Of course randomA is terrible, you're modding it with 16! It's never going to have a period longer than 16 like that! Same with randomB, just with a slightly larger number. Both of these are just bog-standard linear congruential generators. LCGs are pretty bad for anything "serious", but for picking Tetris pieces they're fine, and they're easy to implent (or at least I thought they were, but then you see an article like this where one of them has period 16...). I don't immediately recognie randomC(), but it also looks terrible. Just shifting some bits around and adding a counter. At least it has some internal state so it it's not stupidly periodic.
I haven't read up on what's the issue with V8's Math.random(), but I would have to imagine it's superior to all these three. I'm also sure there's plenty of excellent randomness libraries (and plenty of terrible ones) on NPM.
Also, this kind of visual inspection will weed out truly garbage PRNGs, but it's not a good test in general. Testing for pseudo-randomness is hard, and best left to people who know what they are doing.
Also also: for Tetris, you shouldn't just pick pieces at random, that's not how Tetris works nowadays. Tetris works by putting all 7 pieces in a bag, and then pulling them out at random. When the bag is empty, you fill it again with the seven pieces and start over. More info here: . If you're new to programming, implementing the 7-bag system properly is a good little challenge, you'll get to learn all about the Fisher-Yates shuffle .
For what it's worth, LFSRs can be nice for generating random sequences with periods of predictable length - and they're cheap! They also recently got a bit of a publicity bump with the rediscovery of how Doom used one for the "death fade" transition, that randomly but exhaustively overpainted all screen pixels with blood red. 
But in general - yeah, there's a lot to consider with picking RNGs, not the least of which being context. For games Xorshift is often a good enough choice because it's fast, small, and the game environment is chaotic already (because of the unpredictable players) so there is rarely need for something much stronger.
By the way, Doom's random number generator for the game mechanics... not so fantastic  :)
It's a purely abstract game with endless possibilities for how it can be made. That's what makes it timeless. There's no reason you have to use bag randomizer in your own personal projects. That is, unless you feel some strange need to check off boxes to comply with what the current IP holders happen to prescribe at a particular moment in time.
In fact, there's an argument for using a memoryless randomizer: it maximizes variation, unpredictability, and increases challenge.
So no, it's not an "abstract game with endless possibilities". Tetris is Tetris, a concrete game made by a great game designer. It gets cloned and copied constantly, so much so that people forget that it was actually authored by a person. Comments like yours erase Pajitnov's authorship and ownership, which he has rightly earned.
Nobody talks of any other kind of media this way, we shouldn't do it about games either. When speaking of Harry Potter, no one thinks of JK Rowling as just "the current IP holder" (she's the author!), and no one considers fan fiction on the same level as the real thing.
The article states "when the game plays, the tetrominos are selected at random". When it comes to standard Tetris, as defined by the Tetris Company, this is incorrect. I was correcting the error. Obviously you can do it however you want, but that is how Tetris does it.
As for what's more fun, obviously opinions can differ. But as someone who plays a lot (A LOT) of Tetris, I personally vastly prefer the 7-bag system. It really opens up the game strategically, and it allows you to play much faster.
> So no, it's not an "abstract game with endless possibilities". Tetris is Tetris, a concrete game
While protecting their IP in a court of law, The Tetris Company successfully argued that it does not exhibit scènes à faire because it is a purely abstract game.
> Moreover, Xio does not dispute that Tetris is a purely fanciful game, meaning it has no
grounding in the real world, unlike a video game simulating a karate match or a golf
game. Therefore, the analyses in Data East and Incredible Technologies are largely
inapplicable; the scènes à faire doctrine has little weight in instances such as this
because there are no expressive elements “standard, stock, or common” to a unique puzzle game that is divorced from any real world representation.
> Modern versions of Tetris released after 2001 use a bag-style randomizer that guarantees players will never receive more than four S or Z pieces in a row. This is one of the "Indispensable Rules" enforced by the Tetris Guideline that all officially licensed Tetris games must follow.
