🔢 K-th Smallest Element: Insertion Sort vs Merge Sort

This project compares the performance of Insertion Sort and Merge Sort in finding the k-th smallest element of a randomly generated list. The goal is to evaluate how each sorting algorithm behaves as the list size increases, using repeated measurements for benchmarking.

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📁 Project Structure

• insertion.py – Uses Insertion Sort to sort the list and find the k-th smallest element.
• merge.py – Uses Merge Sort to sort the list and retrieve the k-th smallest element.

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⚙️ How It Works

Each script:

1. Generates random lists of different sizes.

2. Selects a random valid k for each list.

3. Sorts the list using the chosen algorithm.

4. Retrieves the k-th smallest element.

5. Measures and prints:

   • Average execution time
   • Maximum execution time
   • List size
   • Tested k values (for Merge Sort)

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🧪 Example Output

List size: 5000
Average time: 0.4321 seconds
Max time: 0.4902 seconds
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💻 Requirements

• Python 3.x
• No external dependencies (uses only random, time and built-in functions)

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👤 Author

Cláudio Alves Gonçalves de Oliveira Email: hi@claudioav.com

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📄 License

This project is licensed under the MIT License.