DPy: Code Smells Detection Tool for Python

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 signifi...

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Bibliographic Details
Published in:Proceedings (IEEE/ACM International Conference on Mining Software Repositories. Online) pp. 826 - 830
Main Authors: Boloori, Aryan, Sharma, Tushar
Format: Conference Proceeding
Language:English
Published: IEEE 28.04.2025
Subjects:
Code smells
Codes
Computer architecture
Continuous integration
Data mining
Java
Measurement
Pipelines
Python
Repository mining
Software
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ISSN:2574-3864
Online Access:Get full text
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Summary: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]
ISSN:2574-3864
DOI:10.1109/MSR66628.2025.00119