Detecting the functional interaction structure of software development teams
Christian Zingg1, Alexander von Gernler2, Carsten Arzig2
1Chair of Systems Design, ETH Zurich, Zurich, Switzerland.
Plos One
|October 24, 2024
Summary
This study introduces a data-driven method to map software team interaction structures using daily work traces. It helps teams understand and improve knowledge diffusion and overall performance.
Area of Science:
- Software Engineering
- Team Dynamics
- Organizational Behavior
Background:
- Understanding team functional interaction structures is crucial for optimizing software development.
- Existing methods often lack data-driven insights into real-time team interactions.
- Identifying interaction patterns can reveal opportunities for improved collaboration and knowledge sharing.
Purpose of the Study:
- To present a novel data-driven approach for detecting the functional interaction structure of software development teams.
- To quantify and evaluate team interaction preferences based on daily work traces.
- To provide insights for improving team performance and knowledge diffusion.
Main Methods:
- Utilizing traces from development platforms to capture member activities.
- Accounting for varying activity levels among team members.
- Employing a block-constrained configuration model to compute role-based interaction preferences.
Main Results:
- Successfully extracted the functional interaction structure of a software product team.
- Validated the accuracy of the detected structure through member interviews.
- Demonstrated the ability to compare team structures against benchmarks to identify improvement areas.
Conclusions:
- The proposed approach offers an efficient and real-time method for analyzing and managing team interaction structures.
- Quantifying functional interactions aids in understanding team dynamics and enhancing performance.
- This technique can pinpoint specific areas for knowledge diffusion improvement within development teams.
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