
- AI change review
Read the existing code, reproduce the reported behavior, review proposed changes, and verify your final implementation. You can use AI assistance while staying responsible for the result.
Prepare with a worked example
- How to review AI-generated code in an interview
Work through a flawed AI patch, design a regression that exposes it, and explain a repair with evidence. A practical code-review exercise for AI-assisted interviews.
See how nrml evaluates an attempt, including the limits of automated evidence.