Bug Density #
Indicates the number of bugs per a certain amount of lines of code, providing insight into the overall quality of the code.
Indicates the number of bugs per a certain amount of lines of code, providing insight into the overall quality of the code.
Calculates the frequency of build failures in the Continuous Integration (CI) process.
Measures the complexity of the code, which can impact maintainability and readability.
Represents the percentage of code that is covered by automated tests, which is crucial for ensuring that as much code as possible is tested to identify defects.
Quantifies the amount of duplicated code in a codebase.
Indicators of deeper problems in code, 'code smells' are patterns that may not be outright bugs but suggest design issues that can increase the risk of bugs or failures in the future.
The percentage of the CPU's capacity that the application uses during execution, impacting the application's performance and server load.
Measures the percentage of defects that escape into production, signifying the effectiveness of pre-release testing.
Measures the extent to which the codebase is documented.
Flaky tests are those that produce inconsistent results each time they are run.
Amount of memory used by the application during execution.
Counts the number of revisions a pull request goes through before merging, which can indicate the clarity of requirements and effectiveness of initial submissions.
Refers to the size of pull requests in terms of lines of code, where smaller pull requests are generally easier to review and less likely to introduce errors.
The average time taken for the system to respond to a request in a production environment.
Measures the percentage of tests that pass during the development process.
Tracks the amount of time spent addressing technical debt, which includes refactoring code, improving design, or updating documentation, crucial for long-term project health.
The average duration from when a pull request is opened until it is merged.