strstr
Joined 15 years ago
Joined 15 years ago
> Sampling the current RNG through observations,
> Computing the current internal RNG state,
> Predicting the future internal states,
> Calculating corresponding quality levels for each future call, and finally
> Making use of the predicted levels with some adapters.
The entropy->seeds (internal RNG state) step took more math of course. Frankly, I wouldn’t be surprised if they could have extracted the seeds without the math with a bit of RE and memory inspection.
The version I did wasn’t predicting quality of course, it was predicting tie breakers
The prng was seeded with usec time at first call. I called the rng a bunch of times to harvest entropy, and scanned the plausible usec times to find the seed. Then I primed the prng so I would win ties.
Frankly, I assume I implemented this wrong, but the theory was there lol.
The funny one is the buildings that have better landscaping. A few of the buildings in the post only look attractive as a consequence of the green courtyard in front. If you cover up that part of the photo, they just don’t look as stunning compared to the other. Perhaps that’s an argument for traditional courtyards (fair enough), but it doesn’t imply the need for traditional building construction.
QuickSelect is average case n, and is, roughly, quick sort where you throw away one of the sides each time and recurse on the other. This has a fat tail for cases where you pick a bad pivot (similar to quicksort), but you can median-of-medians your way out of that problem if someone cares. (Median of medians being where you subdivide the array into, say, 5 arrays, recursively compute the median on those, and pick the middle median as your pivot, which guarantees linear progress per iteration)
Eventually most of those started getting spoiled too lol.
Frankly, I’m surprised split lock detection is enabled anywhere outside of multi-tenant clouds.