Remaining changes
Wolfgang Corcoran-Mathe
(04 Sep 2020 17:12 UTC)
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Re: Remaining changes
John Cowan
(05 Sep 2020 03:41 UTC)
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(missing)
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(missing)
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(missing)
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Fwd: Remaining changes
Marc Nieper-Wißkirchen
(06 Sep 2020 07:43 UTC)
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Re: Remaining changes
Marc Nieper-Wißkirchen
(06 Sep 2020 09:33 UTC)
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Re: Remaining changes
Wolfgang Corcoran-Mathe
(06 Sep 2020 17:24 UTC)
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Re: Remaining changes
Marc Nieper-Wißkirchen
(06 Sep 2020 17:30 UTC)
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Re: Remaining changes
Wolfgang Corcoran-Mathe
(06 Sep 2020 17:40 UTC)
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Re: Remaining changes
John Cowan
(06 Sep 2020 20:04 UTC)
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Re: Remaining changes
Marc Nieper-Wißkirchen
(06 Sep 2020 20:40 UTC)
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Re: Remaining changes
John Cowan
(07 Sep 2020 00:03 UTC)
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Re: Remaining changes
Marc Nieper-Wißkirchen
(07 Sep 2020 06:31 UTC)
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Re: Remaining changes
Wolfgang Corcoran-Mathe
(07 Sep 2020 15:46 UTC)
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Re: Remaining changes
Wolfgang Corcoran-Mathe
(07 Sep 2020 20:56 UTC)
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Re: Remaining changes
John Cowan
(07 Sep 2020 21:16 UTC)
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Re: Remaining changes
Wolfgang Corcoran-Mathe
(07 Sep 2020 21:57 UTC)
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Re: Remaining changes
Marc Nieper-Wißkirchen
(08 Sep 2020 14:25 UTC)
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Re: Remaining changes
John Cowan
(08 Sep 2020 15:26 UTC)
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Fwd: Remaining changes
John Cowan
(05 Sep 2020 17:48 UTC)
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Fwd: Remaining changes
Marc Nieper-Wißkirchen
(05 Sep 2020 12:59 UTC)
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Re: Remaining changes Marc Nieper-Wißkirchen (05 Sep 2020 13:07 UTC)
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Am Sa., 5. Sept. 2020 um 14:58 Uhr schrieb Marc Nieper-Wißkirchen <xxxxxx@nieper-wisskirchen.de>: > Please take into consideration that, as Wolfgang observed, vectors > have no O(1) random access guarantee. There are meaningful > implementions of vectors conceivable that have, say, O(log n) random > access time. Actually, such implementations are not only conceivable but, given the illusion of unlimited space, the standard implementation of a vector has O(log n) random access time: (vector-ref vec i) => [fetch value at location vector-base(vec) + i] So, complexity comes from the addition, which is O(log n) in the size n of the added numbers. That it does not matter in practice, is due to the fact that n is usually bounded by the size of the computer's memory. When we talk about algorithmic complexities, though, it only makes sense if we view the independent variable (n in this example) as potentially arbitrarily large. (Otherwise, merge sort would sort in O(n) or even in O(1)...)