ML Bug Squash: NaN, Distribution, ROC-AUC

Bug SquashStripeLast reported August 2025Low Frequency
Reported
2× across candidate reports
First seen
January 2025
Last reported
August 2025
Reported outcome
unknown

Problem Overview

You are given a web-based VS Code environment (or similar IDE with debugger support) and a Python ML codebase with three planted bugs to find and fix: 1. Test_score / NaN bug: The score output is NaN, blocking all downstream calculations. The root cause is that the data generation logic…

  • 2 candidate-reported follow-ups — the exact probes interviewers asked, with the trigger for each
  • The rest of the problem statement — full requirements, constraints, and edge cases
  • Approach and trade-offs — what passing candidates did, and the mistakes that sink people
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Verified Source
Every question is reconstructed from multiple independent candidate reports. Verbatim follow-ups, not invented ones.
Codex Fact-Checked
Technical claims, formulas, and scale numbers are reviewed against primary sources.
Interviewer Follow-ups
The exact follow-ups reported by candidates, with the trigger that prompts each one — plus the mistakes that sink people.
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