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

TL;DR

This paper introduces OSS Mentor, a deep reinforcement learning framework designed to help open source developers improve their contributions, demonstrating significant performance improvements and pioneering the application of deep RL in open source management.

Contribution

It presents the first deep reinforcement learning framework for managing open source contributions, trained on empirical knowledge to enhance developer performance.

Findings

OSS Mentor significantly outperforms existing methods

The framework effectively adapts to different developer needs

First application of deep RL in open source software management

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.