Just wanted to offer some missing bits you might find interesting, specifically, the third function you don't recognise is the random function from the original Tetris on the NES. It comes from the article that went through all the asm of the NES Tetris cartridge.
And yup, that first one is quite quite terrible for random - it came from some of the first results in StackOverflow intentionally looking for something that was overly simple and "bad" at random.
But really the article was about testing and visualising how your own random functions might be.
A better introduction is the PCG website (it's biased towards PCG, but a) that's not a bad choice for many use cases, and b) it raises and discusses many issues regarding PRNG choice).
EDIT to add: and FWIW, any serious PRNG of course allows seeding, and then the issue boils down to choosing a shared seed.
The default “good” random number generator is the “Mersenne Twister” (most of the time, the 32-bit MT19937 version). It generates numbers which look quite random while not being cryptographically strong (the problem with crypto-strong generators is that they tend to be slower, and can still cause legal issues in some jurisdictions). A lot of languages use this for the default random number generator.
Some people really like using xorshift generators; with the right parameters, xorshift can generate high quality numbers while being much simpler than MT19937. One version of this which some use is JKISS32; it’s small and makes good numbers.
Random number generators can be tested using a series of tests called “dieharder”; another test for RNGs is “bigcrush” which takes hours, sometimes days, to fully run. These tests make sure the random number generators are statistically random, using a large number of tests of the generator.
The biggest problem with MT19937, besides its complexity and large state size, is that it needs to have its state properly seeded.
Like I said, it’s a heated debate which random number generator is the best one.
It is a heated debate, but it should be easier to agree that some RNG is not the best one than to agree it is.
Having said that, I think most projects should move on from MT19937 by now, defaulting to a cryptographically secure PRNG, and allowing to switch to a faster one (such as PCG or xoroshiro) when desired.
There are a lot of crypto-strong RNGs out there (AES on OFB mode? Counter Mode? SHA-3 in SHAKE128 or SHAKE256? Salsa20 or ChaCha? Or, do what I do and use RadioGatún), so not much standardization on that front.
With non crypto, we have in this thread already mentioned PCG ( http://www.pcg-random.org/ ), JKISS32, xoroshiro, and Vigna’s generators. There are others. Again, not much standardization.
But you're right, there's no successor anointed yet to MT19937, but it's about time. Wish some real expert in the field would publish an authoritative account (but opinionated enough to make real choices) that programming language devs could point to, and across the board implement:
* safe (ie, a cryptographically secure PRNG) <- default
* fast (if your application needs speed more than security against adversaries, such as Monte Carlo integration)
* others (if you really know what you're doing)
EDIT to add: it feels a bit like the old chestnut about IBM: nobody ever gets fired for choosing the Mersenne Twister...
I created a 'Random' service that lives for the length of the execution of the application.
This service has an instance of Random that persists with the object, and exposes simple methods with min/max parameters.
I register the service in a unity container, and then immediately resolve it, causing the Random type inside of the random service to instantiate.
Then anywhere I want to generate a random number, I inject that service.
This works because, as long as you persist a single instance of 'Random', two calls to 'Next' or 'NextDouble' won't result in the same number.
edit: It shows small-periods but otherwise it's not all that useful (see below).
The random number generator here is used quite often in projects and it looks pretty random. But if you look at the code you can see that it has four numbers that store state and its output can be entirely predicted from those four numbers that are consecutive outputs of the RNG.
Also you can always choose well-established, arbitrarily complex psuedo random algorithms. If you want to guarantee low correlation you could use PRBS (whatever shift amount you need, 31 may be enough for most scenarios) with the same shift register values and seeds that are maximally equidistant.
You can use any stream cipher you want instead, of course, but in my experience for video games the problem isn’t “I need a random bit” (which AES CTR is very good at but MT or any PCG/LCG is really just as fit for purpose) but “I need to sample from this weird distribution”. Stuff goes wrong as soon as someone needs to do something as simple as sampling from a set of cardinality not exactly a power of two let alone something more complex.