The short answer is that quick-sort is ideally suited to sorting large sets of data. With small sets of data, the combination of selecting an optimal pivot, partitioning the set and the need to recursively call itself adds an overhead that even the most inefficient bubble-sort can easily overcome via iteration alone. Using triple partitioning to ensure stability simply adds to the overhead.
I haven't tested the effects on arrays, but using in place sorting of doubly-linked lists with inline, triple-partitioning and non-recursive tail calls, I've found the cut off point is around 20 items. Anything less and an optimised bubble-sort performs better on average. However the actual difference is negligible -- only a few microseconds. On a modern computer, no-one is going to notice the difference.
For larger datasets, the quick sort is hard to beat unless the dataset is already sorted. I cater for that by performing a single-pass optimised bubble-sort. If a change is detected and the unsorted subset has 20 or more items, a quick-sort controls the remainder of the sorting process.
In merge sort the whole is divided into two sub arrays. (This way of solving problem is called Divide and conquer algorithm) These sub arrays are called auxiliary arrays. First an array A is divided into two auxiliary arrays A1 and A2. Now these auxiliary arrays are further divided until we reach a stage with an auxiliary array of 2 elements. These 2 elements are arranged in incremental order and merged with the previous divided arrays. So we can say that auxiliary array is used to implement the basic principle of merge sort.
Yes, that's how quick-sort works.
Quick Sort
You can sort an array with any method you want, but there is a built-in qsort function, declared in stdlib.h (see the attached link).bubble sort, quick sort, insertion sort, merge sort, radix sort and lot more..merge sort is the most efficient one..
Never. Bubble sort is often cited as an example of how not to write a sorting algorithm and is used purely as a programming exercise. It is never used in production code. Although reasonably efficient when sorting small lists, an insertion sort performs better on average. But for larger lists it has no practical uses. A merge sort is better for large lists, but if stability isn't an issue a quick sort is even better. Hybrid sorts typically use quick sort until a partition is small enough for an insertion sort to complete the job.
You cannot sort arrays by other arrays; that wouldn't make sense, anyway.
Quick sort runs the loop from the start to the end everytime it finds a large value or a small value while in merge sort starts from the first position of the array and assembles the large or small numbers in one side in just one loop so its more faster than quick sort
In merge sort the whole is divided into two sub arrays. (This way of solving problem is called Divide and conquer algorithm) These sub arrays are called auxiliary arrays. First an array A is divided into two auxiliary arrays A1 and A2. Now these auxiliary arrays are further divided until we reach a stage with an auxiliary array of 2 elements. These 2 elements are arranged in incremental order and merged with the previous divided arrays. So we can say that auxiliary array is used to implement the basic principle of merge sort.
Quick Sort
Yes, that's how quick-sort works.
Quick Sort
You can sort an array with any method you want, but there is a built-in qsort function, declared in stdlib.h (see the attached link).bubble sort, quick sort, insertion sort, merge sort, radix sort and lot more..merge sort is the most efficient one..
Arrays hold objects in a programming language. For example, they could hold a list of names. You can sort or call up any of the names now that they are in an array easily.
When you want to sort an array.
Although quick sort has a worst case time complexity of O(n^2), but for sorting a large amount of numbers, quick sort is very efficient because of the concept of locality of reference.
quick sort is a divide and conquer method , it is not dynamic programming
Never. Bubble sort is often cited as an example of how not to write a sorting algorithm and is used purely as a programming exercise. It is never used in production code. Although reasonably efficient when sorting small lists, an insertion sort performs better on average. But for larger lists it has no practical uses. A merge sort is better for large lists, but if stability isn't an issue a quick sort is even better. Hybrid sorts typically use quick sort until a partition is small enough for an insertion sort to complete the job.