Data Dictionary

Gitential Data Explained

measure & analyze

Main Performance KPIs

  • Coding Hours

    Estimated time spent by author on writing the inlier lines by a median speed derived from his overall commits (median of his speeds for all commits). Scale has been set to min 5 minutes and maximum 4 hours per commit with the assumption of frequent and regular code commits.

  • Code Volume

    Source lines of code, also known as lines of code, is a software metric used to measure the size of a computer program by counting the number of lines in the text of the program's source code. Calculation: total lines of code inserted – total lines of code deleted.

  • Contributors

    Number of individual developers (contributors) contributed to the work in the selected repositories within the given timeframe. It can be any kind of commit activity or comments.

  • Efficiency

    Efficiency is the percentage of a developer’s contributed code that’s productive, which generally involves balancing coding output against the code’s longevity. Efficiency is independent of the amount of code written. The higher the efficiency rate, the longer that code is providing business value.

  • Velocity

    Velocity gives us an estimation of on average how many lines of code is written in an hour. It is the ratio of total productive code volume to total estimated coding hours. Unexpected spikes in velocity can mean engineering difficulties in implementation which might require support from other team members or from management.

  • Commits

    The amount of commits done by a developer. This represents the number of changes made to the original code which can be extensions, rewrites, optimization, bug fixes, etc.

Gitential is a platform that delivers automated software development analytics to help teams measure, analyze, and improve development productivity based on actionable insights.

measure & analyze

Main Performance KPIs

  • Coding Hours

    Estimated time spent by author on writing the inlier lines by a median speed derived from his overall commits (median of his speeds for all commits). Scale has been set to min 5 minutes and maximum 4 hours per commit with the assumption of frequent and regular code commits.

  • Code Volume

    Source lines of code, also known as lines of code, is a software metric used to measure the size of a computer program by counting the number of lines in the text of the program's source code. Calculation: total lines of code inserted – total lines of code deleted.

  • Contributors

    Number of individual developers (contributors) contributed to the work in the selected repositories within the given timeframe. It can be any kind of commit activity or comments.

  • Efficiency

    Efficiency is the percentage of a developer’s contributed code that’s productive, which generally involves balancing coding output against the code’s longevity. Efficiency is independent of the amount of code written. The higher the efficiency rate, the longer that code is providing business value.

  • Velocity

    Velocity gives us an estimation of on average how many lines of code is written in an hour. It is the ratio of total productive code volume to total estimated coding hours. Unexpected spikes in velocity can mean engineering difficulties in implementation which might require support from other team members or from management.

  • Commits

    The amount of commits done by a developer. This represents the number of changes made to the original code which can be extensions, rewrites, optimization, bug fixes, etc.

Gitential is a platform that delivers automated software development analytics to help teams measure, analyze, and improve development productivity based on actionable insights.

measure & analyze

Top Deep Dive
Performance Metrics

  • Developer Utilization

    Ratio of elapsed time to utilized time based one estimated working hours. Elapsed time considers a 5-day working week and an 8-hour working day in its calculation. Holidays are not considered.

  • Productive Code

    Total lines of code that hasn't been rewritten in the last 3 weeks. As we are taking into consideration a 21-day window for this metrics the most accurate information will be available after 3 weeks. As today’s productive code can turn to unproductive within the next 21 days, it’s best to analyze it for older implementation.

  • Unproductive Code

    A quantified representation of the event when an engineer rewrites their own code shortly after it has been checked in - less than 3 weeks old. A certain amount of Churn code can be expected for any developer.

  • Code Complexity

    It is important because simple code is easier to maintain and easier for other engineers to work in. More experienced engineers tend to write simpler code. Lower code complexity is better.

  • Implementation Lines

    Total number of lines of codes which are not marked as test line.

  • Test Lines

    Total number of lines of code which are marked as a test line.

  • Average Pull Request Cycle Time

    The time it takes from the first commit that belongs to the pull request until merging to the master branch. It contains time spent on code writing, PR pickup time, and PR review time.

