How to Improve Code Coverage 

Any organization developing enterprise software must have a robust testing system to secure its codebase. Bad code, when deployed, can lead to significant financial losses—thousands, if not millions, of dollars. It can drive away customers and create vulnerabilities that cybercriminals can exploit, putting sensitive information at risk.

Code coverage forms an integral part of any complete testing strategy. Think of it as a vigilant inspector in your codebase who scrutinizes every nook and cranny of your code to unveil potential vulnerabilities and weaknesses. It highlights the potentially problematic areas of your code, enabling you to eliminate any risks proactively.

If your team wants to achieve optimal code coverage, then understanding some best practices and how to implement them with a code coverage solution like Codacy is pivotal.

What is Code Coverage?

Code coverage measures how much of a program’s source code has been tested. It encompasses several metrics that assess how thoroughly a test suite runs your source code, indicating which lines, branches, conditions, or functions have been executed during testing.

Incorporating code coverage into your testing strategy offers a wide range of benefits. For one, it will help you identify untested code that is more likely to contain bugs or potential issues. It also streamlines code maintenance and refactoring activities while removing the need for unnecessary tests.

Note that code coverage simply measures the percentage of code covered by tests. Achieving 100% coverage doesn’t guarantee a bug-free application, though it can mean fewer bugs in production. While code coverage is a valuable metric, it’s just one of many tools developers use to ensure code quality.

Moreover, code coverage isn't restricted to tests alone; it also encompasses other types of code execution, including manual testing and other techniques like static code analysis.

How is Code Coverage Calculated?

Code coverage is typically obtained by using a code coverage tool. These tools run alongside your tests and monitor which parts of the code are executed. Once the tests are done, the tool produces a code coverage analysis report.

The report might include metrics like the percentage of code executed, which lines of code were or were not executed, and the coverage of different branches in conditional statements. The calculation can vary based on the type of coverage:

• Statement Coverage: This type of coverage targets the execution of individual lines within functions, ensuring all code is traversed during testing to identify dead code, unreachable parts, and any missing or unused statements and branches.
  
  
• Branch Coverage: Programs often consist of decision trees known as branches (e.g., if, if-else, do-while loops, etc.). Branch coverage measures the percentage of decision branches taken during testing, ensuring that all possible outcomes are considered and tested.
  
  
• Function Coverage: Functions are "self-contained" modules of code that accomplish a specific task. This code coverage metric measures the percentage of functions or subroutines called at least once during testing.
  
  
• Condition Coverage: This verifies that each condition is tested for both true and false outcomes, helping to identify potential issues in conditional logic and ensuring decision-making accuracy.

Improving Code Coverage With Codacy

Code coverage is a key testing strategy for creating robust and maintainable software. Codacy’s code coverage solution, Codacy Coverage, is designed to help organizations maintain high coverage while ensuring that every piece of contributed code meets their high standards.

Let’s explore how Codacy can help you improve code coverage.

1. Centralize Your Code Coverage Insights

Many code coverage tools are available to help you gather data on tests you’re running, no matter the programming language you use. Some popular code coverage tools are JaCoCo and Cobertura (Java), Istanbul and jscoverage (JavaScript), SimpleCov and undercover (Ruby), pytest-cov and Coverage.py (Python), as well as Coverlet and NCover (C#).

It’s worth mentioning that Codacy supports the report formats generated by most of the tools listed above (see our coverage reporter documentation for the full list of supported formats and more information). 

After selecting the coverage tools that best suit your team, the next step is to find an easy way to monitor your code coverage reports. This can be particularly challenging for large software companies with numerous repositories to oversee.

Codacy Coverage’s repository dashboard offers a simple and effective way to monitor all your coverage. You just need to generate coverage reports for commits on your CI/CD workflow, upload the coverage data to Codacy, and you’re good to go!

The dashboard provides valuable data at a glance, including a code coverage percentage, coverage evolution reports, and a list of open pull requests for every repository.

2. Set Coverage Target And Benchmark Effectively

While there’s no perfect code coverage number to aim for, the commonly accepted benchmark is 80%. This target strikes a healthy balance; pursuing a higher percentage can be costly and may not yield significant benefits. 

