I have been using Git for approximately 13-14 years. I have used GitHub Code Scanning for about three to four years. The primary purpose is to identify any vulnerability in the code itself. The system logs vulnerabilities that we can immediately examine to see all the error-prone areas. The AI functionalities include predefined agents that scan through and immediately provide responses regarding the best nomenclature or code coverage percentage. It's actually a one-time setup, and the team benefits as long as they push code and changes in the repository itself. Every time we push something, we immediately check the total deviation, whether our code coverage has improved, or if any vulnerability has been identified. There is always a metrics dashboard that we can see and identify. Primarily, GitHub is used for doing the versioning itself in the repository. With vulnerability functionality being provided and AI agents available, it makes a complete package. As soon as we publish our code, we immediately get to know the test code coverage. This immediately informs us about all the vulnerable areas which are not being fully tested. If we address those areas, most vulnerabilities are resolved. Even after tests are added, if by any chance the test is not treated cleanly or corner cases are missed, GitHub Code Scanning immediately flags those corners. It's always beneficial to have because it's not humanly possible to check all corner case scenarios, but as a system where they diagnose each line item, that's very helpful.
