All odd numbers are prime: 1 is prime, 3 is prime, 5 is prime, 7 is prime, 9 is experimental error, 11 is prime, and so on, I don't have funding to check all of them, but it suggests an avenue of productive further work.
Look, just because it breaks everything, that's no reason not to include it in a joke. We'll just have to rebuild the entire edifice of mathematics.
Seriously, thanks for the link, I hadn't considered the implications of including 1 in the set of primes, and it really does seem to break a lot of ideas.
It's been a fat minute since I last did any programming outside of batch scripts and AHK... I'm struggling to understand how it's not returning false for 100% of the tests
It is always returning false, but the screen shows a test, where a non-prime evaluating as false is a pass and a prime evaluating as false is a fail :))
How many primes are there before 1 and 2^31. IIRC prime numbers get more and more rare as the number increases. I wouldn't be surprised if this would pass 99% of tests if tested with all positive 32 bit integers.
Per the prime number theorem, for large enough N the proportion of primes less than or equal to N is approximately 1/log(N). For N = 2^(31) that's ~0.0465. To get under 1% you'd need N ~ 2^(145).
Ah yes, my favorite recurring lemmy post! It even has the same incorrect test output.
Last time I saw this I did a few calculations based on comments people made: https://l.sw0.com/comment/32691 (when are we going to be able to link to comments across instances?)
There are 9592 prime numbers less than 100,000. Assuming the test suite only tests numbers 1-99999, the accuracy should actually be only 90.408%, not 95.121%
In response to the question of how long it would take to round up to 100%:
The density of primes can be approximated using the Prime Number Theorem: 1/ln(x).
Solving 99.9995 = 100 - 100 / ln(x) for x gives e^200000 or 7.88 × 10^86858. In other words, the universe will end before any current computer could check that many numbers.
But you can use randomised test-cases. Better yet, you can randomise values in test-cases once and throw away the ones you don't like and get arbitrarily close to 100% with a reasonable amount of tests