Comment by ilikebits
5 hours ago
LOC is useful here not because it's a metric for output but because it's a metric for _understandability_. Reviewing 200 lines is a very different workload than reviewing 2000.
5 hours ago
LOC is useful here not because it's a metric for output but because it's a metric for _understandability_. Reviewing 200 lines is a very different workload than reviewing 2000.
That's assuming the 200 lines are logical and consistent. Many of my most frustrating LLM bugs are caused by things that look right and are even supported by lengthy comments explaining their (incorrect) reasoning.
Ok? No one is saying that all LOC are equal. Ceteris paribus, 2000 lines is 10x more time consuming to review than 200
The point is that LOC is never a good metric for any aspect of determining the quality of code or the coder because it ignores the nuance of reality. It's impossible to generalize because the code can be either deceptively dense or unnecessarily bloated. The only thing that actually matters is whether the business objective is achieved without any unintended side effects.
4 replies →
> 2000 lines is 10x more time consuming to review than 200
Very far from the truth in practice, every line of code isn't as difficult/easy to review as the other.
3 replies →
It’s still a bad metric.
I have worked with code where 1000s of lines are very straightforward and linear.
I’ve worked on code where 100 lines is crucial and very domain specific. It can be exceptionally clean and well-commented and it still takes days to unpack.
The skills and effort required to review and understand those situations are quite different.
One is like distance driving a boring highway in the Midwest: don’t get drowsy, avoid veering into the indistinguishable corn fields, and you’ll get there. The other is like navigating a narrow mountain road in a thunderstorm: you’re 100% engaged and you might still tumble or get hit by lightning.
There’s still a limit on how far one can drive in a day, no matter the road.
The number of bugs tends to be linear to lines of code written meaning fewer lines of code for the same functionality will have fewer bugs.
So I’m pretty skeptical that reviewing 2000 lines of code won’t take any more time than reviewing 200 lines of code.
Furthermore how do you know the AI generated lines are the open highway lines of code and not the mountain road ones? There might be hallucinations that pattern match as perfectly reasonable with a hard to spot flaw.
Its still posssible to run any LLM in a loop and optimize for LoC while preserving the wanted outcome.