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Commit 9c36253

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style(book): better wording for table
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‎book/content/part01/algorithms-analysis.asc

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@@ -59,10 +59,10 @@ To give you a clearer picture of how different algorithms perform as the input s
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|Input size -> |10 |100 |10k |100k |1M
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|Finding if a number is odd |< 1 sec. |< 1 sec. |< 1 sec. |< 1 sec. |< 1 sec.
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|Sorting elements in array with merge sort |< 1 sec. |< 1 sec. |< 1 sec. |few sec. |20 sec.
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|Sorting elements in array with Bubble Sort |< 1 sec. |< 1 sec. |2 minutes |3 hours |12 days
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|Finding all subsets of a given set |< 1 sec. |40,170 trillion years |> centillion years |∞ |∞
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|Find all permutations of a string |4 sec. |> vigintillion years |> centillion years |∞ |∞
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|Sorting array with merge sort |< 1 sec. |< 1 sec. |< 1 sec. |few sec. |20 sec.
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|Sorting array with Selection Sort |< 1 sec. |< 1 sec. |2 minutes |3 hours |12 days
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|Finding all subsets |< 1 sec. |40,170 trillion years |> centillion years |∞ |∞
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|Finding string permutations |4 sec. |> vigintillion years |> centillion years |∞ |∞
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|=============================================================================================
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Most algorithms are affected by the size of the input (`n`). Let's say you need to arrange numbers in ascending order. Sorting ten items will naturally take less time than sorting out 2 million. But, how much longer? As the input size grow, some algorithms take proportionally more time, we classify them as <<part01-algorithms-analysis#linear, linear>> runtime [or `O(n)`]. Others might take power two longer; we call them <<part01-algorithms-analysis#quadratic, quadratic>> running time [or `O(n^2^)`].

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AltStyle によって変換されたページ (->オリジナル) /