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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