RDEL #60: How (and why) should teams try distributed pair programming?
This week we look at a summary of research papers covering the practice, benefits, and use cases for distributed pair programming.
Welcome back to Research-Driven Engineering Leadership. Each week, we pose an interesting topic in engineering leadership and apply the latest research in the field to drive to an answer.
As remote work reshapes global collaboration, distributed teams are using remote-friendly strategies to knowledge share and collaborate on development work. One common strategy is pair programming. This week we ask: how (and why) should teams try distributed pair programming?
The context
In today's rapidly evolving tech landscape, the rise of remote work has transformed how teams collaborate, especially in software development. Pair programming, a practice where two developers work together on a coding task, has long been praised for improving code quality and developer skills (we previously covered the pros/cons here). However, as more teams shift to remote work, Distributed Pair Programming (DPP) has emerged as an alternative that leverages the benefits of traditional pair programming while accommodating the geographical spread of team members.
DPP allows two developers to work on the same codebase from different locations, using collaboration tools for communication and screen sharing. In addition to improving code quality, DPP fosters problem-solving skills, reduces individual workload, and enhances the learning experience by encouraging teamwork and knowledge sharing. This approach is not without challenges, such as communication barriers and time zone differences, but it has the potential to significantly enhance remote team collaboration if implemented effectively.
The research
A systematic review was conducted to examine Distributed Pair Programming (DPP) and its effectiveness in both educational and professional environments. Researchers analyzed 23 studies published since 2010, focusing on how DPP impacted team learning and performance. Key factors such as individual characteristics, team environment, and technology use were explored.
Across the numerous studies reviewed, these were the top drivers that impacted the success of DPP:
Individual characteristics: Compatibility between pairs, including factors like skill level and prior experience, plays a major role in DPP's success. Studies showed that pairs with similar technical skills performed better and experienced fewer misunderstandings during collaboration.
Team design: Scripted role-switching (alternating between "driver" and "navigator") significantly improved engagement and task distribution among participants. Research found that structured role-switching reduced cognitive load by ensuring both members actively contributed throughout the session.
Technology: Teams using collaboration tools with integrated screen-sharing and communication features experienced smoother coordination and higher productivity.
Satisfaction: Programmers reported higher levels of satisfaction when they perceived their partner's skill level to be similar to their own.
Task complexity: Contrary to some expectations, increasing task complexity did not significantly reduce the effectiveness of DPP. Studies indicated that well-matched pairs were able to handle complex tasks with the same efficiency as simpler tasks, likely due to improved communication dynamics.
The application
This literature review highlighted that Distributed Pair Programming (DPP) can improve collaboration, satisfaction, and productivity when pairs are well-matched in skill level, role-switching is structured, and effective collaboration tools are used.
For engineering leaders considering using DPP as a tool in their engineering teams, consider the following steps:
Create compatible pairs: Match team members with similar or complementary skill levels to reduce friction and improve communication during coding sessions. Consider using a formal assessment of skills to pair developers more effectively.
Implement structured role-switching: Introduce a system where developers alternate between the "driver" and "navigator" roles during coding tasks. This ensures balanced participation and keeps both individuals actively engaged.
Leverage collaboration tools: Invest in robust collaboration tools with screen-sharing and communication features, such as IDEs with integrated plugins, to facilitate smooth, real-time interactions between distributed team members.
With this, teams can benefit from the collaborative learning and productivity improvements that pair programming offers, even from afar.
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Wishing you a great week, and a Happy Research Monday!
Lizzie