Revolutionizing Newcomers' Onboarding Process in OSS Communities: The Future AI Mentor (2505.04277v1)

Abstract: Onboarding newcomers is vital for the sustainability of open-source software (OSS) projects. To lower barriers and increase engagement, OSS projects have dedicated experts who provide guidance for newcomers. However, timely responses are often hindered by experts' busy schedules. The recent rapid advancements of AI in software engineering have brought opportunities to leverage AI as a substitute for expert mentoring. However, the potential role of AI as a comprehensive mentor throughout the entire onboarding process remains unexplored. To identify design strategies of this AI mentor'', we applied Design Fiction as a participatory method with 19 OSS newcomers. We investigated their current onboarding experience and elicited 32 design strategies for future AI mentor. Participants envisioned AI mentor being integrated into OSS platforms like GitHub, where it could offer assistance to newcomers, such asrecommending projects based on personalized requirements'' and assessing and categorizing project issues by difficulty''. We also collected participants' perceptions of a prototype, namedOSSerCopilot'', that implemented the envisioned strategies. They found the interface useful and user-friendly, showing a willingness to use it in the future, which suggests the design strategies are effective. Finally, in order to identify the gaps between our design strategies and current research, we conducted a comprehensive literature review, evaluating the extent of existing research support for this concept. We find that research is relatively scarce in certain areas where newcomers highly anticipate AI mentor assistance, such as ``discovering an interested project''. Our study has the potential to revolutionize the current newcomer-expert mentorship and provides valuable insights for researchers and tool designers aiming to develop and enhance AI mentor systems.

Revolutionizing Newcomers' Onboarding Process in OSS Communities: The Future AI Mentor

The paper "Revolutionizing Newcomers' Onboarding Process in OSS Communities: The Future AI Mentor" by Xin Tan et al. investigates the potential of leveraging AI to support the onboarding process of newcomers in Open Source Software (OSS) communities. The authors address a critical challenge faced by OSS communities: the efficient integration and retention of new contributors. Given the high turnover rates in these communities, the continuous influx of newcomers is essential for sustaining and evolving OSS projects. However, the initial onboarding process presents multiple barriers for newcomers, often resulting in their premature disengagement.

Current Challenges in Newcomer Onboarding

The paper begins by outlining the traditional methods employed to onboard newcomers, such as comprehensive readme files, guideline documents, and dedicated labels like "good first issues" (GFIs) on project repositories. Despite these measures, newcomers often face difficulties stemming from a lack of clarity in guidelines, outdated or overwhelming information, and a misalignment between labeled tasks and their skill levels.

The authors identify several critical steps in the onboarding process that pose significant challenges, including:

• Discovering a project of interest amid millions of repositories.
• Understanding the project’s structure and guidelines.
• Identifying suitable tasks.
• Analyzing issues and coding solutions.

Many newcomers resort to using AI for limited tasks like code generation or searching for project information, but these tools aren’t specifically designed for comprehensive onboarding support.

AI Mentor Design Strategies

The core contribution of the paper is the derivation of 32 design strategies for an AI mentor, curated through participatory design fiction with newcomers. These strategies are aimed at facilitating different phases of the onboarding process. Key strategies include:

• Personalized project recommendations based on newcomers' interest and skill profiles.
• Comprehensive support in understanding and deploying project guidelines, with AI-assisted summaries and Q&A systems.
• Enhanced navigation tools for grasping the project's code structure.
• More accurate task recommendations and difficulty assessments.

These strategies prioritize overcoming the three most challenging steps: discovering a project, understanding project structure, and identifying tasks, which are prominently highlighted as areas where AI mentorship is desired.

Implementation and Validation

The authors developed a prototype named "OSSerCopilot" to validate their design strategies. Integrated with GitHub, the most representative OSS development platform, the prototype demonstrated a practical implementation of the proposed AI mentor features. Feedback from 19 participants indicated high satisfaction with the prototype, emphasizing its usefulness and ease of use. The Technology Acceptance Model (TAM) survey further confirmed participants' positive perceptions, with most willing to utilize the tool in the future.

Implications and Future Research

The paper highlights several implications for OSS communities, tool designers, and researchers:

1. Practical Implication: For OSS maintainers, it's suggested to refine existing onboarding tools, aligning them more closely with AI-assisted recommendations to reduce cognitive load and enhance newcomer integration.
2. Theoretical Implication: For researchers, the gap identified in existing literature, particularly the sparse exploration of AI in the initial onboarding phases like project discovery and understanding guidelines, invites further investigation.
3. Future AI Developments: The paper provides a roadmap for future developments in AI-driven solutions, suggesting a focus on full-cycle onboarding support rather than isolated task assistance.

In conclusion, this paper provides a compelling argument and methodology for reimagining OSS newcomer onboarding with an advanced, AI-driven mentor system. By addressing significant research gaps and offering actionable design strategies, it sets the stage for future innovations in AI-enhanced onboarding processes that could transform OSS communities' ability to retain valuable new contributors.