What are the best practices for using a code coverage tool?

2 Limitations of code coverage

Code coverage is not a perfect indicator of software quality or testing completeness. It does not tell you how well your tests are designed, how effective they are at finding defects, or how realistic they are at simulating user scenarios. It also does not account for the logic, functionality, or performance of your code. Therefore, you should not rely on code coverage alone to judge the quality of your software or test suite. You should also use other metrics and methods, such as code reviews, static analysis, functional testing, performance testing, and user feedback.

3 Choosing the right tool and level of coverage

There are many code coverage tools available for different programming languages, frameworks, and platforms. You should choose the tool that best suits your needs, preferences, and budget. Consider the features, usability, compatibility, and support of the tool. Common features of code coverage tools include the ability to measure different types of coverage (e.g., statement, branch, condition, function, or line coverage), generate reports in various formats (e.g., HTML, XML, JSON, or CSV), visualize the coverage results in different ways (e.g., graphs, tables, charts, or heat maps), filter/sort/group/compare the coverage results by different criteria (e.g., file, class, method, test case, or branch), and integrate with other tools (e.g., code editors, test runners, code analyzers, or code repositories). The level of coverage that you aim for depends on various factors such as the type/size/complexity/criticality of your software and the time/resources available for testing. Generally speaking, higher levels of coverage are more desirable for software that is more complex or critical; conversely lower levels of coverage may be acceptable for software that is less complex or critical. The level of coverage should also be consistent and realistic across your software and test suite as well as aligned with your testing goals and quality standards.

4 Interpreting and reporting the results

Interpreting and reporting the results of code coverage analysis should be done in a meaningful and actionable way. It shouldn't be treated as an absolute measure, but rather as a relative and indicative measure. Additionally, it should be used as a tool or guide, not a goal or target. When interpreting and reporting the results, it's important to consider the type and quality of tests, complexity of code, and purpose of coverage analysis. Identify gaps and risks in the test suite and code, such as areas of low or zero coverage or high complexity. Communicate the results clearly by using visuals, appropriate formats, and language that will resonate with your audience. Monitor and track the results over time to measure progress and trends. Celebrate improvements while addressing any issues or challenges.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?