Merge Sort Program in Java: Difference Between Merge Sort & Quicksort
By Rohan Vats
Updated on Jul 03, 2023 | 7 min read | 6.05K+ views
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By Rohan Vats
Updated on Jul 03, 2023 | 7 min read | 6.05K+ views
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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.
Quicksort and Merge Sort program in Java are two well-liked and effective ways for sorting components in Java programmes in the realm of sorting algorithms. Both algorithms use distinct methods and each has its pros and drawbacks. This review will examine the variations between Merge Sort and Quicksort with an emphasis on how they are implemented in Java.
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The merge sort Java code is a divide-and-conquer algorithm, as mentioned earlier. It is a stable sort, which implies that throughout the sorting process, the array items keep their initial positions about one another.
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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.
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Although functionally similar, pertinent emphasis must be laid upon the fundamental difference between quicksort and mergesort in JAVA.
1. Approach:
2. Performance:
3. Stability:
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Also Read: Types of Literals in Java with Examples
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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In conclusion, choosing the best sorting algorithm for a particular case requires a grasp of the distinctions between Merge Sort and Quicksort. Both techniques have advantages and disadvantages, and Java’s implementation of both makes array sorting effective. When implementing sorting algorithms in their Java programmes, developers can make well-informed choices by taking into account aspects like stability, performance, and memory utilisation.
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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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.
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.
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.
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Rohan Vats is a Senior Engineering Manager with over a decade of experience in building scalable frontend architectures and leading high-performing engineering teams. Holding a B.Tech in Computer Scie...
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