Dataset de Repositórios em Clean Architecture para Análise de Violações Arquiteturais

This dataset contains a curated collection of open-source software repositories following the Clean Architecture pattern, primarily implemented in Python with frameworks such as FastAPI and Flask. The dataset was created to support research on architectural violations, detection of architectural smells, and evaluation of structural metrics in software projects. It includes seven repositories selected to provide diversity in architectural design and project size. All repositories are included in their original form, without modifications, and are freely available under their respective open-source licenses. The dataset aims to provide a reproducible foundation for experiments involving: Analysis of architectural violations in Clean Architecture projects Evaluation of software metrics such as coupling and stability Testing and validation of automated architecture smell detection tools Research combining static analysis and AI-driven code inspection Contents: fastapi-clean-architecture python-clean-architecture clean-architecture cookiecutter-python-flask-clean-architecture rentomatic python-clean-architecture-example clean-architecture-python Each repository is documented in the included README.md, which provides authorship, source links, and usage guidance. Intended audience: Researchers, software engineers, and educators interested in software architecture, Clean Architecture, and AI-assisted code analysis.