Code smells violate best practices in software development that make code difficult to understand and maintain. Code smell detection tools help practitioners detect maintainability issues and enable researchers to conduct repository mining and empirical research involving code smells. Though significant efforts have been made to effectively detect smells in code, majority of the available tools target programming languages such as Java. Despite the most popular language, a code smell detection tool that can identify not only implementation-level code smells but also support detection of smells at the design granularity is lacking. This paper presents DPy, a code smell detection tool for Python. The tool currently supports eight design smells, eleven implementation smells, and various code quality metrics for Python code. Our replication package includes the tool, instructions to use it, all the validation data and scripts [1].
Julien Malka LTCI, Télécom Paris, Institut Polytechnique de Paris, France, Stefano Zacchiroli Télécom Paris, Polytechnic Institute of Paris, Théo Zimmermann Télécom Paris, Polytechnic Institute of Paris
