NFAs are cheaper to construct, but have a O(n*m) matching time, where n is the size of the input and m is the size of the state graph. NFAs are often seen as the reasonable middle ground, but i disagree and will argue that NFAs are worse than the other two. they are theoretically “linear”, but in practice they do not perform as well as DFAs (in the average case they are also much slower than backtracking). they spend the complexity in the wrong place - why would i want matching to be slow?! that’s where most of the time is spent. the problem is that m can be arbitrarily large, and putting a large constant of let’s say 1000 on top of n will make matching 1000x slower. just not acceptable for real workloads, the benchmarks speak for themselves here.
14:17, 5 марта 2026Экономика
。safew官方版本下载对此有专业解读
国内参与者众多是一个好的现象。一家独大往往意味着市场想象空间有限。回溯智能手机早期，同样是百花齐放、形态各异。如今各家对AI眼镜的定义也截然不同：车厂视其为车控入口，小米侧重家居联动，而阿里聚焦“办事能力”与生态协同。
there was a whole bunch of practical stuff that had to be done to get the PSF actually off the ground, including, I don’t know, registering to be a 501(c)(3).
。同城约会对此有专业解读
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