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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.。PDF资料对此有专业解读
This entry was posted in commodore, retrocoding on February 28, 2026 by Michael Martin.，详情可参考heLLoword翻译官方下载
Alex Imas, professor of behavioral science, economics, and applied AI at the University of Chicago Booth School of Business, agreed, with an important clarification. It’s “trivially true” that businesses ideally wouldn’t need any human workers, he told Fortune, “but from the perspective of, like, if you did that tomorrow, you would end up in a very bad place for many, many different reasons.”