| 2026 | Evaluating the Use of LLMs for Automated DOM-Level Resolution of Web Performance Issues. | Gideon Peters, SayedHassan Khatoonabadi, Emad Shihab |
| 2026 | Why Are Agentic Pull Requests Merged or Rejected? An Empirical Study. | Sien Reeve Ordonez Peralta, Fumika Hoshi, Hironori Washizaki, Naoyasu Ubayashi, Inase Kondo, Yoshiki Higo, Hiroki Mukai, Norihiro Yoshida, Kazuki Kusama, Hidetake Tanaka, Youmei Fan |
| 2026 | How Do Agents Perform Code Optimization? An Empirical Study. | Huiyun Peng, Antonio Zhong Qiu, Ricardo Andrs Calvo Mndez, Kelechi G. Kalu, James C. Davis |
| 2026 | IssuePilot: An Agentic Framework for Personalized Issue Recommendation and Onboarding in Open-Source Projects. | Shlok Pandey, Akhila Sri Manasa Venigalla |
| 2026 | When AI Code Doesn't Stick: An Empirical Study on Reverted Changes Introduced by AI Coding Agents. | Issam Oukhay, Mahi Begoug, Moataz Chouchen, Ali Ouni |
| 2026 | How do Agents Refactor: An Empirical Study. | Lukas Ottenhof, Daniel Penner, Abram Hindle, Thibaud Lutellier |
| 2026 | LLM-Based Detection of Tangled Code Changes for Higher-Quality Method-Level Bug Datasets. | Md. Nahidul Islam Opu, Shaowei Wang, Shaiful Chowdhury |
| 2026 | How Do Agentic AI Systems Address Performance Optimizations? A BERTopic-Based Analysis of Pull Requests. | Md. Nahidul Islam Opu, Shahidul Islam, Muhammad Asaduzzaman, Shaiful Alam Chowdhury |
| 2026 | An Empirical Study of Policy as Code: Adoption, Purpose, and Maintenance. | Ruben Opdebeeck, Mahmoud Alfadel, Akond Rahman, Yutaro Kashiwa, Joo F. Ferreira, Raula Gaikovina Kula, Coen De Roover |
| 2026 | How AI Coding Agents Modify Code: A Large-Scale Study of GitHub Pull Requests. | Daniel Ogenrwot, John Businge |
| 2026 | Stop Comparing Apples and Oranges: Matching for Better Results in Mining Software Repositories Studies. | Sabato Nocera, Nyyti Saarimki, Valentina Lenarduzzi, Davide Taibi, Sira Vegas |
| 2026 | Toward Linking Declined Proposals and Source Code: An Exploratory Study on the Go Repository. | Sota Nakashima, Masanari Kondo, Mahmoud Alfadel, Aly Ahmad, Toshihiro Nakae, Hidenori Matsuzaki, Yasutaka Kamei |
| 2026 | When AI Teammates Meet Code Review: Collaboration Signals Shaping the Integration of Agent-Authored Pull Requests. | Costain Nachuma, Minhaz F. Zibran |
| 2026 | Source Code Hotspots: A Diagnostic Method for Quality Issues. | Saleha Muzammil, Mughees Ur Rehman, Zoe Kotti, Diomidis Spinellis |
| 2026 | AndroT: A Dataset of Android Apps with Tests. | Hovhannes Muradyan, Mattia Fazzini |
| 2026 | Context Engineering for AI Agents in Open-Source Software. | Seyedmoein Mohsenimofidi, Matthias Galster, Christoph Treude, Sebastian Baltes |
| 2026 | How Do Agentic AI Systems Deal With Software Energy Concerns? A Pull Request-Based Study. | Tanjum Motin Mitul, Md. Masud Mazumder, Md. Nahidul Islam Opu, Shaiful Alam Chowdhury |
| 2026 | Early-Stage Prediction of Review Effort in AI-Generated Pull Requests. | Dao Sy Duy Minh, Huynh Trung Kiet, Nguyen Lam Phu Quy, Pham Phu Hoa, Tran Chi Nguyen, Nguyen Dinh Ha Duong, Truong Bao Tran |
| 2026 | Human-Agent versus Human Pull Requests: A Testing-Focused Characterization and Comparison. | Roberto Milanese, Francesco Salzano, Angelica Spina, Antonio Vitale, Remo Pareschi, Fausto Fasano, Mattia Fazzini |
| 2026 | MOOT: a Repository of many Multi-objective Optimization Tasks. | Tim Menzies, Tao Chen, Yulong Ye, Kishan Kumar Ganguly, Amirali Rayegan, Srinath Srinivasan, Andre Lustosa |
| 2026 | IntelliSA: An Intelligent Static Analyzer for IaC Security Smell Detection Using Symbolic Rules and Neural Inference. | Qiyue Mei, Michael Fu |
| 2026 | Assessing Task-based Chatbots: Snapshot and Curated Datasets for Dialogflow. | Elena Masserini, Diego Clerissi, Daniela Micucci, Leonardo Mariani |
| 2026 | OSSGameBench: A Large-Scale Dataset of Development Activities in Open-Source Video Games. | Faiz Marsad, Nimmi Weeraddana |
| 2026 | LILA: Decentralized Build Reproducibility Monitoring for the Functional Package Management Model. | Julien Malka, Arnout Engelen |
| 2026 | GLiSE: A Prompt-Driven and ML-Powered Tool for Automated Grey Literature Extraction in Software Engineering. | Brahim Mahmoudi, Zacharie Chenail-Larcher, Houcine Abdelkader Cherief, Quentin Stivenart, Naouel Moha, Florent Avellaneda |