5 papers
Trust-Calibrated Code Review: A Participatory Design Study of Review Workflows for LLM-Generated Multi-File Changes
Lo Gullstrand Heander, Agnia Sergeyuk, Ilya Zakharov +2
Background: Developers increasingly review multi-file code changes generated by LLM-based agents, yet no validated end-to-end workflow or IDE tooling design exists for this scenari…
Echoes of AI: Investigating the Downstream Effects of AI Assistants on Software Maintainability
Markus Borg, Dave Hewett, Nadim Hagatulah +5
[Context] AI assistants, like GitHub Copilot and Cursor, are transforming software engineering. While several studies highlight productivity improvements, their impact on maintaina…
Code for Machines, Not Just Humans: Quantifying AI-Friendliness with Code Health Metrics
Markus Borg, Nadim Hagatulah, Adam Tornhill +1
We are entering a hybrid era in which human developers and AI coding agents work in the same codebases. While industry practice has long optimized code for human comprehension, it…
Code Review as Decision-Making -- Building a Cognitive Model from the Questions Asked During Code Review
Lo Gullstrand Heander, Emma Söderberg, Christofer Rydenfält
Code review is a well-established and valued practice in the software engineering community contributing to both code quality and interpersonal benefits. However, there are challen…
ACE: Automated Technical Debt Remediation with Validated Large Language Model Refactorings
Adam Tornhill, Markus Borg, Nadim Hagatulah +1
The remarkable advances in AI and Large Language Models (LLMs) have enabled machines to write code, accelerating the growth of software systems. However, the bottleneck in software…