Investigating Issues that Lead to Code Technical Debt in Machine Learning Systems

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Autores principales: Ximenes, Rodrigo, Santos Alves, Antonio Pedro, Escovedo, Tatiana, Spinola, Rodrigo, Kalinowsli, Marcos
Formato: Recurso digital
Publicado: Zenodo 2024
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author Ximenes, Rodrigo
Santos Alves, Antonio Pedro
Escovedo, Tatiana
Spinola, Rodrigo
Kalinowsli, Marcos
author_facet Ximenes, Rodrigo
Santos Alves, Antonio Pedro
Escovedo, Tatiana
Spinola, Rodrigo
Kalinowsli, Marcos
contents <p>This repository contains three main files produced for the paper 'Investigating Issues that Lead to Code Technical Debt in Machine Learning Systems.' We make available:</p> <ul> <li>A file containing the Miro Board produced (Miro Board - Investigating Issues that Lead to Code Technical Debt in Machine Learning Systems.pdf);</li> <li>A file containing Appendix A that complements the results from other ML life cycle stages (Appendix A - Assessing and Refining the List of Candidate Issues.pdf)</li> <li>A file containing Appendix B that presents a full table of each ML life cycle stage and its issues and descriptions (Appendix B - List of Issues Leading to Machine Learning Code Technical Debt.pdf)</li> </ul>
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publishDate 2024
publisher Zenodo
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spellingShingle Investigating Issues that Lead to Code Technical Debt in Machine Learning Systems
Ximenes, Rodrigo
Santos Alves, Antonio Pedro
Escovedo, Tatiana
Spinola, Rodrigo
Kalinowsli, Marcos
<p>This repository contains three main files produced for the paper 'Investigating Issues that Lead to Code Technical Debt in Machine Learning Systems.' We make available:</p> <ul> <li>A file containing the Miro Board produced (Miro Board - Investigating Issues that Lead to Code Technical Debt in Machine Learning Systems.pdf);</li> <li>A file containing Appendix A that complements the results from other ML life cycle stages (Appendix A - Assessing and Refining the List of Candidate Issues.pdf)</li> <li>A file containing Appendix B that presents a full table of each ML life cycle stage and its issues and descriptions (Appendix B - List of Issues Leading to Machine Learning Code Technical Debt.pdf)</li> </ul>
title Investigating Issues that Lead to Code Technical Debt in Machine Learning Systems
url https://doi.org/10.5281/zenodo.14173984