MLSToolbox Code Generator: A tool for generating quality ML pipelines for ML systems
Machine learning-based systems play a critical and increasingly pervasive role in various aspects of daily life. Despite the growing recognition of the importance of producing high-quality code for Machine Learning (ML) pipelines to ensure proper evolution, maintenance, and reusability, actionable g...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2025 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/446607 |
| Acceso en línea: | https://hdl.handle.net/2117/446607 https://dx.doi.org/10.1016/j.softx.2025.102379 |
| Access Level: | acceso abierto |
| Palabra clave: | Machine learning pipeline Software quality Low-code Code generation Python Àrees temàtiques de la UPC::Informàtica::Enginyeria del software Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Aprenentatge automàtic |
| Sumario: | Machine learning-based systems play a critical and increasingly pervasive role in various aspects of daily life. Despite the growing recognition of the importance of producing high-quality code for Machine Learning (ML) pipelines to ensure proper evolution, maintenance, and reusability, actionable guidance at the design and implementation levels remains scarce. This paper introduces MLSToolbox Code Generator, a low-code tool designed to support data scientists in graphically defining ML pipelines and generating their corresponding Python code. The tool leverages core Software Engineering design principles to promote high-quality Python code. Through a detailed example, we demonstrate how data scientists can use the tool. The flexible and extensible architecture of the tool enables data scientists to customize ML pipeline generation to meet domain-specific requirements, fostering greater efficiency and adaptability in ML workflows. |
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