[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-82133-en":3,"doc-seo-82133-105":29,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":13,"seo_description":14,"update_tm":27,"read_time":28},82133,1099514067438,"River Wang","https://ap-avatar.wpscdn.com/avatar/100002539ee87300030?x-image-process=image/resize,m_fixed,w_180,h_180&k=1780474512215547542",8,"Research & Report","From Generic to Personalized: Exploring Persona-Aware Code Review Explanations","Code review is essential for software quality and team collaboration, yet developers may interpret review comments differently, reducing communication effectiveness. The study investigates personified, persona-aware code review explanations through an ongoing mixed-methods user study where developers evaluated persona-aligned comments across multiple code snippets. Findings indicate that explanation preferences vary by problem-solving style, experience level, and role, with a stronger value placed on depth, learning support, practical suggestions, and risk awareness. The work proposes inclusive, human-centered AI systems that adapt feedback to individual preferences and build trust.","From Generic to Personalized: Exploring Persona-Aware Code  \nReview Explanations  \nShamse Tasnim Cynthia♦ , Ratnadira Widyasari♣ , Banani Roy♦ , Italo Santos♠ , and David Lo♣  \n♦University of Saskatchewan, Canada ♣ Singapore Management University, Singapore  \n♠University of Hawai’i, USA  \n{shamse.cynthia, [banani.roy}@usask.ca](banani.roy}@usask.ca), {ratnadiraw.2020, [davidlo}@smu.edu.sg](davidlo}@smu.edu.sg), [isantos3@hawaii.edu](isantos3@hawaii.edu)  \narXiv :2607 .08990v 1 [ cs . SE] 9 Jul 2026  \nAbstract  \nCode 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.  \nKeywords  \ncode review, persona-aware, GenderMag, problem-solving styles  \nACM Reference Format:  \nShamseTasnim Cynthia♦ , Ratnadira Widyasari♣ , Banani Roy♦ , Italo Santos♠ , and David Lo♣ . 2018. From Generic to Personalized: Exploring PersonaAware Code Review Explanations. In JAWs ’26: ACM 1st Journal Ahead Workshop. ACM, New York, NY, USA, 5 pages. [https://doi.org/XXXXXXX](https://doi.org/XXXXXXX). XXXXXXX  \n1 Introduction  \nCode review is a widely used technique for systematically examining code changes, aiming to increase software quality [24] . Code reviews provide several benefits for the project, including finding bugs, knowledge transfer, and assurance of adherence to project guidelines and coding style [7, 26]. An effective code review depends on active involvement and cooperation between reviewers and code authors. Prior research has identified several key characteristics of high-quality review comments, showing that explanatory feedback and a constructive tone promote understanding, whereas harsh language, superficial critiques, and impractical suggestions hinder  \nPermission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission [and/or a fee. Request permissions from permissions@acm.org](and/or a fee. Request permissions from permissions@acm.org).  \nJAWs 2026, Rio De Janeiro, Brazil  \n© 2018 Copyright held by the owner/author(s) . Publication rights licensed to ACM. ACM ISBN 978-1-4503-XXXX-X/2018/06  \n[https://doi.org/XXXXXXX.XXXXXXX](https://doi.org/XXXXXXX.XXXXXXX)  \nknowledge transfer [13, 35, 37]. Moreover, review comments are perceived as more helpful when they help build positive relationships among developers [8] . However, recent findings by Widyasari et al. [39] indicate that the interpretation of code review explanations can vary substantially across developers. What appears obvious to one developer may not be equally clear to another, which might reflect the underlying cognitive diversity in how developers reason abou","cbCainXZ4GyYps3l","https://ap.wps.com/l/cbCainXZ4GyYps3l","pdf",1601054,1,5,"English","en",105,"# Abstract\n# Introduction\n# Motivational Example","[{\"question\":\"What problem does the study address in code review communication?\",\"answer\":\"Developers can interpret the same code review comments differently, which can hinder effective communication and lead to misunderstanding or ignored feedback.\"},{\"question\":\"How does the proposed approach personalize code review explanations?\",\"answer\":\"It generates persona-aligned explanations guided by problem-solving profiling (e.g., GenderMag), aiming to tailor tone, format, and level of detail to individual differences.\"},{\"question\":\"What does the study say developers value in persona-aligned explanations?\",\"answer\":\"Across problem-solving profiles, developers favored explanatory depth, learning support, practical suggestions, and risk awareness more than conciseness, to balance personalization with clarity and 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