Abstract:
Merge sort is often considered one of the most universally effective traditional sorting algorithms due to its consistency. It utilizes a divide and conquer algorithmic approach to break a large array down into smaller and smaller sub-components until only a couple of values are being compared, and then the sub-arrays are then merged back together to form a total sort.
The purpose of this comparative analysis is to determine the efficiency of both iterative and merge-sort against one another over a series of large data sets in order to gauge the effectiveness of the program over a significant enough period of time to gauge the effectiveness of the algorithm. The expectation from this benchmark is to prove that the best-case (big Ω), average-case (Θ), and worst-case (O) performance of the algorithm will be consistent over any size data set.
/*Program Sources:
* Recursive & Iterative Merge sort methods aquired from Geeks for Geeks
* https://www.geeksforgeeks.org/iterative-merge-sort/
*
* JVM warmup Idea/method retrieved from:
* https://www.baeldung.com/java-jvm-warmup
*
* All methods cited have been edited or revised in order to more
* effectively work with benchmark program
*/
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