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Sorting Algorithms: Insertion Sort, Bubble Sort, Merge Sort, Quick Sort, Heap Sort, External Sort

  • The insertion-sort algorithm sorts a list of values by repeatedly inserting a new element into a sorted sublist until the whole list is sorted. The insertion sort algorithm presented here sorts a list of elements by repeatedly inserting a new element into a sorted partial array until the whole array is sorted.
  • At the kth iteration, to insert an element into an array of size k, it may take k comparisons to find the insertion position, and k moves to insert the element. Let T(n) denote the complexity for insertion sort and c denote the total number of other operations such as assignments and additional comparisons in each iteration.

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  • Insertion Sort algorithm implementation in Java and demo result:

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  • A bubble sort sorts the array in multiple phases. Each pass successively swaps the neighboring elements if the elements are not in order. The bubble sort algorithm makes several passes through the array. On each pass, successive neighboring pairs are compared. If a pair is in decreasing order its values are swapped; otherwise, the values remain unchanged.
  • The technique is called a bubble sort or sinking sort, because the smaller values gradually “bubble” their way to the top and the larger values sink to the bottom. After the first pass, the last element becomes the largest in the array. After the second pass, the second-to-last element becomes the second largest in the array. This process is continued until all elements are sorted.

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  • Bubble Sort algorithm implementation in Java, and demo result:

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  • The merge sort algorithm can be described recursively as following: The algorithm divides the array into two halves and applies a merge sort on each half recursively. After the two halves are sorted, merge them. Following illustrates a merge sort of an array of eight elements (2 9 5 4 8 1 6 7). The original array is split into (2 9 5 4) and (8 1 6 7). Apply a merge sort on these two subarrays recursively to split (2 9 5 4) into (2 9) and (5 4) and (8 1 6 7) into (8 1) and (6 7).
  • This process continues until the subarray contains only one element. For example, array (2 9) is split into the subarrays (2) and (9). Since array (2) contains a single element, it cannot be further split. Now merge (2) with (9) into a new sorted array (2 9); merge (5) with (4) into a new sorted array (4 5). Merge (2 9) with (4 5) into a new sorted array (2 4 5 9), and finally merge (2 4 5 9) with (1 6 7 8) into a new sorted array (1 2 4 5 6 7 8 9).

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  • Merge Sort algorithm implementation in Java and demo result:

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  • The algorithm selects an element, called the pivot, in the array. It divides the array into two parts, so that all the elements in the first part are less than or equal to the pivot and all the elements in the second part are greater than the pivot. The quick sort algorithm is then recursively applied to the first part and then the second part. Each partition places the pivot in the right place. The selection of the pivot affects the performance of the algorithm. Ideally, the algorithm should choose the pivot that divides the two parts evenly.
  • For simplicity, assume the first element in the array is chosen as the pivot. Following illustrates how to sort an array (5 2 9 3 8 4 0 1 6 7) using quick sort. Choose the first element, 5, as the pivot. The array is partitioned into two parts. The highlighted pivot is placed in the right place in the array. Apply quick sort on two partial arrays (4 2 1 3 0) and then (8 9 6 7). The pivot 4 partitions (4 2 1 3 0) into just one partial array (0 2 1 3). Apply quick sort on (0 2 1 3). The pivot 0 partitions it into just one partial array (2 1 3). Apply quick sort on (2 1 3). The pivot 2 partitions it into (1) and (3). Apply quick sort on (1). Since the array contains just one element, no further partition is needed.

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  • Quick Sort algorithm implementation in Java, and demo result:

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  • A heap sort uses a binary heap. It first adds all the elements to a heap and then removes the largest elements successively to obtain a sorted list. Heap sorts use a binary heap, which is a complete binary tree. A binary tree is a hierarchical structure. It either is empty or it consists of an element, called the root and two distinct binary trees, called the left subtree and right subtree.

  • The length of a path is the number of the edges in the path. The depth of a node is the length of the path from the root to the node. A binary heap is a binary tree with the following properties:

    ■ Shape property: It is a complete binary tree.

    ■ Heap property: Each node is greater than or equal to any of its children

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  • Heap Sort algorithm implementation in Java, and demo result:

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  • We can sort a large amount data using an external sort. All the sort algorithms discussed previously assume that all the data to be sorted are available at one time in internal memory such as in an array. To sort data stored in an external file, we must first bring the data to the memory and then sort it internally. However, if the file is too large all the data in the file cannot be brought to memory at one time. To sort data in a large external file is called an external sort.

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