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OSS Mentor A framework for improving developers contributions via deep reinforcement learning

2022-10-24 14:26:55
Jiakuan Fan, Haoyue Wang, Wei Wang, Ming Gao, Shengyu Zhao
arXiv_AI
       
Abstract

In open source project governance, there has been a lot of concern about how to measure developers' contributions. However, extremely sparse work has focused on enabling developers to improve their contributions, while it is significant and valuable. In this paper, we introduce a deep reinforcement learning framework named Open Source Software(OSS) Mentor, which can be trained from empirical knowledge and then adaptively help developers improve their contributions. Extensive experiments demonstrate that OSS Mentor significantly outperforms excellent experimental results. Moreover, it is the first time that the presented framework explores deep reinforcement learning techniques to manage open source software, which enables us to design a more robust framework to improve developers' contributions.

Abstract (translated)

URL

https://arxiv.org/abs/2210.13990

PDF

https://arxiv.org/pdf/2210.13990.pdf

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