A comprehensive, interactive Python application designed to benchmark, analyze, and visualize the performance of various core algorithms. Featuring a custom Graphical User Interface (GUI), this tool provides real-time execution insights, time complexity analysis, and automated reporting.
- Multi-Algorithm Benchmarking: Compare sorting, searching, and custom algorithms side-by-side under identical execution environments.
- Interactive GUI: User-friendly interface built for configuring dataset sizes, types (random, sorted, reversed), and iteration counts dynamically.
- Live Visualizations: Real-time plotting of time complexity, comparisons, and algorithmic behaviors.
- Deep Technical Reports: Automatically generates structured performance analyses, memory usage overviews, and execution summaries.
ALGO/
│
├── algorithms/ # Core algorithmic implementations (Sorting, Searching, etc.)
├── benchmark/ # Performance evaluation and metrics collection engines
├── gui/ # User interface components and windows
├── visualization/ # Charting, plotting, and real-time animation modules
├── analysis/ # Complexity verification and statistical processing
├── data/ # Test datasets and configurations
└── report/ # Automated markdown and data export tools
## 🛠️ Tech Stack & Dependencies
- **Core:** Python 3.8+
- **GUI Framework:** CustomTkinter (Modern Tkinter extension)
- **Data & Visualization:** Matplotlib, NumPy, Pandas
- **Static Analysis:** Pyright
⚡ Quick Start
Prerequisites
Ensure you have Python installed, then clone the repository:
git clone [https://github.com/Fatmanur-dinc/algorithm-benchmark-analysis.git](https://github.com/Fatmanur-dinc/algorithm-benchmark-analysis.git)
cd algorithm-benchmark-analysis
Installation
Set up a virtual environment and install the required dependencies:
python -m venv .venv
source .venv/bin/activate # On Windows use: .venv\Scripts\activate
pip install -r requirements.txt
Run the Application
python main.py
📚 Documentation & Deep Dives
This project includes highly detailed analysis and architectural documentation. Explore the links below for a comprehensive technical breakdown:
📖 Project Analysis & Overview - General concepts and design goals.
⚙️ Technical Details - Under-the-hood implementation and system design.
📈 Sorting Algorithms Analysis - Execution metrics and comparisons for specific sorting strategies.
🧪 AI Explanations - Algorithmic theory, complexities, and insights.
🧭 Quick Start Guide - Detailed usage instructions.
📄 License
This project is licensed under the MIT License - see the LICENSE file for details.