Dart Code Metrics: An Essential Tool for Flutter Developers
Dart Code Metrics (DCM) is a static code analysis tool for Flutter and Dart. It provides a comprehensive set of metrics to help you find and fix issues in your code. It’s free and open source and provides a set of extra rules that you can use to enforce best practices. It is a great compliment to the Dart Analyzer that comes with the Dart SDK. The post explains why you should use it in your team and how to get started.
Static Code Analysis
Programmers need static code analysis because it provides an essential safeguard to improve code quality, maintainability, and security throughout the software development lifecycle. Static code analysis tools automatically detect potential bugs, vulnerabilities, and coding standard violations without executing the code. This enables programmers to address issues proactively. It reduces the risk of critical failures and security breaches and helps ensure that code remains clean, consistent, and adherent to best practices. It also fosters a continuous improvement culture, resulting in more reliable, efficient, and secure software for end-users.
The emergence of large language models (LLMs) like ChatGPT, capable of generating code, has heightened the importance of static code analysis. As LLMs increasingly automate coding tasks, the potential for introducing subtle bugs and vulnerabilities grows. Static code analysis mitigates these risks by examining generated code and identifying issues. Integrating static code analysis into the development pipeline allows programmers to harness LLMs’ power while maintaining high code quality, security, and maintainability standards.
You should use the existing Dart Analyzer. This has a lot of great lints, and many are specific to Flutter. Check out my package austerity which attempts to enforce as many rules as possible. It’s a great way to get started with Dart static analysis.
Code Metrics
Code metrics are a specialized form of static code analysis that quantifies various aspects of source code, such as complexity, maintainability, and modularity. By measuring these attributes, developers can better understand their codebase and identify areas that may be problematic. Your team can make more informed decisions about refactoring or optimizing the code.
Programmers should use code metrics because they offer valuable insights into a codebase’s health and overall quality. High-quality code is easier to understand, maintain, and extend, leading to better long-term outcomes for the development team and end-users. Code metrics can reveal hidden problems, such as overly complex or tightly coupled code, which can be challenging to modify or scale.
Using code metrics with other static code analysis techniques provides a more comprehensive view of a codebase’s quality. By incorporating code metrics into your development process, you can ensure that it adheres to best practices, eliminate potential bugs and vulnerabilities, and optimize the codebase for long-term maintainability and success.
Dart Code Metrics
The DCM package is a powerful extension to the built-in Dart Analyzer, providing additional insights and tools specifically tailored for Dart and Flutter projects. You can benefit from advanced code analysis capabilities beyond the standard linting and error detection provided by the Dart Analyzer.
Key Features
- Customizable rule sets: DCM offers a comprehensive set of predefined rules that enforce best practices and coding standards. Developers can customize these rules to fit their team’s specific needs and requirements, ensuring consistent code quality across the project.
- Cyclomatic complexity analysis: This metric measures the number of independent paths through a program’s source code. It provides insights into the complexity and potential maintainability issues of the codebase. You can identify high-complexity functions or methods and prioritize refactoring efforts to minimize technical debt.
- Maintainability index: This is a mixture of other metrics but calculates the overall maintainability of your code. This is valuable so you can get a bird’s eye picture of your codebase or pinpoint the worst areas of a codebase.
- Integration: You can use this package in your CICD pipeline. In particular, DCM explicitly supports GitHub actions and Codemagic.
- Number of parameters: This is a great metric because having too many parameters can indicate that a given function is too complicated.
This enables more informed decision-making and facilitates the creation of high-quality, robust, and maintainable applications that stand the test of time.
Getting Started
The DCM package comes with great documentation. See the getting started guide.
Installation
flutter pub add --dev dart_code_metrics
Usage
flutter pub run dart_code_metrics:metrics analyze lib
Conclusion
You should use static code analysis. The analyzer that comes with Dart is great, and it’s very important to turn on the rules that come with it. Try austerity to get started, but once you’ve spent some time with the built-in analyzer, go further and use DCM to get an objective picture of your codebase. You may be able to use the metrics to track the progress of the codebase over time and use the metrics to persuade your team to spend more time on code quality. Check out the documentation and install it today.
