{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T19:50:13Z","timestamp":1782849013036,"version":"3.54.5"},"reference-count":62,"publisher":"Association for Computing Machinery (ACM)","issue":"FSE","license":[{"start":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T00:00:00Z","timestamp":1782777600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/legalcode"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Proc. ACM Softw. Eng."],"published-print":{"date-parts":[[2026,6,30]]},"abstract":"<jats:p>With the advent of powerful large language models (LLMs), research in automated software engineering has increasingly focused on leveraging these models to achieve a deeper semantic understanding of code or to engineer sophisticated agent-based processes. The predominant goal of these efforts is to enhance developer productivity through automated assistance. However, this research trajectory has largely overlooked a critical factor: the developers themselves. Programming is a deeply human and individualized activity; developers exhibit significant variation in their coding styles, tool-chain preferences, domain-specific expertise, and problem-solving strategies. Consequently, the current paradigm of one-size-fits-all code intelligence systems struggles to accommodate the unique characteristics and needs of individual developers. To address this gap, we introduce VirtualME, a novel IDE-embedded data infrastructure designed to model the developer by continuously capturing and interpreting their dynamic programming behaviors and preferences.  \nVirtualME contains three components. (1) Log-level Behavior Extraction: it captures and extracts developers' log-level behaviors (edits, navigations, etc.) from IDE. (2) Task-level Behavior Recognition: it aggregates log-level behaviors into task-level behaviors (\u201cskimming API docs\u201d, \u201citerative debugging\u201d, etc.) via a multi-agent pipeline. (3) Developer-persona Measurement: it builds a rule engine to distill a four-dimensional developer persona: Core Technical Foundation, Practical Development Efficiency, Personal Development Norms, and Technical Adaptability.  \nOn top of VirtualME, we propose a solution for personalized repository-level knowledge Q&amp;A by integrating the developer persona into a Chain-of-Thought (CoT) guided agent. We evaluated VirtualME by building a multi-repository benchmark with real-world developer trajectories, balancing correctness and personalization. Experimental results show that VirtualME-enhanced answers outperform generic baselines on five dimensions: correctness, cognitive-level fit, technology-stack relevance, behavioral-pattern alignment, and stylistic preference, yielding an average 33.80% improvement. Our results demonstrate that abundant, continuous developer-behavior data can unlock Personalized Code Intelligence. By integrating this personalized understanding into the code intelligence loop, our approach paves the new way for adaptive and personalized code intelligence.<\/jats:p>","DOI":"10.1145\/3797147","type":"journal-article","created":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T17:06:14Z","timestamp":1782839174000},"page":"435-458","source":"Crossref","is-referenced-by-count":0,"title":["On the Road to Personalized Code Intelligence: Portraiting and Assisting Developers Based on Their In-IDE Behaviors"],"prefix":"10.1145","volume":"3","author":[{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0009-0009-8747-4885","authenticated-orcid":false,"given":"Yuhong","family":"Liu","sequence":"first","affiliation":[{"name":"Beihang University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0009-0008-1266-8039","authenticated-orcid":false,"given":"Yunhe","family":"Su","sequence":"additional","affiliation":[{"name":"Beihang University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0009-0005-4258-8521","authenticated-orcid":false,"given":"Zhipeng","family":"Peng","sequence":"additional","affiliation":[{"name":"Beihang University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0009-0009-2009-5637","authenticated-orcid":false,"given":"Zhiwen","family":"Luo","sequence":"additional","affiliation":[{"name":"Beihang University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0003-1476-7213","authenticated-orcid":false,"given":"Lin","family":"Shi","sequence":"additional","affiliation":[{"name":"Beihang University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0003-1087-226X","authenticated-orcid":false,"given":"Zhi","family":"Jin","sequence":"additional","affiliation":[{"name":"Wuhan University, Wuhan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0002-2258-5893","authenticated-orcid":false,"given":"Li","family":"Zhang","sequence":"additional","affiliation":[{"name":"Beihang University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2026,6,30]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"2014. 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