Patterns of Developer Adoption of LLM-Generated Code Refactoring Suggestions

David Schön, Faiza Amjad, Tehreem Asif, Ranim Khojah, Mazen Mohamad, Francisco Gomes De Oliveira Neto, Philipp Leitner
January, 2026
DOI

Abstract

This paper studies how developers adopt code refactoring suggestions generated by large language models, identifying patterns in acceptance and rejection behavior.

Type
Conference paper
Publication
International Conference on Predictive Models and Data Analytics in Software Engineering (PROMISE 2026)
Mazen Mohamad
Mazen Mohamad
Researcher at RISE Research Institutes of Sweden

My research interests include Safety & Cybersecurity of Autonomous Systems, AI4Security, and Security4AI.