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What Sourabh demonstrated

Built and verified a full legacy-service repair for a car-maintenance repo: fixed the wear calculation with true division, handled missing service readings safely, corrected the nightly report’s average, and preserved the 15,000 km / 80% rules. Also added the missing regression test, documented the review process in NOTES.md, and produced a data-driven breakdown-risk analysis that ranks cars by the factors the fleet history actually supports.

  • Leakage-Free Bug Diagnosis
  • Bounded AI Prompting and Review
  • Acceptance-Driven Verification
  • Data-Driven Risk Analysis

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