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A master's thesis from Aalborg University
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Predictive Insights: Machine Learning and FOSS Project Sustainability

Authors

; ;

Term

4. Term

Education

Digitalisation and Application Development, MSc

Publication year

2024

Submitted on

Pages

58

Abstract

This thesis explores the use of machine learning models to predict the graduation and retirement of Free and Open Source Software (FOSS) projects within the Apache Software Foundation Incubator (ASFI) using sustainability metrics. By training models with established sustainability indicators, we demonstrated predictive potential for ASFI projects. Key metrics impacting predictions included community size, development activity, growth, communication frequency, and turnover. Our findings highlight a link between sustainability and ASFI graduation and retirement, advocating for a combined qualitative and quantitative approach to improve our understanding and its prediction accuracy.

Keywords

FOSS ; Sustainabiilty ; Apache ; ASFI ; Machine-Learning ; ML ; Prediction

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