Introduction to the Merge Sort Program in JAVA
As the name suggests, the merge sort program in JAVA is a sorting algorithm. It has been classically conceptualized as the divide and conquer algorithm in JAVA. The merge sort program in Java works by recursively breaking down an input array into two or more of its constituent sub-problems until these are simple enough to be solved directly.
The constituent sub-problems can either be similar or somewhat related to the parent problem. The individual solutions to each sub-problem are then combined to attain the solution to the original parent problem.
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How Does the Merge Sort Program in Java Work?
As iterated earlier, the merge sort program in JAVA is a divide and conquer algorithm. It is a stable sort which means that the array elements maintain their original positions relative to each other throughout the sorting process.
- Divide: In this step, an input array is divided into its two constituent halves. This step is continually repeated for all the resultant half arrays until there are no more half arrays to divide further.
- Conquer: In this step, the divided arrays are sorted and merged from bottom to top to reach the final sorted array.
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Difference Between Quicksort and Merge Sort Program in Java
Although functionally similar, pertinent emphasis must be laid upon the fundamental difference between quicksort and mergesort in JAVA.
- Mechanism: Quicksort is an internal, in-place sorting algorithm, whereas mergesort is an external, out-of-place sorting algorithm. In quicksort, elements are sorted basis a key element known as the pivot. The pivot is generally the middle value in an input array. Elements with a lesser value than the pivot are pushed to the pivot’s left side, while elements with a greater value to the pivot’s right side. Here, the left side is referred to as the left partition, and the right side is referred to as the right partition. Contrarily, mergesort splits an array into two sub-arrays (n/2) repeatedly until only one element is left. It then combines the sub-arrays to form the sorted array.
- Application: While quicksort is suitable for small arrays, mergesort works with any array, regardless of its size.
- Speed: In the case of quicksort, the smaller the dataset, the faster the algorithm. Mergesort, on the other hand, works at a consistent speed for all data sets.
- Space requirement and memory usage: As mentioned earlier, mergesort is an external, out-of-place sorting algorithm. Its space complexity is O (n). Therefore, it requires an additional storage of (O (n)) to sort the auxiliary array.
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Time- Complexity Analysis of Merge Sort Program in JAVA
The merge sort program in JAVA has a time complexity of O (n*log n). According to Binary Search, whenever a number is divided into half in every step, it can be represented by the logarithmic function ‘log n’. The number of steps (at most) can be represented by log n +1. The middle of any sub-array is O (1).
Thus, to merge the sub-arrays, a running time of O (n) will be required. Hence, the total time for the merge sort program in JAVA becomes n (log n +1). This amounts to a time complexity of O (n*log n) in all the three cases (worst, average and best) as merge sort always takes linear time to merge two halves.
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Just as sorted data for humans is logically sound and easier to comprehend, sorted arrays are more manageable for computers to work with. This is where the merge sort program in JAVA proves advantageous. It is an efficient, general-purpose, comparison-based sorting algorithm.
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What is sorting in programming?
Sorting is the technique of putting objects in a particular order. This is usually done to make them more manageable, or to make them easier to access. In computer science, we have sorting algorithms for data structures. These sort algorithms can be divided into two categories. One is the comparison-based sorting algorithms and the other is insertion-based sorting algorithms. In comparison-based sorting algorithms, an element is compared with another element to find the matching sort key, which is the only key common between them. In insertion-based sorting algorithms, the new element is added to the front of an array and the element placed in the end is shifted to the beginning.
What are the types of sorting algorithms in programming?
Sorting algorithms are mostly classified into 3 types: sequential sorting, parallel sorting, partitioning sorting. Sequential sorting is easiest to understand. It is the one that we use when we are sorting in our head. Everything is sorted from smallest to largest. The most common sequential sorting algorithms are insertion sort, bubble sort, quick sort and merge sort. All these sorting algorithms can be easily parallelized. In the case of parallel sorting, each of the tasks depends on the previous task's result. So, the order of the output is not guaranteed. Two parallel sorting algorithms that are used are topological sort and bottom-up mergesort. Partitioning sorting algorithms try to partition the input array so that each subarray can be sorted individually. Partitioning sorting algorithms include binary search, chaining, heap sort, and radix sort.
What are the differences between merge sort and quick sort?
Merge sort is a divide and conquer algorithm. It divides a list into two partitions based on some pivot item, recursively sort each of the partitions and then merges the output. The merge step can be done with a parallel merge sort. Quick sort is a O(nlogn) sorting algorithm. It is a much simpler algorithm, but it must pivot on a random array element each time.