`dslinter` is a pylint plugin for linting data science and machine learning code. We plan to support the following Python libraries: TensorFlow, PyTorch, Scikit-Learn, Pandas and NumPy.
Source code for "An Empirical Study of Code Smells in Transformer-based Code Generation Techniques".
Simpler Transfer Learning (Using "Bellwethers"). ARXIV link: https://arxiv.org/abs/1703.06218
A Machine-learning Based Ensemble Method for Anti-patterns Detection
A Python toolkit to help developers write professional-grade, maintainable, and clean code following clean code principles.
A tool to measure and compare the energy consumption of code variants.
Example projects illustrating Code Smells in order to apply Refactoring techniques.
Tips for a clean code and SOLID architecture
MIRROR of https://codeberg.org/catseye/yucca : A dialect-agnostic static analyzer for 8-bit BASIC programs
Context-aware code smell detection platform integrating a DSL interpreter, metric analysis, and asynchronous event-driven processing.
🧀 The command line tool that detects code smells for refactoring
CIT 411 Module 2 assignment using AI to review Python code smells, data-structure choices, loop patterns, and refactoring decisions.
A Python AST visualizer & static analyzer.
A systematic literature review on the code smells datasets and validation mechanisms
This repository is intended to present the refactoring of the payroll project.
A software-engineering code-quality tutor built as a four-agent pipeline: deterministic analysis (radon, AST, code-smell detection) plus Claude-generated explanations and PDF reports, with a live view of the agents at work.
"A static analysis tool designed to detect, quantify, and track technical debt in software projects. Provides automated code metrics, architectural smell detection, and actionable insights to improve maintainability and reduce refactoring costs."
CodeSmellHunter 🕵️♂️ is a static Python code analysis tool 🔍 that uses AST-based inspection 🌳 to detect common code smells, helping developers reduce maintainability risks
A study on the correlation between GitHub Stars and Code Quality.
Experimental code for the Smelligent study on detecting inline code comment smells.
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