How to Measure Code Simplicity

Learn about Code Simplicity, including how to measure it, and leverage it in dashboards and visualizations with Metabase.

What is Code Simplicity?

Code simplicity covers a number of different measurements. As a general rule of thumb, most people involved in software engineering understand that having clean code is essential. Code simplicity can tell you more about how efficient code being written is. Being able to measure code simplicity can help you learn more about the efficiency of code in a variety of ways depending on your specific needs.

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Graphs of Code Simplicity

How to calculate Code Simplicity

Typically code simplicity is calculated with different tests for different things. For example, you can test for cyclomatic complexity, which is a test that measures the number of independent paths a code must take in order to complete a task. You should also use code simplicity for risk assessment. Areas with complicated code can be more prone to bugginess and lessen reliability. One of the biggest facets of assessing code simplicity is peer review. Allowing teams to help each other with code can help others get on the same page and work more efficiently. This can help with onboarding new employees as well.

Other KPIs to measure related to Code Simplicity

  • Application Change Time — how long application changes take to move from request to running in production.
  • Application Monitoring — coverage and health of the monitoring that watches your applications in production.
  • Change Volume — how much change ships per period — commits, pull requests, or releases.
  • Commit to Deploy Time — the lag between a commit landing and that change running in production.
  • Cost Performance Indicator — earned value divided by actual cost — whether delivery is tracking the budget.
  • F1 Score — the harmonic mean of precision and recall for a classification model.
  • Flow Efficiency — active work time as a share of total elapsed time — how much of the cycle is waiting.
  • Issue Resolution Time — how long issues take from report to resolution, best tracked with medians and percentiles.
  • Machine Learning Performance — accuracy, drift, and latency of machine learning models in production.

Why build a dashboard for Code Simplicity?

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How to use Metabase to measure Code Simplicity

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