4 papers · 1 filter
Code Health in LLM-Based Test Generation: Effectiveness and Token Efficiency
Freya Wirdemann, Markus Borg, Nadim Hagatulah +1
Coding agents powered by Large Language Models (LLMs) are now prominent in software engineering. Previous work has shown that AI tools perform better on high-quality source code th…
Technical Debt Friction for Maintenance Prioritization: An Industrial Multi-Case Study
Simeon Tverdal, Phu Nguyen, Arda Goknil +3
Software-intensive organizations need effective ways to identify where maintenance and refactoring efforts will yield the greatest practical benefit. Although software analytics su…
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…