The impact report has been designed to provide clear data about Clayton's adoption within your organization and its outcome over time.
To access your Impact dashboard:
Home > from the left-side menu "Insights"
Click on "Impact"
From the impact tab you can pick a specific period of time and eventually restrict the scope of the report by selecting a specific set of projects. The widgets in the report show Clayton's adoption and usage outcomes within the reporting period.
Understanding the metrics
Active Projects: This metric measures the number of repositories or Salesforce Orgs you've scanned during the reporting period.
Developers: This metric tracks the number of unique contributors who have committed code in the reporting period.
Clayton counts active contributors by analyzing Git activity associated with each commit. It looks at the number of unique individuals contributing to the development of the application within any 90-day rolling window.
Code Review Criteria: This shows the number of code review criteria that you've delegated to Clayton.
Detection Accuracy: This measures the proportion of detections that have been accepted as valid issues rather than reported as false positives.
Scans: This metric measures the number of code reviews Clayton has performed. By reviewing code, you are able to not only assess quality of your project but also proactively catch potential issues before they go to production, which is a key part of our shift-left approach.
Issues Detected: This shows the total number of unique problems that Clayton has detected.
Bugs Prevented measures the number of issues Clayton found in a pull request (PR) that were fixed before the code was merged. This shows how many potential bugs were caught and resolved early in the development process. If Clayton finds 3 issues in a PR. Developers fix 2 of them before merging. 2 bugs would be counted as Prevented.
Efficiency Gain: This metric calculates the number of hours that Clayton has saved your developers.
Open Issues: This metric compares the number of open issues on your main branch at the end of the reporting period to the number at the beginning.
Mean Time to Merge: This metric displays the average time between the opening and merging of a pull request during this period, comparing it to the previous period's average.