4 papers · 1 filter
CodeHealth Predicts the Token Cost of Agentic Code Review: A Pre-Registered Study of 465 Agent-Authored Pull Requests
Lo Gullstrand Heander, Markus Borg, Emma Söderberg +1
Context: Organizations increasingly delegate code review to multi-agent large language model (LLM) pipelines billed per token. Low code quality raises human maintenance effort, but…
Orchestrating AI-Assisted Code Remediation: Socio-Technical Bottlenecks in a Large Industrial Repository
Andreas Bexell, Lo Gullstrand Heander, Emma söderberg
Background: Code degradation in large, long-lived codebases is costly to remediate through manual refactoring and opportunistic clean-ups. LLM-based coding assistants can perform m…
Helpful but Fallible: Developer Experiences of AI Tools Under a Coordinated Industrial Roll-out
Andreas Bexell, Rushali Gupta, Lo Gullstrand Heander +5
AI-enabled software development tools (AI-devtools) are being industrially adopted under strong expectations of productivity gains, yet developers' experiences of such roll-outs ar…
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…