Registered user since Wed 24 Jan 2018
Dr. Markus Borg is a senior researcher at the intersection of software engineering and applied artificial intelligence. He is a principal researcher at CodeScene and an adjunct lecturer at Lund University. Markus serves on the editorial board of Empirical Software Engineering and is a department editor for IEEE Software.
My goal is to support the successful engineering of software and data-intensive systems. While my software engineering interests are broad, most of my work relates to machine learning, i.e., my research interests span both software engineering intelligence (AI4SE) and AI engineering (SE4AI).
In AI4SE, I seek to tap into the collected wisdom of historical project data to facilitate machine learning for actionable decision support. My most impactful contributions have been related to defect management, for example, bug assignment and change impact analysis. Core ideas are currently operationalized in internal tools at Ericsson.
In SE4AI, I investigate quality assurance of systems that embed machine learning components. I am particularly interested in development mandated by automotive safety standards and the EU AI Act. Our research studies involve requirements engineering, MLOps pipelines, software testing in automotive simulators, and our open-source demonstrator SMIRK.
Contributions
2025
Requirements Engineering: Foundation for Software Quality (REFSQ)
2024
PROFES
ICSME
- Author of Ghost Echoes Revealed: Benchmarking Maintainability Metrics and Machine Learning Predictions Against Human Assessments within the Industry Track-track
- Author of Does Co-Development with AI Assistants Lead to More Maintainable Code? A Registered Report within the Registered Reports Track-track
- Committee Member in Industry Track - Program Committee within the Industry Track-track
Requirements Engineering
ICST
International Conference on Technical Debt
2023
Requirements Engineering
- Committee Member in Program Committee within the Research Papers-track
- Panelist of Panel: Requirements Engineering and Large Language Models: Best of Friends or Worst of Enemies? within the Research Papers-track
- Panelist of PhD advisors at your disposal within the Doctoral Symposium-track
- Author of Ergo, SMIRK is Safe: A Safety Case for a Machine Learning Component in a Pedestrian Automatic Emergency Brake System within the Journal-First-track