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In this repository you will find an application used to benchmark five different sorting algorithms. You will also find a report which introduces the chosen sorting algorithms, and discusses the results of the benchmarking process. The five sorting algorithms chosen are:

  1. Insertion Sort
  2. Merge Sort
  3. Counting Sort
  4. Quicksort
  5. Timsort
  • Python 3.6v was used

The following libraries/modules were imported:

import numpy as np
import pandas as pd
import time
import copy
import matplotlib.pyplot as plt
  • numpy was used to generate random arrays with n different sizes
  • pandas was used to create a dataframe containing the running times of all sorting algorithms
  • time was used to "measure" the running time of the chosen sorting algorithms
  • copy was used to make a copy.deepcopy() of the original arrays
  • matplotlib.pyplot was used to plot the running time of the sorting algorithms
File name Description
sorting_algorithms.py File that contains functions of the the five sorting algorithms
benchmark.py File that contains the functions that runs and measure the running time of the sorting algorithms, prints the results as a dataframe and shows the plot of the results
randomArrays.py File that contains the function that generate random arrays of different size and also contains the arrays created
CTA_Project.pdf PDF file that contains the project instructions
CTA_report.docx PDF file that introduces the chosen sorting algorithms, and discusses the results of the benchmarking process.