From Generic to Personalized: Exploring Persona-Aware Code Review Explanations
2026-07-09 • Software Engineering
Software Engineering
AI summaryⓘ
The authors studied how developers understand comments during code reviews and found people interpret feedback differently based on their experience, role, and problem-solving style. They tested personalized review comments designed to match these styles and found people preferred detailed explanations that help them learn and assess risks rather than brief comments. Their work suggests that code review tools could be better if they adapt feedback to each developer’s way of thinking while keeping it clear and trustworthy. This study is part of ongoing research into making AI-assisted code reviews more human-centered and inclusive.
code reviewsoftware qualitycollaborationpersonasproblem-solving stylesuser studyexplanatory depthAI-assisted feedbackpersonalizationdeveloper experience
Authors
Shamse Tasnim Cynthia, Ratnadira Widyasari, Banani Roy, Italo Santos, David Lo
Abstract
Code review is essential for ensuring software quality and supporting collaboration, yet prior work shows that developers can interpret code review comments differently. These differences can hinder effective communication, particularly in collaborative settings. To address this challenge, we explore the potential of personified code review explanations. We report initial findings from an ongoing mixed-methods user study in which developers evaluated persona-aligned review comments across multiple code snippets. Our results suggest that preferences for explanation styles vary across problem-solving styles, experience levels, and roles. Across problem-solving style profiles, developers valued explanatory depth, learning support, practical suggestions, and risk awareness over conciseness, highlighting the need to balance personalization with clarity and trust. Based on these findings, we outline a vision for inclusive, human-centered AI-assisted code review systems that adapt feedback to developers' problem-solving preferences.