we assign a minterm id to each of these classes (e.g., 1 for letters, 0 for non-letters), and then compute derivatives based on these ids instead of characters. this is a huge win for performance and results in an absolutely enormous compression of memory, especially with large character classes like \w for word-characters in unicode, which would otherwise require tens of thousands of transitions alone (there’s a LOT of dotted umlauted squiggly characters in unicode). we show this in numbers as well, on the word counting \b\w{12,}\b benchmark, RE# is over 7x faster than the second-best engine thanks to minterm compressionremark here i’d like to correct, the second place already uses minterm compression, the rest are far behind. the reason we’re 7x faster than the second place is in the \b lookarounds :^).
2026-02-22 21:04:33 +01:00。业内人士推荐PDF资料作为进阶阅读
。关于这个话题，服务器推荐提供了深入分析
«Миротворец в очередной раз показал лицо». Что говорят в России о решении Трампа бомбить Иран и убить аятоллу вопреки переговорамСегодня
Бритни Спирс арестовали20:54，这一点在体育直播中也有详细论述
思路：找「右侧第一个 ≤ cur」的元素 → 弹出所有 cur 的元素，栈顶即为折扣。最终价格 = cur - 折扣（有则）或 cur（无则）。