
This is actually genius, I’m not gonna lie.

I looked for a few minutes, nearly gave up, and then I found it nearly instantly once I started looking for the correct distance between C - W. Kind of interesting!
This is one of those things a computer could do instantaneously, but a human can not.
Cowever, ask a computer to find a how IRL, and it just sits there on your desk and blinks at you.
I, too, cannot find a how IRL
Found it. I wonder what the designer did to make sure to have exactly one cow in there.
What I would have done is started filling in letters randomly and every time a C or W ends up next to an O, choose the same letter or an O to put on the opposite side of the O.
Its hard to prove, but I’m pretty sure there isn’t a situation where a space can’t be filled in with this algorithm.
Yes, this would work — but it comes with a subtle statistical bias: the character ‘W’ ends up underrepresented. With a naïve “avoid COW” approach, only about 25% of the grid will typically be ‘W’.
A more elegant solution would be:
- fill the grid completely at random
- search for every “COW” cluster
- whenever one is found, copy a random character from one cell in the cluster into another cell of the same cluster
- Iterate until no “COW” remains
- search for every “COW” cluster
That keeps the distribution much closer to uniform while still guaranteeing a valid puzzle. Then just insert the single “COW” manually wherever you want the hidden solution to be.
Julia code example
s= (320,180) #size m=rand(['C','O','W'],s) #random init c=1 while c>0 #iterate till solved c=0 for i in 1:first(s) for j in 1:last(s) #check for 'COW' in each cluster of 3 and copy a character #from a rendom cell to an other random cell of the cluster if found if i>2 && m[i-2:i,j] ==['C','O','W'] #vertical c +=1 r =shuffle([1,2]) m[i-r[1],j] = m[i-r[2],j] end if j>2 && m[i,j-2:j] ==['C','O','W'] #horizontal c +=1 r =shuffle([0,1,2]) m[i,j-r[1]] = m[i,j-r[2]] end end end endThe neat part is that this preserves an almost perfectly balanced character frequency.
For comparison, the puzzle in the example image seems to contain roughly:
C: ~260 (~25%) O: ~520 (~50%) W: ~244 (~25%)
So the original author clearly used a different generation strategy.
Possibly on purpose: visually, ‘C’ and ‘O’ are much easier to confuse than ‘W’. Reducing the number of 'W’s therefore increases the search difficulty. In that sense, the approach suggested by @Snazz@lemmy.world is probably preferable: keep the distribution mostly balanced, but intentionally bias it just enough to make the puzzle psychologically annoying.
I wonder if there is a non iterative way to generate this puzzle with a ‘uniform’ character distribution 🤔
- fill the grid completely at random
Top of the page says find 1 cow, so yes
i almost lost focus before finding it because of all the owo’s

Put it in spoiler tags, please!
Found it

Easy
I did wonder if that might prove to be the answer, glad it wasn’t! 😁
Now you’re thinking like a Taskmaster.
The best way to think
Nailed it!
Spoiler!


Put it in spoiler tags, please!
Sorry….
Tap for spoiler
Line 15, end of the line
You know about spoiler tags?
Gawd, it would have been so fucking funny if there actually wasn’t a single instance of cow in it, though. Lol
I would have tried longer if I knew it was actually there! I do remember focusing near there and missing it, though.
owo
wow
woo
COO. Cow in Scots.
Good description. I read this and perfectly estimated the location you described within 5 seconds.
Many, many cocs.
Had to find it

Use spoiler tags, please!
It’s missing the 1, try again
I found coooooooc :)
Wow!















