Git Tricks for Onboarding to a New Codebase

2026년 4월 10일 · 약 3분

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High-Churn Files

git log --format=format: --name-only --since="1 year ago" | sort | uniq -c | sort -nr | head -20

Shows the most frequently changed files in the last year.
These files often represent areas of the codebase with the highest maintenance burden.
The top files can be cross-analyzed with bug hotspots to identify the highest-risk parts of the system.

git shortlog -sn --no-merges

Shows the number of commits by each author, excluding merge commits.
If one person accounts for more than 60% of commits, the project may have a bus factor risk.
If a top contributor has not been active in the last 6 months, it may indicate a maintenance gap.
With only 3 out of 30 contributors active over the past year, this suggests a knowledge discontinuity caused by developer turnover.
However, if the team uses squash merges, the commit history may be misleading for this analysis.

Shows the top 20 files with the most bug-related commits.
By comparing this list with the high-churn files, we can identify code that is both frequently changed and bug-prone.
While the accuracy depends on the quality of commit messages, even an approximate bug hotspot map can still be useful.

git log --format='%ad' --date=format:'%Y-%m' | sort | uniq -c

Monthly commit counts provide a visual view of project activity over time.
A consistent or increasing commit frequency suggests healthy development.
A sudden drop, such as a 50% decrease in commits within a month, may signal the departure of key contributors or a shift in project focus.
A sustained decline over 6-12 months suggests a loss of team momentum, while periodic spikes followed by stagnation may indicate a batch-style release pattern.
In one real-world case, a CTO recognized from a commit velocity chart that a specific point in time aligned with the departure of a senior engineer.
This data reflects not just code activity, but team dynamics.

git log --oneline --since="1 year ago" | grep -iE 'revert|hotfix|emergency|rollback'

Measures the frequency of urgent fixes and recovery actions.
A few incidents per year are normal, but incidents every two weeks may signal a lack of trust in the deployment process.
This often indicates deeper issues such as unstable tests, the absence of a staging environment, or complex rollback procedures.
A result of zero may indicate either a stable codebase or poorly labeled commit messages.
Crisis patterns tend to be clearly visible, and their mere presence is often enough to assess operational reliability.