`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
Catches the bugs linters miss — logic-first code review via execution tracing. Finds behavioral bugs, type-contract breaches & semantic mismatches across 9 risk categories. Six skills: review, explain, diff, locate, health-check, and autonomous audit-and-fix pipeline. Claude Code · Codex CLI · Gemini CLI.
🧀 The command line tool that detects code smells for refactoring
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.
This repository is intended to present the refactoring of the payroll project.
A Python AST visualizer & static analyzer.
A systematic literature review on the code smells datasets and validation mechanisms
A study on the correlation between GitHub Stars and Code Quality.
CodeSmellHunter 🕵️♂️ is a static Python code analysis tool 🔍 that uses AST-based inspection 🌳 to detect common code smells, helping developers reduce maintainability risks
Python code smell detector & refactoring guide — 82 patterns, 55 AST checks, zero dependencies. Works as Agent Skills plugin, PyPI package, GitHub Action, or pre-commit hook.
This repository is a curated collection of code files intentionally designed for refactoring tasks. It serves as a dataset for evaluating and improving automated code refactoring techniques, including scripts, tools, and AI-based approaches.
Visualize and analyze Python code as interactive AST graphs to identify complexity, performance issues, and code smells with clear refactoring guidance.
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