Metrics for functional testing

Defect density: The number of defects identified per unit of code, typically per thousand lines of code (KLOC). A high defect density can indicate areas of the code that might require additional scrutiny or rework. By focusing on these areas, teams can enhance code quality. Improve this metric by increasing the rigor of code reviews, using static code analysis tools, and ensure developers have access to training and best practices. To measure this metric, compare the number of defects to the size of the codebase in KLOC.

Test pass rate: The percentage of test cases that pass successfully. This metric provides an overview of the software's health and readiness for release. A declining pass rate can indicate emerging issues or code instability. Monitoring the test pass rate helps to evaluate the effectiveness of quality assurance testing process. Measure this by comparing the number of successful tests to the total tests run.

Escaped defect rate: The number of defects found by users post-release compared to those identified during testing. A higher rate can suggest gaps in the testing process and areas where user flows are not effectively tested. Track this metric by comparing the number of post-release defects to the total defects identified.

Test case run time: The duration taken to run a test case or a suite of test cases. Increasing the duration can highlight bottlenecks in the test process or performance issues emerging in the software under test. Improve this metric by optimizing test scripts and the order they run in, enhancing testing infrastructure, and running tests in parallel. Measure the timestamp difference between the start and end of test case execution.

Test coverage: The percentage of the codebase tested. This is generally further segmented as the percentage of functions, statements, branches, or conditions. Test coverage gives an overview of potential untested or under-tested areas of the application. Improve this metric by prioritizing areas with lower coverage, using automation and tools to enhance coverage, and regularly review test strategies. Measure this metric by calculating the ratio of code covered by tests to the total lines of code in the application.

Feature-to-bug ratio: The proportion of new features developed compared to the number of bugs fixed. This metric provides insight into the balance between innovation and quality assurance. A higher ratio might indicate a focus on feature development, while a lower ratio can suggest a phase of stabilization or significant technical debt. To strike a balance, align your software development strategy with business goals and feedback loops. Regularly assess the ratio to determine if there's a need to prioritize defect resolution over new feature development, or vice versa. Measure by dividing the total number of new features by the total number of bugs fixed in a given period.