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  2. Bubble sort - Wikipedia

    en.wikipedia.org/wiki/Bubble_sort

    Bubble sort, sometimes referred to as sinking sort, is a simple sorting algorithm that repeatedly steps through the input list element by element, comparing the current element with the one after it, swapping their values if needed. These passes through the list are repeated until no swaps have to be performed during a pass, meaning that the ...

  3. Best, worst and average case - Wikipedia

    en.wikipedia.org/wiki/Best,_worst_and_average_case

    Bubble sort: Array: O ... O(n) O(n n!) O(∞) O(1) Graphs of functions commonly used in the analysis of ... case running time yields a quadratic function of the input ...

  4. Sorting algorithm - Wikipedia

    en.wikipedia.org/wiki/Sorting_algorithm

    For example, if any number of elements are out of place by only one position (e.g. 0123546789 and 1032547698), bubble sort's exchange will get them in order on the first pass, the second pass will find all elements in order, so the sort will take only 2n time.

  5. Time complexity - Wikipedia

    en.wikipedia.org/wiki/Time_complexity

    Graphs of functions commonly used in the analysis of algorithms, showing the number of operations N as the result of input size n for each function. In theoretical computer science, the time complexity is the computational complexity that describes the amount of computer time it takes to run an algorithm. Time complexity is commonly estimated ...

  6. Algorithmic efficiency - Wikipedia

    en.wikipedia.org/wiki/Algorithmic_efficiency

    Analysis of algorithms, typically using concepts like time complexity, can be used to get an estimate of the running time as a function of the size of the input data. The result is normally expressed using Big O notation .

  7. Worst-case complexity - Wikipedia

    en.wikipedia.org/wiki/Worst-case_complexity

    In computer science (specifically computational complexity theory), the worst-case complexity measures the resources (e.g. running time, memory) that an algorithm requires given an input of arbitrary size (commonly denoted as n in asymptotic notation). It gives an upper bound on the resources required by the algorithm.

  8. Integer sorting - Wikipedia

    en.wikipedia.org/wiki/Integer_sorting

    Time bounds for integer sorting algorithms typically depend on three parameters: the number n of data values to be sorted, the magnitude K of the largest possible key to be sorted, and the number w of bits that can be represented in a single machine word of the computer on which the algorithm is to be performed.

  9. Counting sort - Wikipedia

    en.wikipedia.org/wiki/Counting_sort

    Bucket sort may be used in lieu of counting sort, and entails a similar time analysis. However, compared to counting sort, bucket sort requires linked lists, dynamic arrays, or a large amount of pre-allocated memory to hold the sets of items within each bucket, whereas counting sort stores a single number (the count of items) per bucket. [4]