Which is the fastest sorting algorithm when the list is nearly sorted?
What is the best sorting algorithm for an almost sorted array?How one should optimally sort the almost sorted data of an array is a common problem. Many sorting algorithms are available, but the one which is best suited for the almost sorted array is the insertion sort. Show
Analysis of different sorting techniquesIn this article, we will discuss important properties of different sorting techniques including their complexity, stability and memory constraints. Before understanding this article, you should understand basics of different sorting techniques (See : Sorting Techniques). Time complexity Analysis – Comparison based sorting –
Non-comparison based sorting –
In-place/Outplace technique – Online/Offline technique – Stable/Unstable technique – In the first iteration, the minimum element found is 1 and it is swapped with 4 at 0th position. Therefore, the order of 4 with respect to 4 at the 1st position will change. Similarly, quick sort and heap sort are also unstable. Out of non-comparison based techniques, Counting sort and Bucket sort are stable sorting techniques whereas radix sort stability depends on the underlying algorithm used for sorting. Analysis of sorting techniques :
Que – 1. Which sorting algorithm will take the least time when all elements of input array are identical? Consider typical implementations of sorting algorithms. Solution: As discussed, insertion sort will have the complexity of n when the input array is already sorted. Que – 2. Consider the Quicksort algorithm. Suppose there is a procedure for finding a pivot element which splits the list into two sub-lists each of which contains at least one-fifth of the elements. Let T(n) be the number of comparisons required to sort n elements. Then, (GATE-CS-2012) (A) T(n) <= 2T(n/5) + n (B) T(n) <= T(n/5) + T(4n/5) + n (C) T(n) <= 2T(4n/5) + n (D) T(n) <= 2T(n/2) + n Solution: The complexity of quick sort can be written as: As given in question, one list contains 1/5th of total elements. Therefore, another list will have 4/5 of total elements. Putting values, we get: T(n) = T(n/5) + T(4n/5) + cn, which matches option (B). Time and Space Complexity Comparison Table :
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Which is the fastest sorting algorithm when the list is nearly sorted?Bubble sort is fast, but insertion sort has lower overhead. Shell sort is fast because it is based on insertion sort. Merge sort, heap sort, and quick sort do not adapt to nearly sorted data. Which is the best sorting algorithm to use when the list is almost ordered in ascending sequence?Many sorting algorithms are available, but the one which is best suited for the almost sorted array is the insertion sort. Which sorting algorithm gives best performance when array elements are already sorted quick heap merge insertion?Question 10 Explanation: The bubble sort is at its best if the input data is sorted. Which algorithm gives better performance in sorting Mcq?Explanation: Quick sort is the fastest known sorting algorithm because of its highly optimized inner loop. 2. Which of the following sorting algorithm is best of the elements are already sorted?Which of the following sorting algorithm is best suited if the elements are already sorted? Explanation: The insertion sort's best case running time is O. (n). When the input list is already sorted, the best case scenario occurs. Which algorithm is more efficient?Quicksort is one of the most efficient sorting algorithms, and this makes of it one of the most used as well. The first thing to do is to select a pivot number, this number will separate the data, on its left are the numbers smaller than it and the greater numbers on the right. Time Complexities of Sorting Algorithms:
Bubble sort is fast, but insertion sort has lower overhead. Shell sort is fast because it is based on insertion sort. Merge sort, heap sort, and quick sort do not adapt to nearly sorted data. You may also like:
Why are Sorting Algorithms Important?Since sorting can often help reduce the algorithmic complexity of a problem, it finds significant uses in computer science. A quick Google search reveals that there are over 40 different sorting algorithms used in the computing world today. Crazy right? Well, you will be flabbergasted when you realize just how useful sorting algorithms are in real life. Some of the best examples of real-world implementation of the same are:
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