This project is a comprehensive implementation of various sorting algorithms, namely Insertion Sort, Heap Sort, Quick Sort, and Counting Sort. The primary objective is to analyze the operational structure of these algorithms and compare their execution times. The project leverages the Python GUI framework, Tkinter, to enhance the visualization of inputs and results.
The project incorporates a user interface developed with Tkinter, which accepts necessary inputs about the array to be sorted and generates the array accordingly. The sorted array is subsequently displayed, along with the time taken by the user-selected sorting algorithm to sort the array. The array generation system is designed to handle different input sizes.
The project utilizes the following tools and technologies:
- Visual Studio Code: Employed as the code editor.
- Python: Used as the high-level programming language for development.
- Tkinter: Serves as the framework for GUI implementation.
The project is structured into four distinct sections:
- Generator Section: Contains the code related to the generation of random arrays.
- Sorter Section: Houses the complete implementation of all four sorting algorithms.
- GUI Section: Integrates the functionalities of the Generator and Sorter sections, and contains the code for the entire frontend of the project.
- Main Section: Invokes instances for all other sections.
The project offers the following features:
- Generation of random arrays of user-defined sizes, within the minimum and maximum parameters specified by the user, eliminating the need to manually input large numbers of elements.
- Implementation of four different sorting algorithms – Insertion Sort, Heap Sort, Quick Sort, and Counting Sort.
- Capability to track the time taken for sorting by different algorithms, aiding in the analysis and comparison of algorithm performance.
- Input validation and error checking to ensure data integrity and reliability.