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 :^).
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这一结果同样能满足以色列的核心诉求：一个无核的伊朗。这将失去对以色列的致命威胁。伊朗此前多次表态要消灭以色列，而以色列国土面积狭小，一颗原子弹就足以使其面临灭顶之灾，消除伊朗的核能力，就等于消除了以色列的核心生存危机，以色列自然也会接受这样的方案。