OSS Mentor A framework for improving developers contributions via deep reinforcement learning
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Abstract (arXiv)
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.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 2 of its 20 references that are in the map. First posted on arXiv 24 Oct 2022.
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References · 2
- 2015Continuous control with deep reinforcement learningcited by 3,407
- 2016Generative Adversarial Imitation Learningcited by 1,597
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