Which metric is least useful when measuring code maintainability?

Code maintainability is one of the main aspects of a codebase. It refers to how easily the code can be understood, corrected, adapted, and enhanced. Although many consider maintainability mainly to affect developers’ productivity, there are many other reasons for improving code maintainability. For example,

• Reducing the cost of future code changes.
• Ensuring future developers can easily understand code.
• Making the code adaptable for rapid changes.
• Reducing the risk of errors, bugs, vulnerabilities, and system failures.

If code maintainability is this important, we should have a standard way to measure it and find maintainability issues in our code to improve our codebase. For that, you can use code quality measuring tools like SonarQube, CodeClimate, or Checkstyle. They provide various metrics related to code maintainability, like cyclomatic complexity, code coverage, lines of code, etc.

But the important question is: Do we need to consider all these metrics? The short answer is NO. The usefulness of the metrics can vary based on different factors like project requirements, complexity, software type, tech stack, etc. This article will help you understand which metric is the least useful for your project when measuring code maintainability.

Maintainability Metrics

Before evaluating the effectiveness of maintainability metrics, it is essential to understand the different metrics available and what they measure:

• Cyclomatic complexity: The number of linearly independent paths through the code.
• Code churn: The frequency and volume of code changes over time.
• Technical debt: The cost and effort required to fix issues in the code that have been deferred.
• Code coverage: The percentage of the codebase covered by automated tests.
• Lines of code (LOC): The number of lines in the codebase. Larger codebases often are harder to maintain.
• Coupling between objects (CBO): The degree to which classes are dependent on one another. Higher coupling generally reduces maintainability.
• Comment density: The ratio of comments to code.
• Code duplication: The amount of duplicated code in the codebase.
• Modularity: The degree to which the codebase is divided into independent, self-contained modules. Higher modularity generally improves maintainability.
• Change proneness: The likelihood of certain parts of the codebase requiring changes.

Apart from the above, there are other metrics like Halstead Metrics, Maintainability Index, Fan-in/Fan-out, Response For a Class (RFC), Weighted Methods per Class (WMC), God Class Detection, and more to measure maintainability.

Deciding the Least Useful Metric

The most useful metric for measuring code maintainability always depends on several factors, mainly your project requirements. So, let’s get an idea about different factors that affect our decision, consider an example with different metrics, and decide what the least effective metric among them is. Here are some common factors you need to consider:

• Project’s context and goals: Decide if the selected metric aligns with the project goals. For example, code churn might be more useful for projects focusing on reducing technical debt than metrics like cyclomatic complexity or code coverage.
• Relevance to maintainability: Evaluate how closely the metric relates to code maintainability. For example, some developers might consider the number of lines of code (LOC) less relevant to maintainability since it doesn’t directly reflect how easy the code is to maintain.
• Actionability: The metric should provide actionable insights to improve code maintainability. For example, metrics like defect density are less actionable than metrics like code duplication.
• Relevance to code quality: Metrics should have a good correlation with code quality. For example, cyclomatic complexity is directly relevant to code quality since it measures the complexity of the code’s control flow.
• Consider the metric’s complexity: The complexity of the metric should be justified by the insights it provides. For example, metrics like technical debt are more complex than others since they consider many aspects like bugs, design issues, and code smells.

Now, let’s use these factors and rank the ten metrics mentioned above according to their usefulness. For this evaluation, I have considered a large e-commerce application with the requirements and goals below.

• Should facilitate frequent updates due to changing business needs.
• The codebase is large.
• Multiple teams are working on different modules.
• Must maintain high availability, scalability, security, and performance.
• Identify and refactor complex or unstable code areas.
• Enhance code quality to reduce bugs and technical debt.
• Improve collaboration among teams.

Also, I have used a scoring system to rank them numerically.

• Relevance to maintainability: 1 (Low) to 5 (High)
• Actionability: 1 (Low) to 5 (High)
• Ease of interpretation: 1 (Low) to 5 (High)
• Relevance to code quality: 1 (Low) to 5 (High)
• Metric complexity: 1 (High) to 5 (Low) (Inverted because lower complexity is preferred)

Based on the project and the factors I considered, the least useful metric for code maintainability is comment density, followed by lines of code and change proneness.

However, it is essential to keep in mind that this ranking can be changed based on your project requirements, goals, and the factors you consider.