Engineering AnalyticsHow to Calculate and Analyze Code Churn Rate?

Hamza Ghufran · 2022-07-16

Code churn rate is the number of times changes are made to the code during the development cycle. Code churn is a natural part of the coding process and can fluctuate based on various factors. Code churn rates can be segregated into good and bad and be normalized across developers, teams, modules, and projects as well. 

Why is Code Churn Rates crucial for developers?

Code churn rate metrics are crucial to understanding the entire development process and the people involved - both the developer and the client. It helps identify the number of times changes are made to the code, which can indicate internal and external hurdles such as constant change by the teams to achieve perfection or changes made to accommodate unclear requirements. Measuring the code churn rate helps managers navigate through the entire development process and meet the deadlines without any hold-ups. There’s more - 

  • Code churn rates can help identify the nature of the feature under development. For instance, a new feature may demand multiple iterations to become fit for release, resulting in a spike in the code churn rate.
  • Can be an early indicator of scope creep as the higher rates can sometimes be the result of new features or requirements that were not initially agreed upon.
  • A higher code churn rate after feedback or a stand-up discussion translates to the feedback being implemented to the initial code base
  • Code churn rates also signal a red flag in the clarity of the deliverables, as unclear objectives may require the developer to work on the same task multiple times. 
  • Code churn rates can also indicate blockers in the development process and help the developer to get extra pairs of eyes and hands.
  • It also provides insights into the workload distribution and helps optimize resource allocation by identifying the areas of the code which are often changed and require more testing.
  • Tracking code churn rates help understand if the development process needs more testing or a push in the deadline and saves the team from last-minute surprises.
  • The churn rate should reduce or stabilize towards the deadline. Else, the code can be very volatile, or bug-prone after production. 

The iterative code churns cycles can be interpreted in two ways - the evolution of the developer working on the code or the evolution of the file during the development process. 

How to calculate the code churn rate? 

As mentioned earlier, code churn occurs when the developer deletes, updates, modifies, or rewrites sections or the entire code within 21 days of writing it. This code churns can be an indicator of something good, like code refactoring, or bad, like a non-linear development approach. However, the verdict can only be passed after the code churn rate calculation, which can be performed in two ways. 

  • One way for code churn rate calculation is to consider it as an aggregate of the number of lines of code added, deleted, and modified. For instance, if you have written over 1000 lines and deleted about 350 for whatever reason, the code churn rate is 35%. 
  • The other is file-based, where n number of updates/modifications happen to a file over a particular time, and the code churn rate calculation returns a value of n.
Code churn

Using this calculation managers should be able to track the pattern in code churn rates throughout the development cycle and identify at which stage of the process the number is higher. Ideally, they should also be able to classify higher code churns as good or bad by analyzing and understanding the cause and impact of it. Hence, managers should be equipped to differentiate between a normal code churn rate and an alarming one to steep in and take the necessary next steps.

Code Churn Rate - Good, Bad, or Ugly

Interpreting the nature of code churn is subject to various internal and external factors. If leveraged properly, code churn rate is a metric that is beneficial to both the managers and the developers as it enables them to assess and monitor the evolution of the code. It provides a real-time view into the development process and helps draws inferences on the progress, identify bottlenecks and take countermeasures earlier.

However, code change rates are not consistent. It varies across individuals, teams, projects, and even stakeholders. However, tracking code churn rates consistently can help managers classify and even arrive at normalized values across all departments. So, what makes a code churn rate good, and what gives it the tag of bad?

Github's code frequency graph

The Good Side of high code churn rates

A higher code churn rate can be alarming at first glance. But, it does not always signal a problem. Understanding the root behind the staggering number can sometimes help decode the proactive reasons listed below.

