Integrating Pair Programming as a Work Practice

2025-06-24

AI Summary

Empirical evidence on pair programming (PP) adoption and sustained practice remains inconsistent, hindering its transition from ad hoc experimentation to routine engineering practice. Method: Adopting a single-case exploratory design, this study conducts two rounds of cross-role in-depth interviews with practitioners, followed by thematic analysis to identify four critical dimensions: cognitive alignment, resource support, team climate, and task suitability. Contribution/Results: Findings reveal that individuals’ perceived tangible benefits constitute the primary driver for sustained PP engagement; effective implementation necessitates moving beyond prescriptive, one-size-fits-all approaches toward a dynamic, collective-learning–driven adaptation mechanism. Accordingly, we propose the Adaptive Pair Programming Practice Model, which emphasizes context-sensitive, team-autonomous optimization of pairing frequency, role rotation, and task–pairing alignment. This model provides a theoretically grounded, actionable framework for institutionalizing PP as a scalable, sustainable software engineering practice.

Technology Category

• Cognitive Modeling & Cognitive Systems: Adaptive Behavior
• Application Domains: Software Engineering
• Reasoning under Uncertainty: Probabilistic Programming

Application Category

• User Modeling, Personalization and Recommendation: Practical large-scale studies of user experience
• Security and Privacy: Large-scale security measurements
• Search and Retrieval-Augmented AI: Efficiency and scalability of Web search engines

Abstract

Context: Pair programming (PP) is more relevant than ever. As modern systems grow in complexity, knowledge sharing and collaboration across teams have become essential. However, despite well-documented benefits of PP, its adoption remains inconsistent across software teams. Objective: This study aims to understand the factors that facilitate or hinder team members' adoption as well as lasting engagement in PP. Method: We have conducted an exploratory single-case study in a mature agile company in Norway. We collected data through two rounds of interviews with team members in different roles and performed a thematic analysis of the interviews. Results: Our key finding is that multiple factors, related to the perceptions of how PP contributes to daily work, efforts associated with engaging in PP sessions, company and team attitudes, resources, infrastructure, and task characteristics, affect PP engagement. Conclusion: Long-term engagement in PP requires expected benefits with the practice being confirmed in firsthand experiences. Adapting the practice to each unique team, with insights drawn from collective learning, is also beneficial. Our findings will be beneficial for software practitioners seeking to make PP an integrated part of their team's workflow.

Problem

• Understand factors affecting pair programming adoption in teams
• Explore barriers and facilitators for lasting pair programming engagement
• Study how team dynamics and resources influence pair programming use

Innovation

• Exploratory single-case study in agile company
• Thematic analysis of multi-role interviews
• Adapting pair programming to team context