Worth noting that "cognitive complexity" may mean SonarQube metric – a metric that is not widely recognized by industry, created by SonarQube employee as (imho failed) attempt to address "issues" with "cyclomatic complexity" (principled, intdustry recognised metric). It'll count things like nullish coalescing and optional chaning as +1 on your complexity which makes it unusable with jsx or ts code.
With low thresholds ("clean code" like low) both LoC and "cognitive complexity" (as in SQ) are bad measures that lit up in red large percentage of otherwise correct code in complex projects. The way people usually "solve" them is through naive copy pasting which doesn't reduce any cognitive load - it just scatters complexity around making it harder to reason about and modify in the future.
It may be a bad metric, if you're being proscriptive, but it's a great heuristic. If I see a 500-line function where I'm not expecting one, I'm going to pay a lot more attention to it in the PR to try to figure out just why it isn't shorter.
LOC is often a rough approximation for complexity. We once had an intern who made some useful things, but he didn’t know how to break anything down. One of them was a 1,000 line perl all as one function. I asked if it could be broken down into something more maintainable and he said no. There were several projects like this.
Knowing At a high level what needed to happen to accomplish what the code did, I know for a fact it could have and should have been broken down more. However, because of the complexity of what he wrote, no one had the patience to go through it. When he left, the code got thrown away.
While 10 LOC vs 50 LOC doesn’t matter, when commas enter the number, it’s a safe bet that things have gone off the rails.
> While 10 LOC vs 50 LOC doesn’t matter, when commas enter the number, it’s a safe bet that things have gone off the rails.
There are times when even a 1,000 LOC function is the better solution. The best example I can think of involve a switch statement with a very high branch factor (e.g., 100), where the individual cases are too simple to break out into separate functions. Something like the core loop of an interpreter will easily become a several-thousand line function.
I would argue an interpreter that needs 1,000 lines for its core loop is probably a complex piece of software, comparable to other 1000-line projects I've made.
Cyclomatic complexity is not equal to LOC and cyclomatic complexity of a switch can be seen as adding just 1 to its enclosing function. Either way, LOC is still not a great metric while cyclomatic complexity approaches a better one.
In my experience, there are very few places where something can't be broken up to reduce cognitive overhead or maintainability. When a problem is solved in a way as to make it difficult to do then maybe it's better to approach the problem differently.
Seems like the article missed an opportunity to talk about testing and MC/DC coverage. I don’t care if the PR is long or short, just show me that you have meaningfully tested how each branch can be reached with the full range of values and behaves correctly. Unit testing is easier with well chosen interfaces and worse without them, regardless of LOC.
> I asked if it could be broken down into something more maintainable and he said no.
This is something AI is good at. It could have shown the intern that it is indeed possible to break such function without wasting an hour of a seniors time.
They were one-off projects where he was the sole dev, not part of a larger project. While not mission critical, the 1k line Perl script was helpful at the time. When we ran into a specific issue it allowed for recovery in minutes vs hours. We eventually added safeguards which prevented the issue from happening in the first place.
> LOC is often a rough approximation for complexity.
I would argue that the word you are looking for is "containment".
Is there any real difference between calling a function and creating a "const varname = { -> insert lots of computation <-; break retval;}" inline?
If you never do that computation a second time anywhere else, I would argue that a new function is worse because you can't just scan in it quickly top to bottom. It also ossifies the interface if you have the function as you have to rearrange the function signature to pass in/out new things. Premature optimization ... mumble ... mumble.
Given that we've shrugged off "object-itis" which really demands small functions and given modern IDEs and languages, that kind of inline-style seems a lot more useful than it used to be.
> If you never do that computation a second time anywhere else, I would argue that a new function is worse because you can't just scan in it quickly top to bottom.
I feel exactly the opposite. By moving "self contained" code out of a method, and replacing it with a call, you make it easier to see what the calling location is doing. Ie, you can have a method that says very clearly and concisely what it does... vs making the reader scan through dozens or hundreds of lines of code to understand it all.
Chapter 12 of Kent Beck's book Tidy First? is about exactly this.
Sometimes I write long functions because I do not have time to write a shorter function. Eventually, if I have time, I go back and refactor a much shorter and tidier version. While later versions may be somewhat more efficient computationally, it is mostly a no-op beyond the aesthetics.
What is the LoC for that function? The first implementation or the final rewrite? They express the same thing.
The whole point of a rule-of-thumb is to be dumb. There are very few good reasons for a 500 loc func, and the code reviewer won't want to verify it's as simple as you claim. You could still have a 50 loc func that's overly complex, and they'll complain about complexity instead of length.
One consideration is that about 40 loc will comfortably fit in one code split, and it's nice if one func will fit in 1-2 splits. Past that length, no matter how simple it is, the reader will have to start jumping around for declarations. That might be ok at first, but at some point the ratio of offscreen to onscreen code gets too big.
I wonder if there is a way to see how physical monitor quality and size improvements have led to more complicated code, nevermind moving off of punch cards.
The type of monitor doesn't matter a whole lot because it's really limited by human eyesight. High-res monitor will enable rendering things tiny if you disable hi-dpi, but then it's unreadable. If you use a big 8K TV to display everything larger, you have to sit further away to comfortably view it. If you add more monitors, at some point it becomes too hard to look at so many things at once.
Personally, my setup has shown the same number of vim rows/cols on my 4K monitor vs my 1080p one (or whatever you call the 16:10 equivalents).
The effective resolution of the eye should be an angular value. I'd say that the smallest comfortable size of text characters for me is about 1/8° wide. I see the width of my 14" FHD laptop screen at about 30°, so the full width contains about 240 characters. This is a large upgrade from 80 columns of VT220 or VGA, and almost twice as much as the densest VT220 mode of 132 columns.
My 28" 4K monitor is exactly like four 14" FHD screens put together. It offers me 480 columns (a bit fewer, because window borders and scroll bars of multiple windows).
So indeed, better screens allow me to see much more text than poorer screens of old. There is a limit, but definitely it was not reached 30-40 years ago yet.
What an arrogant, wordy, and partly wrong take on this matter.
No, LoC is not a dumb metric. In the same way that cognitive complexity, code coverage, and similar metrics aren't. CC is definitely not "superior" to LoC, it's just different.
These are all signals that point to a piece of code that might need further attention. It is then up to the developer to decide whether to do something about it, or not.
You know what's dumb? Being dogmatic, one way or the other. There are very few hard rules in software development—they're mostly tradeoffs. So whenever I hear someone claiming that X is always bad or always good, I try to poke holes in their argument, or just steer clear from their opinion.
With low thresholds ("clean code" like low) both LoC and "cognitive complexity" (as in SQ) are bad measures that lit up in red large percentage of otherwise correct code in complex projects. The way people usually "solve" them is through naive copy pasting which doesn't reduce any cognitive load - it just scatters complexity around making it harder to reason about and modify in the future.
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