Research

I have been researching large-scale software engineering since 2013, from multiple perspectives and always through a multi-disciplinary lens. Starting out with how to implement effective continuous integration, continuous delivery and continuous deployment in large organizations, through the ability to dynamically compose high-performing teams and match skills to needs in major development projects, to the application of Artificial Intelligence to augment software development.

Starting out as a PhD student, the form of my research has changed over the years, from individual research to multi-author collaborations to supervision of PhD students. Throughout, the central theme remains: What does excellence in development of large software system look like, and how can we achieve it?

Artificial Intelligence in software development

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Sample papers:

• UML Sequence Diagram Generation: A Multi-Model, Multi-Domain Evaluation

Teaming

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Sample papers:

• Mob programming: From avant-garde experimentation to established practice
• The dynamic versus the stable team: The unspoken question in large‐scale agile development

Continuous Practices

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Sample papers:

• Modeling continuous integration practice differences in industry software development
• Continuous Practices and DevOps: Beyond the buzz, what does it all mean?
• Achieving traceability in large scale continuous integration and delivery: Deployment, usage and validation of the Eiffel framework

Daniel Ståhl on Google Scholar