Experimentation

New modules sometimes demand a novel approach from the developer. During a time like this, the developer needs to work on a prototype code that can be different from earlier, resulting in higher code churn rates. This anomaly in the code churn is harmless or maybe productive. But, even a good reason like this can be problematic if it takes too much time right at the start of the development cycle and stretches the deadline beyond the allocated window. Hence managers should be vigilant while tracking code churn rates at different stages of the development cycle. 

Optimization

Skilled developers can draw up the logic behind the feature or the module in a relatively shorter time. Sometimes they complete the code and even achieve the desired output. So they formulate a way to make the run-time shorter by coming up with improvements and changes. This could increase the rate of code churn, but this optimization-oriented approach signals proactivity and does not affect the development process. This again can backfire if the developer spends too much time optimizing a single feature jeopardizing the rest of the allocated module or features.

Collaboration

Developers tend to help their colleagues whenever they feel stuck. During this collaboration, the new developer who has come onboard could suggest big and small changes that could result in multiple revisions to the existing code. The new changes can result in higher code change numbers that don’t signal an alarm. Even this new code churn rate should be monitored and ensured that only the necessary changes are made rather than committing to changing the entire blocks of code. This can result in resource leakage.

The Dark Side

Higher code churn that spells disaster can be nullified if managers track the churn trend from the beginning of the project. Organizations can further classify the reason for a higher code churn rate into internal and external.

Internal 

  • Overachievement: Organizations tend to focus on building the MVP version faster to get an idea of staying ahead. Sometimes, the fast-paced method can cause an overlook of the core functionalities or requirements which can result in higher churn rates in the future.
  • Perfectionism: Developers tend to rework the same blocks, only to make them perfect. This excessive attention to detail with no returns on the functionality can negatively impact the deadlines. 
  • Employee Burnout: Having high churn rates in the same areas of the codebase for an extended period can mean the developer is stuck. Not paying heed to the situation can cause the developer to develop boredom, a sense of not being competent, and ultimately, burnout. Managers can identify this by tracking code churn at regular intervals and taking corrective measures. Here's how organizations can weed out software engineer burnout

External

  • Tough feature: Sometimes, the clients can demand features or modules that are difficult to implement in a shorter period. Unprecedented requirements cause a spike in the code churn rates.
  • Added changes after release: External stakeholders may slip in new change requirements not mentioned in the Product Requirements Document during stand-ups or reviews. This can cause unnecessary reworks and code churns
  • Unclear requirements: Miscommunication among the team and the clients can cause chaos sprint after sprint, causing a chink in the armor of an optimal churn rate. Requirements should be made clear at the beginning of the development cycle and verified after every update. 

How to ensure you stay on the bright side? 

Developers should create a mockup of the development flow with the output and get affirmation of the same from the client. This can ensure everyone is on the same page about the deliverable and the deadlines, thus eliminating code churn rates due to external factors. Having a plan that depicts the goal, deliverables and deadlines can loosen the noose of higher code churn rates.

Closing Thoughts 

Code churn rates are subjective. Rather than targeting a low code churn rate and pushing it under the rug, organizations should start taking an analytical stand and understand it. Managers should equip their teams with the relevant data to optimize and reach a normalized, achievable goal. Companies should strategize a development cycle by leveraging insights that focus on planning, streamlining learning, and delivering on deadlines.

💡 One of the primary reasons engineering teams have not been able to leverage essentia code churn metrics is because measuring code churn has been complex and expensive. With Hatica’s engineering analytics platform, engineering managers and leaders can easily track this metric for their teams. Hatica seamlessly connects with Github, Gitlab or any other code hosting platform  to deliver code churn dashboards in minutes. Request a demo here to know more about Hatica and how it equips engineering leaders and teams with data-driven insights into their engineering development process. Request Demo!

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Table of Contents
  • Why is Code Churn Rates crucial for developers?
  • How to calculate the code churn rate? 
  • Code Churn Rate - Good, Bad, or Ugly
  • The Good Side of high code churn rates
  • The Dark Side
  • How to ensure you stay on the bright side? 
  • Closing Thoughts