Measuring coding contribution is hard. The most robust attribution models calculate the difference between the success of the project with and without the contribution, but in practice, we almost never know how successful the project would have been without the contribution. The closest we can get are isolated A/B tests, where we can measure the value of a specific code change in terms of business outcomes.
Measuring the volume of changes in any form is problematic, since it’s possible that the programmers who add the most code are actually making the code worse by accumulating technical debt faster than business value (instead of refactoring so that important changes can be made simply).
