March 15, 2024, 4:42 a.m. | Jo\~ao Helis Bernardo, Daniel Alencar da Costa, S\'ergio Queiroz de Medeiros, Uir\'a Kulesza

cs.LG updates on arXiv.org arxiv.org

arXiv:2403.09547v1 Announce Type: cross
Abstract: Continuous Integration (CI) is a well-established practice in traditional software development, but its nuances in the domain of Machine Learning (ML) projects remain relatively unexplored. Given the distinctive nature of ML development, understanding how CI practices are adopted in this context is crucial for tailoring effective approaches. In this study, we conduct a comprehensive analysis of 185 open-source projects on GitHub (93 ML and 92 non-ML projects). Our investigation comprises both quantitative and qualitative dimensions, …

abstract arxiv continuous cs.lg cs.se development domain github integration machine machine learning machine learning projects ml development nature practice practices projects software software development study type understanding

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