Static Analysis of Code Quality in Open-Source Python Projects

This repository contains the code, data, and figures for reproducing the analysis in the paper:

Static Analysis of Code Quality in Open-Source Python Projects
Submitted to Journal of Undergraduate Research International (JURI), 2025

📖 Overview

This project conducts a systematic static analysis of two popular open-source Python projects (Requests and BeautifulSoup4) to evaluate code quality metrics including cyclomatic complexity, maintainability, and PEP8 compliance.

🔧 Tools Used

• Radon → Lines of Code (LOC), Cyclomatic Complexity (CC), Maintainability Index (MI)
• Pylint → Code quality scoring and code smells detection
• Flake8 → PEP8 style violations

📊 Project Structure

Static-Analysis-of-Code-Quality-in-Open-Source-Python-Projects/
├── run_analysis.py # Main script to reproduce entire analysis
├── analyze_metrics_per_module.py # Core analysis script
├── generate_plots.py # Visualization script
├── requirements.txt # Python dependencies
├── BeautifulSoup4_metrics.csv # Analysis results for BeautifulSoup4
├── requests_metrics.csv # Analysis results for Requests
└── figures/ # Generated visualization plots

🚀 Quick Start (Full Reproduction)

1. Clone this repository

   git clone https://github.com/BashirAdam/Static-Analysis-of-Code-Quality-in-Open-Source-Python-Projects.git
   cd Static-Analysis-of-Code-Quality-in-Open-Source-Python-Projects

2. Install dependencies

   pip install -r requirements.txt

3. Run the complete analysis

   python run_analysis.py

   This single command will:

   • Clone the target projects (Requests and BeautifulSoup4)
   • Run all static analysis tools
   • Generate all metrics CSV files
   • Create all visualization figures
   • Display summary statistics

🔍 Manual Execution

If you prefer to run steps individually:

# Run the metric analysis
python analyze_metrics_per_module.py

# Generate visualizations
python generate_plots.py

📈 Output Files

• BeautifulSoup4_metrics.csv - Metrics for 19 Python modules
• requests_metrics.csv - Metrics for 34 Python modules
• figures/ - 6 visualization plots showing complexity distributions and relationships

CSV Columns:

• Module/File - Name of the Python file
• Lines of Code - Total lines in the file
• Cyclomatic Complexity (avg) - Average complexity score
• Maintainability Index - Code maintainability score (0-100)
• Pylint Score - Code quality score (0-10)
• PEP8 Violations - Number of style guideline violations

📊 Key Findings (Summary)

• BeautifulSoup4: 7,755 LOC, average CC: 3.40, total PEP8 violations: 656
• Requests: 11,248 LOC, average CC: 2.87, total PEP8 violations: 533
• High-complexity modules: dammit.py (BeautifulSoup4) and test_requests.py (Requests) identified as refactoring candidates

📚 Research Context

This work contributes to software engineering by:

• Providing empirical code quality assessment of widely-used Python libraries
• Demonstrating a reproducible methodology for static analysis
• Identifying specific modules that would benefit most from refactoring
• Offering a template for similar code quality studies

🤝 Contact

• Author: Bashir Adam
• Institution: Ostim Technical University

🙏 Acknowledgments

• The open-source communities behind Requests and BeautifulSoup4
• Developers of Radon, Pylint, and Flake8 static analysis tools
• Journal of Undergraduate Research International for considering this work