High Code Churn Isn't Bad. Unless You See This Pattern

Code churn—the rate at which code is rewritten or deleted—is one of the more nuanced engineering metrics. High churn isn't automatically bad, and low churn isn't automatically good. This guide helps you understand what churn reveals about your codebase and when to take action.

What Code Churn Measures

Definition

Code Churn Rate is the percentage of code changes that are deletions (as opposed to additions).

What High vs Low Churn Indicates

High churn (40%+): More code is being removed or rewritten than added. This often indicates:

• Active refactoring or cleanup
• Tech debt paydown
• Code consolidation or simplification
• Or: Frequent rework due to unclear requirements

Low churn (<15%): Most changes are net additions. This often indicates:

• Greenfield development
• Feature-heavy periods
• Or: Accumulating technical debt (no cleanup happening)

Interpreting Churn Rate

Context Matters

Churn rate is meaningless without context. The same rate can be healthy or concerning depending on your situation:

Team-Level vs Developer-Level

Churn rate can be measured at different levels:

• Repository level: Overall health indicator for a codebase
• Developer level: Individual work patterns (some people specialize in refactoring, others in new features)

Healthy vs Unhealthy Churn

What is Code Rework?

Code rework is a specific type of churn where recently written code is modified or rewritten shortly after its initial creation. While churn measures all deletions relative to additions, rework specifically tracks changes to code that was written in the recent past (typically within 21-30 days).

The distinction matters because:

• General churn includes intentional refactoring of old code—often a sign of healthy maintenance
• Rework suggests the initial implementation wasn't quite right, which may indicate unclear requirements, insufficient planning, or learning curves

A team might have healthy overall churn (30-40%) but concerning rework rates if most of that churn happens to code written in the last two weeks. Conversely, high churn with low rework often indicates a mature team actively improving their codebase.

Signs of Healthy Churn

• Planned refactoring: Churn spikes correlate with dedicated tech debt sprints or cleanup initiatives
• Codebase shrinking: Overall lines of code decreasing while functionality stays the same
• Simplification: Complex modules being replaced with simpler implementations
• Deprecation: Old features or APIs being removed as planned
• Test improvement: Rewriting tests to be more maintainable

Signs of Unhealthy Churn

• Thrashing: Same code being rewritten multiple times in short succession
• Requirements churn: Features implemented, then changed, then changed again due to unclear specs
• Bug fix churn: Repeated fixes to the same area because root causes aren't addressed
• Revert churn: Code being added then reverted frequently

How to Tell the Difference

Ask these questions about high-churn periods:

1. Was this planned? (Healthy) Or reactive? (Potentially unhealthy)
2. Is the same code churning repeatedly? (Unhealthy) Or different areas? (Healthy)
3. Are commit messages about improvement? (Healthy) Or fixes? (Investigate)
4. Is the team happy about the changes? (Healthy) Or frustrated? (Unhealthy)

Using File Hotspots with Churn

Churn becomes most useful when combined with file hotspot analysis:

The Danger Zone

High change frequency + High churn = Danger zone. This means a file is:

• Changed frequently (everyone touches it)
• Mostly rewrites (not stable additions)

This combination often indicates an unstable abstraction or unclear ownership. These files are candidates for:

• Architectural review
• Possible redesign
• Breaking into smaller, more stable pieces
• Clearer ownership assignment

Finding Danger Zone Files

Use the File Hotspots page to find frequently-changed files, then investigate their churn patterns.

Developer Churn Patterns

The "Refactoring Hero" Award

CodePulse's Awards system includes a "Refactoring Hero" category that recognizes developers with high churn rates. This celebrates the often-thankless work of:

• Cleaning up legacy code
• Paying down tech debt
• Simplifying complex systems
• Removing dead code

Individual Churn Context

Different developers naturally have different churn patterns based on their roles:

• New feature developers: Lower churn (mostly additions)
• Platform/infrastructure engineers: Higher churn (lots of refactoring and optimization)
• Bug fixers: Moderate churn (targeted changes)
• Tech debt specialists: High churn (cleanup focused)

Don't compare developers' churn rates directly—compare them to their own historical patterns and their assigned work type.

Team Strategies

Allocating Refactoring Time

If your churn is consistently low (<20%) for a mature codebase, you may not be investing enough in maintenance:

• 20% rule: Allocate roughly 20% of sprint capacity to tech debt and refactoring
• Boy scout rule: Leave code better than you found it (small improvements with each PR)
• Tech debt sprints: Periodic dedicated cleanup sprints

Tracking Tech Debt Paydown

Use churn trends to validate that tech debt investment is happening:

• After a "tech debt week," churn should spike temporarily
• Consistent moderate churn (25-35%) suggests healthy maintenance cadence
• Persistently low churn despite known debt suggests it's being deprioritized

Communicating Churn Value

Refactoring work is often invisible to stakeholders. Use churn data to demonstrate value:

Warning Signs to Watch

• Churn dropping to near zero: May indicate all effort going to features, accumulating debt
• Churn spiking without explanation: Investigate—could be thrashing or scope changes
• Same files churning repeatedly: Unstable area needing architectural attention
• High churn + high bug rate: Changes aren't improvements, they're chasing problems

Combining with Other Metrics

Churn is most valuable when combined with:

• Test failure rate: High churn + stable tests = good refactoring. High churn + test failures = risky changes.
• Cycle time: High churn PRs often take longer to review— plan accordingly.
• Risk score: Large deletions in critical paths warrant extra review scrutiny.