Empirical Study of PR Review Throughput on a Mid-Sized Monorepo
Overview
What this challenge is about.
Pull 8 weeks of PR data from the monorepo (~3,800 PRs across 12 teams) covering open-to-merge time, review-comment count, review-round count, reviewer count, lines changed, and author tenure. State 3 falsifiable hypotheses (e.g. 'PRs reviewed by >2 reviewers take >1.6x longer to merge'). Pick statistical tests appropriate per hypothesis (Mann-Whitney for non-normal distributions, Spearman for correlation). Run analysis in a Jupyter notebook with reproducible cell outputs. Author a 6-page report covering methodology, findings (with effect sizes + confidence intervals), threats to validity, and 3 actionable recommendations for the platform team. Deliver study design, dataset, notebook, and report.
The Brief
What you'll do, and what you'll demonstrate.
Run an empirical study on monorepo PR review throughput with statistically defensible findings and actionable recommendations.
Earning criteria — what you'll demonstrate
- Design an empirical SE study with falsifiable hypotheses
- Pick appropriate statistical tests for non-normal SE data
- Report effect sizes and threats to validity honestly
- Translate empirical findings into team-level recommendations
Program Fit
Where this fits in your program.
Sharpens the same skills your degree expects you to demonstrate.
Skills
Skills you'll demonstrate.
Each one shows up on your verified credential.
Careers
Roles this prepares you for.
Real titles. Real skill bridges. Pick the one closest to your trajectory.
Career mappings coming soon.