[paulcole]

If anything that guy’s a great example of why to use LOC as a metric because when he shows you a huge number of LOC, you say, “That’s a lot more than I expected, let’s take a look…” and you see that his performance sucks.

I think of metrics like this as a way to guide deeper looks and decision making. You just have to accept that “all models are wrong, but some models are useful.” LOC can be useful when it guides you to the right questions. It’s a starting point not the end of the conversation.

[ben_w]

I don't think you're using the word "metric" the same way as those of us who are criticising the use of LOC as one.

[paulcole]

Can you share the definition you think you’re using and the one you think I’m using?

[ben_w]

I think you're using metric to mean "any measurement" even when that measurement feeds into an opaque function f(LOC).

I think what's being criticised is when its used as a direct scoring system (e.g. bonus = k * LOC).