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In this report, I benchmarked four different sorting algorithms (insertion, merge, pigeonhole, and counting sort) based on their run-time data obtained from 3 experiments with random data (1), sorted data (2), and reversed data (3).

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BBM204:Sort-Algorithm-Complexity-Benchmark

Performance Analysis of insertion, merge, pigeonhole, and counting sort:

Efficient sorting is important for optimizing the efficiency of other algorithms that require input data to be sorted. The efficiency of a sorting algorithm can be observed by applying it to sort datasets of varying sizes and other characteristics of the dataset instances that are to be sorted. In this report, we will be classifying the given sorting algorithms (insertion, merge, pigeonhole, and counting sort) based on their run-time data obtained from 3 experiments with random data (1), sorted data (2), and reversed data (3).

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In this report, I benchmarked four different sorting algorithms (insertion, merge, pigeonhole, and counting sort) based on their run-time data obtained from 3 experiments with random data (1), sorted data (2), and reversed data (3).

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