The study investigates how users interact with ChatGPT for code generation beyond simple function-level tasks, focusing on project-level benchmarks that involve multi-class dependencies. A user study with 36 participants examined prompting patterns, screen recordings, and chat logs to identify Human‑LLM Interaction (HLI) features that influence productivity. The results highlight three consistently supportive HLI features, five guidelines to boost productivity, and a taxonomy of 29 runtime and logic errors with mitigation strategies.
By Sangwon Hyun, Hyunjun Kim, Jinhyuk Jang, Hyojin Choi, M. Ali Babar
arXiv:2608. 11513v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly integrated into software engineering workflows, helping developers write, debug, test, and maintain code.
By Alex Deaconu, Anubhav Gupta, Manaal Basha, Nicholas Haydu, Gema Rodr\'iguez-P\'erez
arXiv:2608. 07494v1 Announce Type: cross Abstract: AI tools like ChatGPT and DeepSeek, powered by Large Language Models (LLMs), allow users to obtain instant and effective content responses simply by typing requests, such as ``plan a three-day Vienna trip'', ``solve the attached mathematical problem'', ``draft an email to inquire review progress'', etc.
By Yiqun Zhang, Yunfan Zhang, Mingjie Zhao, Sen Feng, Yiu-ming Cheung
arXiv:2605.01392v2 Announce Type: replace-cross
Abstract: Recent advancements in Large Language Models (LLMs) have demonstrated significant potential across software engineering tasks, including soft...
By Yifei Wang, Ruiyin Li, Peng Liang, Yangxiao Cai, Zengyang Li, Mojtaba Shahin, Arif Ali Khan, Qiong Feng
arXiv:2606. 24834v1 Announce Type: new Abstract: LLM-based dialogue assistants have become mainstream tools for software developers, yet current evaluation benchmarks focus exclusively on functional correctness.
By Ali Pourghasemi Fatideh, Wilder Baldwin, Maria Dhakal, Collin McMillan, Sepideh Ghanavati
arXiv:2606. 18258v1 Announce Type: cross Abstract: Large language models (LLMs) exhibit a wide range of human-like behaviors, from expressing thoughts and emotions, to engaging in relationship-building with users, to refusing requests and maintaining boundaries.
By Sunnie S. Y. Kim, Margit Bowler, Leon A Gatys
arXiv:2609.22102v1 Announce Type: cross
Abstract: Large Language Models (LLMs) are widely used as programming assistants, yet it remains unclear whether and how user's demographic information impacts...
By Anubhav Gupta, Mayara Costa Figueiredo, Leticia Santos Machado, Tanner Wright, Ivan Beschastnikh, Cleidson R. B. de Souza, Gema Rodr\'iguez-P\'erez
arXiv:2608. 10319v1 Announce Type: cross Abstract: Large language model (LLM)-powered agents have rapidly evolved from code-completion tools into solvers of complex software engineering tasks.
By Shuyan Huang, Kai Du, Andrew Lan
arXiv:2608.27831v1 Announce Type: cross
Abstract: Coding agents are now commonly evaluated on the SWE-bench family of benchmarks, whose tasks are built from curated GitHub issues--long, structured, a...
By Gyuhyeong Kim, Hyojung Gwon, Jeonghyeon Kim, Kyuhong Shim, Sunjae Lee
arXiv:2607. 03968v1 Announce Type: cross Abstract: Large language models are increasingly deployed as IDE-integrated coding agents that decompose tasks, generate and edit files, run code, and refine outputs over many turns.
By Abhishek Kumar, Carsten Maple
arXiv:2606. 26106v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used in emotionally charged situations involving interpersonal conflict, frustration, and distress.
By Zhixing Sun, Shenghe Xu, Tao Li
arXiv:2608.22993v1 Announce Type: new
Abstract: Students increasingly use LLMs as tutors for coursework and problem solving. Little is known about the level of assistance LLMs provide when students u...
By Suhyeon Lee, Juneha Baek, Jaehyeong Park, Donghyuk Shin