A Programmer’s approach of looking at Array vs. Linked List – Linked List – In general, array is considered a data structure for which size
quicksort
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Why Quick Sort preferred for Arrays and Merge Sort for Linked Lists? – Searching and Sorting – Quick Sort in its general form is an in-place sort. whereas merge sort requires O(N) extra storage, N denoting the array size which may be quite expensive.
Binary Insertion Sort – Searching and Sorting – We can use binary search to reduce the number of comparisons in normal insertion sort. Binary Insertion Sort find use binary search to find the proper location to insert the selected item at each iteration.
JAVA programming – Given a sorted array and a number x, find the pair in array whose sum is closest to x – Searching and sorting – Given a sorted array and a number x, find a pair in array whose sum is closest to x.
C++ programming – Given a sorted array and a number x, find the pair in array whose sum is closest to x – Searching and sorting – Given a sorted array and a number x, find a pair in array whose sum is closest to x.
C programming – Given a sorted array and a number x, find the pair in array whose sum is closest to x – Searching and sorting.- Given a sorted array. find a pair in array whose sum is closest to x.
Search in an almost sorted array – Searching and Sorting – A simple solution is linearly search given key in given array.Time complexity of solution is O(n).We cab modify binary search to do it in O(Logn) time.
QuickSort on Doubly Linked List – Searching and sorting -. The idea is simple, we first find out pointer to last node. Once we have pointer to last node, we can recursively sort the linked list using pointers to first and last nodes of linked list.
QuickSort on Singly Linked List – Searching and sorting – Quick Sort on Doubly Linked List is discussed here.In Singly linked list was given as an exercise. Following is C++ implementation for same.
Iterative Quick Sort – Searching and Sorting – Partition process is same in both recursive and iterative. The same techniques to choose optimal pivot can also be applied to iterative version.