The proposed workshop is designed to address the needs of tech leads and engineering managers, thus the content and exercises will focus on the effective utilization of analyzed data from git repositories to optimize software development processes and enhance team dynamics. An AI-generated code topic will be briefly introduced as a teaser, while the focus remains on practical insights and techniques (based on the fundamentals of software development).
By the end of the workshop, participants will be able to apply the insights and techniques learned to their own projects and teams, and continuously monitor and learn from their git repositories for ongoing improvement.
What will you Learn:
Equip tech leads and engineering managers with the knowledge and skills needed to effectively utilize analysed data extracted from git repositories for optimising software development processes, improving team dynamics, and driving continuous improvement within their teams.
Level: Beginner / intermediate
TAGs: #git #repository-mining #code-quality #architecture #team-dynamics
Target audience: Tech leads, Engineering managers, Developers who want to want to improve their skills in a data-driven way.
Prerequisites on Audience:
- Own laptop.
- Git, Python, Pip installed.
- Experience on working with Python.
- Knowledge on basic data analysis concepts
- Software developed during the workshop.
- The presentation presented during the workshop.
Introduction (10 minutes)
- Brief overview of the workshop and its objectives
- Importance of utilizing data from git repositories for tech leads and engineering managers
Leveraging Commit Data, Component Activity Distribution, and Code Volume Insights (15 minutes)
- Presentation on interpreting commit data, component activity distribution, and code volume and quality metrics
- Hands-on exercise: Analysis of an open-source project’s commit data
Harnessing Author Collaboration, Knowledge Distribution, and Team Dynamics Insights (15 minutes)
- Presentation on collaboration patterns, knowledge distribution, and team dynamics
- Hands-on exercise: Analysis of team dynamics data
A Glimpse into AI’s Impact (5 minutes)
- A brief teaser on AI-generated code’s impact
Conclusion (5 minutes)
- Recap of key learnings
- Calls to action: How to apply these insights