  • Pull Request Merge Ratio

    Ratio between created Pull Request vs. Pull Request deployed to production within the selected time period.

measure & analyze

Top Deep Dive
Performance Metrics

  • Developer Utilization

    Ratio of elapsed time to utilized time based one estimated working hours. Elapsed time considers a 5-day working week and an 8-hour working day in its calculation. Holidays are not considered.

  • Productive Code

    Total lines of code that hasn't been rewritten in the last 3 weeks. As we are taking into consideration a 21-day window for this metrics the most accurate information will be available after 3 weeks. As today’s productive code can turn to unproductive within the next 21 days, it’s best to analyze it for older implementation.

  • Unproductive Code

    A quantified representation of the event when an engineer rewrites their own code shortly after it has been checked in - less than 3 weeks old. A certain amount of Churn code can be expected for any developer.

  • Code Complexity

    It is important because simple code is easier to maintain and easier for other engineers to work in. More experienced engineers tend to write simpler code. Lower code complexity is better.

  • Implementation Lines

    Total number of lines of codes which are not marked as test line.

  • Test Lines

    Total number of lines of code which are marked as a test line.

  • Average Pull Request Cycle Time

    The time it takes from the first commit that belongs to the pull request until merging to the master branch. It contains time spent on code writing, PR pickup time, and PR review time.

  • Pull Request Merge Ratio

    Ratio between created Pull Request vs. Pull Request deployed to production within the selected time period.

  • Coding Hours

    Estimated time spent by author on writing the inlier lines by a median speed derived from his overall commits (median of his speeds for all commits). Scale has been set to min 5 minutes and maximum 4 hours per commit with the assumption of frequent and regular code commits.

  • Code Volume

    Source lines of code, also known as lines of code, is a software metric used to measure the size of a computer program by counting the number of lines in the text of the program's source code. Calculation: total lines of code inserted – total lines of code deleted.

  • Contributors

    Number of individual developers (contributors) contributed to the work in the selected repositories within the given timeframe. It can be any kind of commit activity or comments.

  • Efficiency

    Efficiency is the percentage of a developer’s contributed code that’s productive, which generally involves balancing coding output against the code’s longevity. Efficiency is independent of the amount of code written. The higher the efficiency rate, the longer that code is providing business value.

  • Velocity

    Velocity gives us an estimation of on average how many lines of code is written in an hour. It is the ratio of total productive code volume to total estimated coding hours. Unexpected spikes in velocity can mean engineering difficulties in implementation which might require support from other team members or from management.

  • Commits

    The amount of commits done by a developer. This represents the number of changes made to the original code which can be extensions, rewrites, optimization, bug fixes, etc.

  • Vendors

    Number of vendors grouped by developers. Developers are mapped to vendors.

  • Bugs Ratio

    Ratio between number of bugs vs all pull requests.

  • Developer Utilization

    Ratio of elapsed time to utilized time based one estimated working hours. Elapsed time considers a 5-day working week and an 8-hour working day in its calculation. Holidays are not considered.

  • Productive Code

    Total lines of code that hasn't been rewritten in the last 3 weeks. As we are taking into consideration a 21-day window for this metrics the most accurate information will be available after 3 weeks. As today’s productive code can turn to unproductive within the next 21 days, it’s best to analyze it for older implementation.

  • Unproductive Code

    A quantified representation of the event when an engineer rewrites their own code shortly after it has been checked in - less than 3 weeks old. A certain amount of Churn code can be expected for any developer.

  • Code Complexity

    It is important because simple code is easier to maintain and easier for other engineers to work in. More experienced engineers tend to write simpler code. Lower code complexity is better.

  • Implementation Lines

    Total number of lines of codes which are not marked as test line.

  • Test Lines

    Total number of lines of code which are marked as a test line.

  • Average Pull Request Cycle Time

    The time it takes from the first commit that belongs to the pull request until merging to the master branch. It contains time spent on code writing, PR pickup time, and PR review time.

  • Pull Request Merge Ratio

    Ratio between created Pull Request vs. Pull Request deployed to production within the selected time period.

  • Pull Request Time to Open (days)

    Average number of days it takes from the first commit to create a pull request.

  • Pull Requests without Reviews

    Total number of pull requests merged to the master without any received review.