Practical tips for applying internal quality criteria

Use Automated Tools for Quantitative Metrics

Tools like SonarQube, CodeClimate, or similar static analysis tools can measure cyclomatic complexity, test coverage, and code duplication automatically. Set up these tools in your CI/CD pipeline to track these metrics continuously, so you’re alerted to areas with high complexity or low coverage as you work.
Regularly Review and Refactor Code for Readability

High readability improves collaboration and maintenance. Aim to make each function or class as clear as possible by using meaningful names, reducing overly complex logic, and adhering to a consistent style. Refactor code that becomes confusing or difficult to follow, as this directly enhances readability.
Break Down High-Complexity Functions

Cyclomatic complexity measures the number of decision paths in your code, and high scores indicate difficult-to-maintain functions. If you encounter a function with high complexity, break it into smaller, focused functions. This practice not only makes testing easier but also aligns with the Single Responsibility Principle.
Prioritise Testing for Critical Paths

Test coverage is an important internal metric, but 100% coverage isn’t always realistic or necessary. Focus on testing critical areas thoroughly, such as core logic, calculations, and functions with high cyclomatic complexity, to maximise reliability in key areas of the codebase.
Adopt and Enforce Coding Standards

Adhering to consistent coding standards helps create uniformity, making it easier for others to understand your code. Use linters and formatters to enforce standards and conduct code reviews with coding standards in mind. This approach improves code quality across the team and ensures best practices are consistently followed.
Modularise for Maintainability

Modular, decoupled code is easier to maintain and extend. Aim to create small, cohesive modules and avoid dependencies between unrelated components. For example, use interfaces to abstract dependencies, which enhances testability and supports changes with minimal impact on other parts of the system.
Use Code Reviews to Assess Qualitative Aspects

Set up regular code reviews to evaluate qualitative criteria such as readability, adherence to standards, and modularity. Reviews provide opportunities for feedback, help maintain high standards, and allow developers to catch issues that automated tools may miss.
Document Complex Code and Design Decisions

For sections of code with inherently high complexity or critical design decisions, use inline comments or a separate documentation file to provide context. This helps team members understand the reasoning behind specific approaches, improving maintainability.
Balance Quantitative Metrics with Judgment

High scores in quantitative metrics like test coverage or low cyclomatic complexity don’t guarantee high-quality code on their own. Use these metrics as indicators but rely on qualitative assessments to capture code quality more holistically.