When discussing code coverage, it’s important to understand that not all 
coverage metrics are created equal. Line coverage measures the 
percentage of executable lines run during tests. While it’s the simplest 
metric to track, achieving 100% line coverage doesn’t guarantee that all 
logical paths are tested.

Branch coverage takes this further by verifying that each decision 
point, such as if or switch statements, evaluates both true and false 
outcomes. This ensures that edge cases and conditional logic are tested, 
reducing the risk of overlooked errors.

Path coverage is the most comprehensive metric, measuring all possible 
execution paths through a function or module. Though ideal in theory, 
path coverage can quickly become infeasible for large codebases due to 
combinatorial explosion. In practice, combining line and branch coverage 
provides a strong balance between thoroughness and practicality.

Modern tools now integrate code coverage with automated testing 
frameworks to provide real insights into test quality. Some platforms 
even capture real user interactions to generate test cases 
automatically, helping cover scenarios that traditional tests might 
miss. Keploy, for example, leverages this approach to ensure that API 
and integration tests reflect real-world usage, making code coverage 
more meaningful and actionable.

By understanding these coverage types and focusing on tests that 
exercise critical logic and edge cases, teams can improve software 
reliability while maintaining efficient development workflows.