If you are interested in software testing, you have surely encountered the term "code coverage." It is one of the most popular metrics in the software development process, as it helps track the testing process and uncover errors. But what exactly does this metric mean? In our article, we provide a detailed answer to this question and explain how measuring code coverage supports the success of a project.
Understanding code coverage
To evaluate code coverage data, we need to understand what this metric precisely means. Monitoring code coverage helps assess which areas of the source code have been affected by tests and where there are still uncovered, potentially risky parts.
What does this mean in practice? Suppose the development team is working on releasing a new data-driven healthcare software. The application is the result of months of hard work and development, and during pre-launch testing, the developers proudly report achieving 85% code coverage. However, a severe error occurs a few weeks into use, compromising data integrity. It turns out the error originated from a piece of code that had not been tested.
This example perfectly illustrates that measuring and evaluating code coverage should not only focus on achieving high percentage values but also ensuring that critical functions and code sections are properly tested.
How to set code coverage goals?
When setting code coverage goals during the development process, we must first thoroughly understand the project's nature and objectives. Important questions to ask include: What is the primary purpose of the software? What functionalities and user experiences do we want to provide with the final product? We also need to consider the code's complexity: How complex or novel is the code structure, and what technological challenges do we face during development?
These questions help developers and software testers better understand the level of coverage needed to ensure adequate software quality. It is not enough to set an arbitrary percentage value. Code coverage goals should be determined based on understanding user paths and software components.
Test coverage vs. code coverage
Test coverage and code coverage are two frequently used concepts in software testing that help evaluate the quality of a given software but measure different things.
The test coverage metric refers to the proportion of available test cases covering all possible operational scenarios of the software. For instance, in an online store, test coverage measures how well different purchasing, payment, and shipping combinations—such as various payment methods or shipping address variations—have been tested. The more such scenarios are tested, the higher the test coverage.
Code coverage, on the other hand, shows the percentage of the program's source code affected by tests during their execution. A good analogy is a cookbook, where code coverage measures how many recipes you have actually tried out. If you only bake desserts, although you've tried many recipes, the rest of the book remains uncovered. A high code coverage rate indicates that a large portion of the source code has been reviewed, thereby potentially reducing the number of undiscovered errors.
Advantages and limitations of measuring code overage
Although 100% code coverage does not guarantee error-free software, it significantly reduces the risk of issues not detected by testers. Code coverage percentages provide information about code quality. These metrics allow development teams to identify untested code segments and highlight areas that require further examination. Moreover, code coverage analysis can identify code parts that do not contribute to the program's functionality and can be safely removed from the codebase. Achieving high code coverage rates can also facilitate faster development by highlighting which code areas need more attention.
However, it is important to note that while code coverage is a useful tool for assessing code quality, it is not a guarantee in itself. Despite high coverage values, code quality improvement is not assured if the tests are ineffective or poorly constructed. Code coverage indicates the extent of code execution, not the actual quality of the tests or the overall design and implementation of the testing system.