OSS Mentor A framework for improving developers contributions via deep
reinforcement learning
- URL: http://arxiv.org/abs/2210.13990v1
- Date: Mon, 24 Oct 2022 14:26:55 GMT
- Title: OSS Mentor A framework for improving developers contributions via deep
reinforcement learning
- Authors: Jiakuan Fan and Haoyue Wang and Wei Wang and Ming Gao and Shengyu Zhao
- Abstract summary: We introduce a deep reinforcement learning framework named Open Source Software(OSS) Mentor.
OSS Mentor can be trained from empirical knowledge and then adaptively help developers improve their contributions.
It is the first time that the presented framework explores deep reinforcement learning techniques to manage open source software.
- Score: 14.828595288939749
- License: http://creativecommons.org/licenses/by-nc-nd/4.0/
- 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.
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