A Case Study of Onboarding in Software Teams: Tasks and Strategies
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Abstract (arXiv)
Developers frequently move into new teams or environments across software companies. Their onboarding experience is correlated with productivity, job satisfaction, and other short-term and long-term outcomes. The majority of the onboarding process comprises engineering tasks such as fixing bugs or implementing small features. Nevertheless, we do not have a systematic view of how tasks influence onboarding. In this paper, we present a case study of Microsoft, where we interviewed 32 developers moving into a new team and 15 engineering managers onboarding a new developer into their team -- to understand and characterize developers' onboarding experience and expectations in relation to the tasks performed by them while onboarding. We present how tasks interact with new developers through three representative themes: learning, confidence building, and socialization. We also discuss three onboarding strategies as inferred from the interviews that managers commonly use unknowingly, and discuss their pros and cons and offer situational recommendations. Furthermore, we triangulate our interview findings with a developer survey (N=189) and a manager survey (N=37) and find that survey results suggest that our findings are representative and our recommendations are actionable. Practitioners could use our findings to improve their onboarding processes, while researchers could find new research directions from this study to advance the understanding of developer onboarding. Our research instruments and anonymous data are available at urlhttps://zenodo.org/record/4455937#.YCOQCs0lFd
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 8 Mar 2021.
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Citing papers per year: 2025: 2; 2026: 2.
4 papers.
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- 2026Knowledge Activation: AI Skills as the Institutional Knowledge Primitive for Agentic Software Development16 Mar 2026
- 2025CodeWatcher: IDE Telemetry Data Extraction Tool for Understanding Coding Interactions with LLMs13 Oct 2025
- 2025A Multi-agent Onboarding Assistant based on Large Language Models, Retrieval Augmented Generation, and Chain-of-Thought30 Mar 2025