AI-supported Engineering

Vision

All Software Center companies have efficient product development, release and deployment processes.

Mission

We help the companies to design and develop modern measurement methods and tools by utilizing state-of-the-art analytics, AI and machine learning. We use Action Research to increase the impact and adoption of the results (Action Research in Software Engineering), i.e., we work on-site of the companies. Over the course of ten years of our collaboration, our theme has resulted in over 50 models and tools. We have also published over 200 papers and books that disseminate the results to the public domain. Examples of the metrics designed and introduced to the companies:

Projects

Theme 3 Leader: Miroslaw Staron
Miroslaw Staron

Professor, Software Engineering division, Department of Computer Science and Engineering, University of Gothenburg

More information

Miroslaw.Staron@cse.gu.se

Phone: +46 31 772 10 81

RSS Metrics Blog
  • Levels of automated code development… July 10, 2026
    Image generated by Gemini based on this blow post https://www.mdpi.com/2076-3417/16/10/4788 The practical meaning of automated code generation is shifting rapidly. What was recently categorized as simple “autocomplete” has expanded into complex workflows involving multi-file modifications, test execution, and repository navigation. However, as Zhenhan Chen et al. argue in a recently published article in Applied Sciences, […]
    Miroslaw Staron
  • What are you talking about – one agent asked another… July 3, 2026
    Image taken directly from the paper https://arxiv.org/pdf/2605.24138 The Software Engineering (SE) landscape is shifting from LLM-assisted workflows, like copilots, toward Autonomous SE, where multiple specialized AI agents cooperate without a human in the loop. The premise is exciting: a ‘Designer’ agent creates the plan, and a ‘Programmer’ agent implements it. Yet, simply letting agents talk […]
    Miroslaw Staron
  • Can we force LLMs to generate the code we really want? June 18, 2026
    Experiment design – from the paper Large Language Models (LLMs) are revolutionary for programming productivity, producing functional code snippets in seconds. However, as software engineers, my co-authors and I know that “functional” is not the same as “well-designed.” LLMs are generally “bottom-up” thinkers; they excel at local syntax but struggle to adhere to higher-level architectural […]
    Miroslaw Staron
  • My prompt is better than your prompt – how to optimize your prompts in the age of agentic AI June 12, 2026
    Image generated by Gemini based on the content of this post https://arxiv.org/pdf/2605.19102 Getting Large Language Models (LLMs) to write functional code often feels like casting spells; a slight misphrasing in your prompt can result in a buggy output. This is even more important now that we have agents which work for days on our tasks. […]
    Miroslaw Staron
  • 15 years of Software Center – A Look in the Mirror and over the Front Windshield June 10, 2026
    Image source: Gemini, based on the summary of this blog post. When I write this post, I’m sitting at a reporting workshop of Software Center, at Axis Communications in Lund. Jan has reminded us that we’ve been going on for 15 years. That’s most of my academic career and a lot of my life. Although […]
    Miroslaw Staron
  • Junior Architects with Shaky Logic: Testing AI’s Real-World Coding Skills – article review June 5, 2026
    Image generated by Gemini based on the blog post content https://arxiv.org/pdf/2604.23340 We have all seen Large Language Models (LLMs) write impressive snippets of code or debug a tricky function. AI coding editors like GitHub Copilot are increasingly adopted, with studies suggesting that up to 88% of developers report increased productivity. But accelerations in development come […]
    Miroslaw Staron
  • The Synthetic Engineer: Measuring the Real Impact of AI on Software Delivery May 18, 2026
    https://miroslawstaron.github.io/hallucinations.html#/5 The shift from manual coding to AI-augmented orchestration is no longer a future – it is a reality. Software engineers adopt AI increasingly often and increasingly deep. However, as organizations pour investment into Generative AI tools, a critical question remains: How do we measure the true return on investment? I asked Gemini to analyze […]
    Miroslaw Staron
  • From Gutenberg to Google and on to AI May 11, 2026
    Link to the book I’m often asked what invention I think is the biggest in human history. I do not have one that is the biggest, but I have a short list: 1) Writing – once we learned how to codify knowledge, our progress accelerated tremendously 2) Computing – once we learned how to make […]
    Miroslaw Staron
  • VECS 2026 — The Era of the AI-Defined Vehicle May 5, 2026
    The VECS 2026 conference in Gothenburg has made one thing clear: the transition to Software-Defined Vehicles (SDVs) is no longer a future prediction—it is accelerating rapidly toward total market dominance. I’ve been to both days and it seems that the best time for software is NOW! For a nerdy software engineer like me, this conference […]
    Miroslaw Staron
  • Can You Trust GPT with Your System Design? Testing AI’s Architectural IQ March 30, 2026
    Image by Vinson Tan ( 楊 祖 武 ) from Pixabay https://ieeexplore.ieee.org/document/10978937 We’ve all seen Large Language Models (LLMs) write impressive snippets of code or debug a tricky function. But can an AI actually understand the soul of a system? Can it explain the “why” behind a complex architectural decision? The paper, “Do Large Language Models Contain Software […]
    Miroslaw Staron