A high coverage percentage doesn’t guarantee quality, especially if critical areas of your application are untested or if existing tests fail to catch important issues. Focusing too much on achieving high coverage can lead your team to write superficial tests that cover lines of code rather than meaningful tests aligned with your application’s business requirements.

Codacy simplifies continuous monitoring of coverage levels and performance benchmarks. Its repository dashboard offers an overview of test coverage trends over the past 90 days, providing a clear view of your progress.

The 90-day overview of test coverage trends provides valuable insights into how coverage evolves over time, helping teams assess the effectiveness of their testing efforts.

3. Leverage Codacy’s Code Analysis Feature To Write Testable Code 

Crafting code that's easy to test is critical to achieving high test coverage. Testable code makes it simpler to develop meaningful and thorough test cases. Here are some best practices for writing testable code:

• Break your code into modular components that can be tested individually. 
  
  
• Opt for small, self-contained functions (i.e., blocks of code that perform a specific task or operation) and methods as they are easy to understand, test, and maintain.
  
  
• Implement SOLID principles like Single Responsibility and Dependency Inversions that give codes that are easy to test.
  
  
• Use dependency injection during testing to substitute real dependencies with mocks and stub objects.

Codacy thrives at detecting quality issues in code. It analyzes all repositories in your organization and lists any detected issues on your account’s Quality Issues page. There, you can see the nature of the issues, how to resolve them, and other relevant information.

Another proactive way to keep your code clean and secure is to install Codacy’s IDE extension in your Visual Studio Code or IntelliJ IDEA environment. This will help you catch and fix many quality-related issues while you code.

Codacy’s IDE extension analyzes all branches and open pull requests, categorizing issues by date, author, category, and severity. This makes it easy to sort through and prioritize the critical issues.

4. Make Code Coverage Part of Your Continuous Integration Flow 

Incorporating code coverage into your continuous integration (CI) process will ensure that tests run automatically with each code change, enabling you to monitor coverage metrics continuously.

Codacy Coverage seamlessly integrates into your development workflow, eliminating the need to learn new tools. It works with major Git providers like GitHub, GitLab, and Bitbucket, and you can even display the coverage summary as a comment on GitHub Pull Requests. The summary includes the following:

• Coverage metrics (coverage variation and diff coverage)
  
  
• Targets and status for the quality gates
  
  
• Information used to calculate the metrics (number of covered and coverable lines)
  
  
• If a report is missing, an error explaining why Codacy couldn’t calculate Coverage
  
  
• Links to enable/disable the feature and to change quality gates
  
  
• Link to see your PR on Codacy UI

This feature makes your code review process even more seamless. You don’t need to leave GitHub to check your coverage results; you’ll have all the information you need right there in your workflow. You can access metrics directly from your Git platform, bypassing the need to switch between tools and platforms.

5. Use Coverage Reports to Identify Critical Misses in Testing

The more tests you have in your code, the harder it’ll become to identify what part of the application is checked during the execution of your test suite. A red build can give you insights into what may have broken, but identifying what components have passed the test will be difficult.

You can turn to the coverage reports for deeper insights in such cases. Codacy Coverage lets you explore these reports to identify specific items that weren't tested, helping you pinpoint critical areas of your application that still require testing.

6. Refactor Legacy Codebases

Legacy codebases often suffer from low test coverage and lack comprehensive security testing, such as penetration testing, vulnerability scanning, or static code analysis. This is because many legacy systems were developed at a time when testing practices were less mature or prioritized.

Organizations can reduce the risks of low test coverage in legacy codebases by gradually increasing it. The Diff Coverage metric and targets help improve coverage without overwhelming teams, as both tools ensure that each change leads to steady, manageable progress over time.

In addition to code coverage, it’s essential to implement various other security practices, including SCA, pen testing, Infrastructure as Code (IaC) security, secrets detection, and Cloud Security Posture Management (CSPM) coming soon—all of which Codacy can help you with.

In conclusion, while reaching 100% coverage in every category doesn't ensure a bug-free application, it dramatically lowers the chances of undiscovered issues. Enhanced code coverage allows developers to make changes with confidence, catch bugs early, and maintain the system's long-term reliability and maintainability.

Start your free trial today to explore how Codacy’s coverage dashboard functions and discover just how easy it is to analyze and report on code coverage.