We present Pyra, a static analysis tool that aims at detecting code smells in data science workflows. Our goal is to capture potential issues, focusing on misleading visualizations, challenges for reproducibility, as well as misleading, unreliable or unexpected results. Link to the demo: https://www.youtube.com/watch?v=D-AsyuhsTyo GitHub repository: https://github.com/spangea/Pyra.

Introducing Pyra: A High-Level Linter for Data Science Software

Dolcetti G.;Arceri V.;Urban C.;Cortesi A.
2025-01-01

Abstract

We present Pyra, a static analysis tool that aims at detecting code smells in data science workflows. Our goal is to capture potential issues, focusing on misleading visualizations, challenges for reproducibility, as well as misleading, unreliable or unexpected results. Link to the demo: https://www.youtube.com/watch?v=D-AsyuhsTyo GitHub repository: https://github.com/spangea/Pyra.
2025
Lecture Notes in Computer Science
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10278/5105790
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